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  1. evaluation/query_family/conditional/README.md +29 -0
  2. evaluation/query_family/conditional/analysis_report.md +43 -0
  3. evaluation/query_family/conditional/data/dataset_model_heatmap.csv +47 -0
  4. evaluation/query_family/conditional/data/dataset_model_scores.csv +511 -0
  5. evaluation/query_family/conditional/data/dataset_model_subitems.csv +0 -0
  6. evaluation/query_family/conditional/data/dataset_summary.csv +50 -0
  7. evaluation/query_family/conditional/data/duplicate_asset_audit.csv +1 -0
  8. evaluation/query_family/conditional/data/model_subitem_heatmap.csv +5 -0
  9. evaluation/query_family/conditional/data/model_summary.csv +12 -0
  10. evaluation/query_family/conditional/data/model_summary__c.csv +12 -0
  11. evaluation/query_family/conditional/data/model_summary__m.csv +12 -0
  12. evaluation/query_family/conditional/data/model_summary__n.csv +12 -0
  13. evaluation/query_family/conditional/data/prefix_plot_data.csv +13 -0
  14. evaluation/query_family/conditional/data/prefix_summary.csv +34 -0
  15. evaluation/query_family/conditional/figures/conditional_model_subitem_heatmap_appendix.tex +21 -0
  16. evaluation/query_family/conditional/final/v2/model_summary__m__v2.csv +12 -0
  17. evaluation/query_family/conditional/locality_support_diagnostics/LATEST_RUN.json +5 -0
  18. evaluation/query_family/conditional/locality_support_diagnostics/README.md +12 -25
  19. evaluation/query_family/conditional/locality_support_diagnostics/manifest.json +240 -0
  20. evaluation/query_family/conditional/manifest.json +69 -0
  21. evaluation/query_family/subgroup/README.md +29 -0
  22. evaluation/query_family/subgroup/data/dataset_model_heatmap.csv +50 -49
  23. evaluation/query_family/subgroup/data/dataset_model_scores.csv +560 -476
  24. evaluation/query_family/subgroup/data/dataset_model_subitems.csv +0 -0
  25. evaluation/query_family/subgroup/data/dataset_summary.csv +50 -49
  26. evaluation/query_family/subgroup/data/duplicate_asset_audit.csv +1 -38
  27. evaluation/query_family/subgroup/data/model_subitem_heatmap.csv +4 -4
  28. evaluation/query_family/subgroup/data/model_summary.csv +13 -13
  29. evaluation/query_family/subgroup/data/prefix_plot_data.csv +13 -13
  30. evaluation/query_family/subgroup/data/prefix_summary.csv +37 -37
  31. evaluation/query_family/subgroup/figures/subgroup_branch_dumbbell_main.tex +90 -0
  32. evaluation/query_family/subgroup/figures/subgroup_dataset_model_heatmap_appendix.tex +62 -0
  33. evaluation/query_family/subgroup/figures/subgroup_family_subitem_bars_appendix.tex +66 -0
  34. evaluation/query_family/subgroup/figures/subgroup_model_subitem_heatmap_appendix.tex +20 -0
  35. evaluation/query_family/subgroup/figures/subgroup_prefix_bars_appendix.tex +77 -0
  36. evaluation/query_family/subgroup/figures/subgroup_tradeoff_scatter_main.tex +116 -0
  37. evaluation/query_family/subgroup/final/README.md +48 -0
  38. evaluation/query_family/subgroup/final/analysis_report__v2.md +36 -0
  39. evaluation/query_family/subgroup/final/model_summary__v2.csv +13 -0
  40. evaluation/query_family/subgroup/final/prefix_summary__v2.csv +37 -0
  41. evaluation/query_family/subgroup/final/subgroup_branch_dumbbell_main__v2.tex +90 -0
  42. evaluation/query_family/subgroup/final/subgroup_dataset_model_heatmap_appendix__v2.tex +62 -0
  43. evaluation/query_family/subgroup/final/subgroup_family_subitem_bars_appendix__v2.tex +66 -0
  44. evaluation/query_family/subgroup/final/subgroup_model_subitem_heatmap_appendix__v2.tex +20 -0
  45. evaluation/query_family/subgroup/final/subgroup_model_summary_generated__v2.tex +18 -0
  46. evaluation/query_family/subgroup/final/subgroup_prefix_bars_appendix__v2.tex +77 -0
  47. evaluation/query_family/subgroup/final/subgroup_tradeoff_scatter_main__v2.tex +116 -0
  48. evaluation/query_family/subgroup/final/v2/subgroup_model_summary_generated__v2.tex +18 -0
  49. evaluation/query_family/subgroup/manifest.json +54 -0
  50. evaluation/query_family/subgroup/tables/subgroup_model_summary_generated.tex +18 -0
evaluation/query_family/conditional/README.md ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Conditional Breakdown
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+
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+ This directory contains a conditional-focused decomposition analysis built from the repository's unified `analysis` outputs.
4
+
5
+ ## Inputs
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+
7
+ - Source run: `20260526_v2_official20_plus_c2patch_plus_subgroupconditionalrepair_merged49`
8
+ - Query-level source: `Evaluation/analysis/runs/20260526_v2_official20_plus_c2patch_plus_subgroupconditionalrepair_merged49/summaries/analysis_query_scores__all_datasets.jsonl`
9
+ - Asset-level source: `Evaluation/analysis/runs/20260526_v2_official20_plus_c2patch_plus_subgroupconditionalrepair_merged49/summaries/analysis_asset_scores__all_datasets.csv`
10
+ - Canonical contract: `doc/analytics_family_subitem_contract_v1.md`
11
+
12
+ ## What this analysis exports
13
+
14
+ - deduplicated dataset-model conditional scores
15
+ - canonical three-branch conditional summaries
16
+ - a subgroup-facing derived conditional view for `direction + slice`
17
+ - paper-ready TikZ figures and LaTeX table snippets
18
+ - final copies under `Evaluation/query_fivepart_breakdown/conditional_breakdown/final/`
19
+
20
+ ## Re-run
21
+
22
+ ```bash
23
+ python src/eval/query_fivepart_breakdown/conditional_breakdown/runner.py
24
+ ```
25
+
26
+ ## TeX compilation
27
+
28
+ The runner writes standalone `.tex` files and tries `latexmk -pdf` when available.
29
+ If no local TeX compiler exists, it still exports matching preview `.pdf/.png` files for immediate inspection.
evaluation/query_family/conditional/analysis_report.md ADDED
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1
+ # Conditional Breakdown Report
2
+
3
+ ## Scope
4
+
5
+ - Source analysis run: `20260526_v2_official20_plus_c2patch_plus_subgroupconditionalrepair_merged49`
6
+ - Family analyzed: `conditional_dependency_structure`
7
+ - Excluded models: `cdtd, codi, goggle`
8
+ - Included models: `11` from the frozen README roster
9
+ - Deduplicated dataset-model panels: `510`
10
+ - Conditional query rows used: `25108`
11
+
12
+ ## Canonical and derived views
13
+
14
+ - Canonical score: `mean(dependency_strength_similarity, direction_consistency, slice_level_consistency)`
15
+ - Derived subgroup score: `mean(direction_consistency, slice_level_consistency)`
16
+ - The derived score is not a replacement for the frozen contract; it isolates the two subgroup-sensitive conditional branches for paper analysis.
17
+
18
+ ## Main findings
19
+
20
+ 1. `RealTabFormer` is the strongest model on the subgroup-facing conditional view with mean derived subgroup score `0.748`.
21
+ 2. Canonically, `RealTabFormer` leads the full conditional family with mean conditional score `0.671`.
22
+ 3. `TVAE` is the most direction-heavy model (direction minus slice = `0.167`), while `RealTabFormer` is the most slice-heavy (`0.070`).
23
+ 4. `TVAE` shows the largest strength-to-subgroup drop risk: its dependency-strength mean exceeds its subgroup-facing mean by `-0.197`.
24
+ 5. Dataset difficulty is uneven: `n9` is hardest on the subgroup-facing conditional view (`0.000` mean across models), while `n11` is easiest (`1.000`).
25
+
26
+ ## Files to use first
27
+
28
+ - `figures/conditional_subgroup_tradeoff_scatter_main.pdf`
29
+ - `figures/conditional_strength_vs_subgroup_bridge.pdf`
30
+ - `figures/conditional_branch_dumbbell_main.pdf`
31
+ - `tables/conditional_model_summary_generated.tex`
32
+ - `data/model_summary.csv`
33
+
34
+ ## README compliance note
35
+
36
+ - All plotted models are restricted to the frozen README roster with fixed colors.
37
+ - Scatter plots now use legends instead of point-side model labels, matching the README figure annotation rule.
38
+ - Model order is fixed globally instead of being re-sorted by score.
39
+
40
+ ## Prefix note
41
+
42
+ - Prefix coverage summary rows: `33`
43
+ - Prefix-level figures are exported for `c / m / n` slice checks, but the paper-facing core keeps the full deduplicated panel.
evaluation/query_family/conditional/data/dataset_model_heatmap.csv ADDED
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evaluation/query_family/conditional/data/dataset_model_scores.csv ADDED
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1
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+ c2,c,ctgan,CTGAN,0.9666667,0.9753086666666667,0.849537,20.0,27.0,9.0,0.9305041222222222,0.9124228333333333,0.12577166666666673,0.054243866666666696,3
5
+ c2,c,forestdiffusion,ForestDiffusion,0.9800000000000001,0.9814814814814815,0.915344,20.0,27.0,9.0,0.9589418271604938,0.9484127407407408,0.06613748148148146,0.031587259259259315,3
6
+ c2,c,realtabformer,RealTabFormer,1.0,1.0,1.0,20.0,27.0,9.0,1.0,1.0,0.0,0.0,3
7
+ c2,c,tabbyflow,TabbyFlow,0.7633333999999999,0.8209877407407407,0.530335,20.0,27.0,9.0,0.7048853802469135,0.6756613703703703,0.29065274074074066,0.08767202962962961,3
8
+ c2,c,tabddpm,TabDDPM,0.9666667,0.9753086666666667,0.849537,20.0,27.0,9.0,0.9305041222222222,0.9124228333333333,0.12577166666666673,0.054243866666666696,3
9
+ c2,c,tabdiff,TabDiff,0.7560607,0.8148149259259259,0.5111111111111111,20.0,27.0,9.0,0.6939955790123457,0.6629630185185185,0.3037038148148148,0.09309768148148156,3
10
+ c2,c,tabpfgen,TabPFGen,0.8625,0.8134118518518518,0.7564102222222222,20.0,27.0,9.0,0.8107740246913581,0.784911037037037,0.057001629629629624,0.07758896296296303,3
11
+ c2,c,tabsyn,TabSyn,0.8583334,0.851851962962963,0.7722223333333333,20.0,27.0,9.0,0.8274692320987654,0.8120371481481481,0.0796296296296296,0.04629625185185193,3
12
+ c2,c,tvae,TVAE,0.9800000000000001,0.986532,0.9777777777777779,20.0,27.0,9.0,0.9814365925925926,0.9821548888888889,0.008754222222222108,-0.0021548888888888174,3
13
+ c3,c,arf,ARF,1.0,1.0,,7.0,10.0,,1.0,1.0,,0.0,2
14
+ c3,c,bayesnet,BayesNet,1.0,1.0,,7.0,10.0,,1.0,1.0,,0.0,2
15
+ c3,c,ctgan,CTGAN,1.0,1.0,,7.0,10.0,,1.0,1.0,,0.0,2
16
+ c3,c,forestdiffusion,ForestDiffusion,1.0,1.0,,7.0,10.0,,1.0,1.0,,0.0,2
17
+ c3,c,realtabformer,RealTabFormer,1.0,1.0,,7.0,10.0,,1.0,1.0,,0.0,2
18
+ c3,c,tabbyflow,TabbyFlow,1.0,1.0,,7.0,10.0,,1.0,1.0,,0.0,2
19
+ c3,c,tabddpm,TabDDPM,1.0,1.0,,7.0,10.0,,1.0,1.0,,0.0,2
20
+ c3,c,tabdiff,TabDiff,1.0,1.0,,7.0,10.0,,1.0,1.0,,0.0,2
21
+ c3,c,tabpfgen,TabPFGen,1.0,1.0,,7.0,10.0,,1.0,1.0,,0.0,2
22
+ c3,c,tabsyn,TabSyn,1.0,1.0,,7.0,10.0,,1.0,1.0,,0.0,2
23
+ c3,c,tvae,TVAE,1.0,1.0,,7.0,10.0,,1.0,1.0,,0.0,2
24
+ c4,c,arf,ARF,1.0,0.98,0.9351852222222222,20.0,25.0,9.0,0.9717284074074074,0.957592611111111,0.04481477777777776,0.04240738888888895,3
25
+ c4,c,bayesnet,BayesNet,1.0,0.98,0.8888888888888888,20.0,25.0,9.0,0.9562962962962963,0.9344444444444444,0.09111111111111114,0.06555555555555559,3
26
+ c4,c,ctgan,CTGAN,1.0,0.98,0.8611111111111112,20.0,25.0,9.0,0.947037037037037,0.9205555555555556,0.11888888888888882,0.07944444444444443,3
27
+ c4,c,forestdiffusion,ForestDiffusion,0.975,0.94,0.8333333333333334,20.0,25.0,9.0,0.9161111111111112,0.8866666666666667,0.10666666666666658,0.08833333333333326,3
28
+ c4,c,realtabformer,RealTabFormer,1.0,1.0,1.0,20.0,25.0,9.0,1.0,1.0,0.0,0.0,3
29
+ c4,c,tabbyflow,TabbyFlow,0.975,0.98,0.962963,20.0,25.0,9.0,0.9726543333333334,0.9714815,0.01703699999999997,0.00351849999999998,3
30
+ c4,c,tabddpm,TabDDPM,0.975,0.96,1.0,20.0,25.0,9.0,0.9783333333333334,0.98,-0.040000000000000036,-0.0050000000000000044,3
31
+ c4,c,tabdiff,TabDiff,1.0,1.0,0.8425925555555556,20.0,25.0,9.0,0.9475308518518518,0.9212962777777778,0.15740744444444443,0.07870372222222222,3
32
+ c4,c,tabpfgen,TabPFGen,0.95,0.94,0.9722222222222222,20.0,25.0,9.0,0.954074074074074,0.9561111111111111,-0.03222222222222226,-0.006111111111111178,3
33
+ c4,c,tabsyn,TabSyn,0.975,0.96,0.898148111111111,20.0,25.0,9.0,0.9443827037037037,0.9290740555555554,0.06185188888888893,0.04592594444444453,3
34
+ c4,c,tvae,TVAE,0.975,0.94,0.8888888888888888,20.0,25.0,9.0,0.9346296296296296,0.9144444444444444,0.05111111111111111,0.060555555555555585,3
35
+ c5,c,arf,ARF,0.95,1.0,1.0,4.0,6.0,2.0,0.9833333333333334,1.0,0.0,-0.050000000000000044,3
36
+ c5,c,bayesnet,BayesNet,0.95,1.0,0.9230769999999999,4.0,6.0,2.0,0.9576923333333333,0.9615385,0.07692300000000007,-0.011538500000000007,3
37
+ c5,c,ctgan,CTGAN,0.95,1.0,1.0,4.0,6.0,2.0,0.9833333333333334,1.0,0.0,-0.050000000000000044,3
38
+ c5,c,forestdiffusion,ForestDiffusion,0.8500000000000001,0.9583333333333334,0.7,4.0,6.0,2.0,0.8361111111111112,0.8291666666666666,0.2583333333333334,0.02083333333333348,3
39
+ c5,c,realtabformer,RealTabFormer,0.95,1.0,1.0,4.0,6.0,2.0,0.9833333333333334,1.0,0.0,-0.050000000000000044,3
40
+ c5,c,tabbyflow,TabbyFlow,0.9,1.0,1.0,4.0,6.0,2.0,0.9666666666666667,1.0,0.0,-0.09999999999999998,3
41
+ c5,c,tabddpm,TabDDPM,0.95,0.9583333333333334,0.9230769999999999,4.0,6.0,2.0,0.9438034444444444,0.9407051666666666,0.035256333333333445,0.009294833333333363,3
42
+ c5,c,tabdiff,TabDiff,0.95,1.0,0.9230769999999999,4.0,6.0,2.0,0.9576923333333333,0.9615385,0.07692300000000007,-0.011538500000000007,3
43
+ c5,c,tabpfgen,TabPFGen,0.97222225,1.0,1.0,4.0,6.0,2.0,0.99074075,1.0,0.0,-0.027777750000000045,3
44
+ c5,c,tabsyn,TabSyn,0.95,0.9166666666666666,0.9230769999999999,4.0,6.0,2.0,0.9299145555555555,0.9198718333333333,-0.006410333333333296,0.030128166666666623,3
45
+ c5,c,tvae,TVAE,0.95,0.9166666666666666,0.9230769999999999,4.0,6.0,2.0,0.9299145555555555,0.9198718333333333,-0.006410333333333296,0.030128166666666623,3
46
+ c6,c,arf,ARF,0.2947661111111111,0.5555556666666667,0.45838975000000004,9.0,3.0,16.0,0.436237175925926,0.5069727083333333,0.09716591666666663,-0.21220659722222218,3
47
+ c6,c,bayesnet,BayesNet,0.28106177777777774,0.5711913333333333,0.5042176875000001,9.0,3.0,16.0,0.45215693287037034,0.5377045104166667,0.0669736458333332,-0.2566427326388889,3
48
+ c6,c,ctgan,CTGAN,0.31731933333333334,0.5555556666666667,0.4320315,9.0,3.0,16.0,0.4349688333333333,0.49379358333333334,0.12352416666666666,-0.17647425,3
49
+ c6,c,forestdiffusion,ForestDiffusion,0.18498,0.5437500000000001,0.3816501875,9.0,3.0,16.0,0.3701267291666667,0.46270009375000004,0.16209981250000005,-0.27772009375000006,3
50
+ c6,c,realtabformer,RealTabFormer,0.48381399999999997,0.5745216666666667,0.5466451250000001,9.0,3.0,16.0,0.5349935972222223,0.5605833958333334,0.027876541666666643,-0.07676939583333342,3
51
+ c6,c,tabbyflow,TabbyFlow,0.22148733333333334,0.56806,0.50008775,9.0,3.0,16.0,0.42987836111111116,0.534073875,0.06797224999999996,-0.31258654166666666,3
52
+ c6,c,tabddpm,TabDDPM,0.2566248888888889,0.5525666666666668,0.439969375,9.0,3.0,16.0,0.41638697685185183,0.4962680208333334,0.11259729166666677,-0.23964313194444448,3
53
+ c6,c,tabdiff,TabDiff,0.21521877777777776,0.55,0.4394226875,9.0,3.0,16.0,0.4015471550925926,0.49471134375000003,0.11057731250000002,-0.2794925659722223,3
54
+ c6,c,tabpfgen,TabPFGen,0.30512633333333333,0.578,0.51876475,9.0,3.0,16.0,0.4672970277777777,0.548382375,0.05923524999999996,-0.24325604166666664,3
55
+ c6,c,tabsyn,TabSyn,0.2713772222222222,0.5647296666666667,0.45763275000000003,9.0,3.0,16.0,0.4312465462962963,0.5111812083333334,0.10709691666666665,-0.23980398611111114,3
56
+ c6,c,tvae,TVAE,0.3280121111111111,0.5711913333333333,0.45520312500000004,9.0,3.0,16.0,0.4514688564814815,0.5131972291666667,0.11598820833333323,-0.18518511805555554,3
57
+ c7,c,arf,ARF,0.99,0.983013037037037,0.9659091111111111,20.0,27.0,9.0,0.9796407160493826,0.974461074074074,0.01710392592592591,0.015538925925925984,3
58
+ c7,c,bayesnet,BayesNet,0.9688888999999999,0.9825372592592593,0.9580408888888888,20.0,27.0,9.0,0.9698223493827159,0.970289074074074,0.024496370370370446,-0.001400174074074112,3
59
+ c7,c,ctgan,CTGAN,0.99,0.9790123703703704,0.9594444444444444,20.0,27.0,9.0,0.9761522716049383,0.9692284074074073,0.019567925925925933,0.020771592592592647,3
60
+ c7,c,forestdiffusion,ForestDiffusion,0.99,0.9790123703703704,0.9594444444444444,20.0,27.0,9.0,0.9761522716049383,0.9692284074074073,0.019567925925925933,0.020771592592592647,3
61
+ c7,c,realtabformer,RealTabFormer,0.9688888999999999,0.9825372592592593,0.9719297777777778,20.0,27.0,9.0,0.9744519790123457,0.9772335185185186,0.010607481481481495,-0.008344618518518643,3
62
+ c7,c,tabbyflow,TabbyFlow,0.9188889,0.9558488148148149,0.9249999999999999,20.0,27.0,9.0,0.9332459049382716,0.9404244074074074,0.03084881481481494,-0.021535507407407395,3
63
+ c7,c,tabddpm,TabDDPM,0.9800000000000001,0.989418,0.9480158888888889,20.0,27.0,9.0,0.9724779629629631,0.9687169444444444,0.04140211111111114,0.011283055555555643,3
64
+ c7,c,tabdiff,TabDiff,0.9400000000000001,0.9648735555555555,0.9381313333333333,20.0,27.0,9.0,0.9476682962962962,0.9515024444444444,0.026742222222222223,-0.01150244444444437,3
65
+ c7,c,tabpfgen,TabPFGen,0.9044444,0.8916708148148148,0.774269,20.0,27.0,9.0,0.8567947382716049,0.8329699074074074,0.11740181481481482,0.07147449259259264,3
66
+ c7,c,tabsyn,TabSyn,0.9188889,0.9558488148148149,0.930263111111111,20.0,27.0,9.0,0.935000275308642,0.9430559629629629,0.025585703703703833,-0.024167062962962893,3
67
+ c7,c,tvae,TVAE,0.9688888999999999,0.9768392592592592,0.9126148888888888,20.0,27.0,9.0,0.9527810160493826,0.944727074074074,0.06422437037037043,0.024161825925925973,3
68
+ c8,c,arf,ARF,1.0,1.0,1.0,27.0,19.0,12.0,1.0,1.0,0.0,0.0,3
69
+ c8,c,bayesnet,BayesNet,1.0,1.0,1.0,27.0,19.0,12.0,1.0,1.0,0.0,0.0,3
70
+ c8,c,ctgan,CTGAN,1.0,1.0,0.9722221666666666,27.0,19.0,12.0,0.9907407222222222,0.9861110833333333,0.02777783333333339,0.013888916666666695,3
71
+ c8,c,forestdiffusion,ForestDiffusion,0.8888888888888888,1.0,0.9861110833333333,27.0,19.0,12.0,0.958333324074074,0.9930555416666667,0.013888916666666695,-0.10416665277777781,3
72
+ c8,c,realtabformer,RealTabFormer,1.0,1.0,0.9861110833333333,27.0,19.0,12.0,0.9953703611111111,0.9930555416666667,0.013888916666666695,0.006944458333333348,3
73
+ c8,c,tabbyflow,TabbyFlow,0.8395062222222223,1.0,0.7500002499999999,27.0,19.0,12.0,0.8631688240740741,0.8750001249999999,0.24999975000000008,-0.03549390277777764,3
74
+ c8,c,tabddpm,TabDDPM,0.8395062222222223,1.0,0.740741,27.0,19.0,12.0,0.8600824074074075,0.8703704999999999,0.259259,-0.03086427777777767,3
75
+ c8,c,tabdiff,TabDiff,0.8641974814814815,1.0,0.8240740833333332,27.0,19.0,12.0,0.8960905216049383,0.9120370416666665,0.1759259166666668,-0.04783956018518509,3
76
+ c8,c,tabpfgen,TabPFGen,1.0,1.0,0.95833325,27.0,19.0,12.0,0.9861110833333333,0.979166625,0.041666749999999975,0.020833375000000043,3
77
+ c8,c,tabsyn,TabSyn,0.9753085925925925,1.0,0.8287036666666667,27.0,19.0,12.0,0.9346707530864197,0.9143518333333334,0.17129633333333327,0.06095675925925914,3
78
+ c8,c,tvae,TVAE,0.8703704444444443,1.0,0.6851853333333334,27.0,19.0,12.0,0.851851925925926,0.8425926666666668,0.3148146666666666,0.027777777777777568,3
79
+ c9,c,arf,ARF,0.07142857142857142,0.16666666666666666,0.0,28.0,12.0,9.0,0.07936507936507936,0.08333333333333333,0.16666666666666666,-0.011904761904761904,3
80
+ c9,c,bayesnet,BayesNet,0.08138992857142857,0.1929205833333333,0.004517888888888889,28.0,12.0,9.0,0.09294280026455025,0.0987192361111111,0.18840269444444444,-0.017329307539682523,3
81
+ c9,c,ctgan,CTGAN,0.07848385714285713,0.19081966666666664,0.002382444444444445,28.0,12.0,9.0,0.09056198941798942,0.09660105555555554,0.1884372222222222,-0.018117198412698404,3
82
+ c9,c,forestdiffusion,ForestDiffusion,0.07142857142857142,0.16666666666666666,0.0,28.0,12.0,9.0,0.07936507936507936,0.08333333333333333,0.16666666666666666,-0.011904761904761904,3
83
+ c9,c,realtabformer,RealTabFormer,0.7930757857142857,0.9703620000000001,0.8679631111111111,28.0,12.0,9.0,0.8771336322751323,0.9191625555555556,0.10239888888888893,-0.12608676984126987,3
84
+ c9,c,tabbyflow,TabbyFlow,0.07142857142857142,0.16666666666666666,0.0,28.0,12.0,9.0,0.07936507936507936,0.08333333333333333,0.16666666666666666,-0.011904761904761904,3
85
+ c9,c,tabddpm,TabDDPM,0.07142857142857142,0.16666666666666666,0.0,28.0,12.0,9.0,0.07936507936507936,0.08333333333333333,0.16666666666666666,-0.011904761904761904,3
86
+ c9,c,tabdiff,TabDiff,0.07142857142857142,0.16666666666666666,0.0,28.0,12.0,9.0,0.07936507936507936,0.08333333333333333,0.16666666666666666,-0.011904761904761904,3
87
+ c9,c,tabpfgen,TabPFGen,0.07142857142857142,0.16666666666666666,0.0,28.0,12.0,9.0,0.07936507936507936,0.08333333333333333,0.16666666666666666,-0.011904761904761904,3
88
+ c9,c,tabsyn,TabSyn,0.07142857142857142,0.16666666666666666,0.0,28.0,12.0,9.0,0.07936507936507936,0.08333333333333333,0.16666666666666666,-0.011904761904761904,3
89
+ c9,c,tvae,TVAE,0.07918557142857142,0.1930571666666667,0.0036004444444444447,28.0,12.0,9.0,0.09194772751322754,0.09832880555555557,0.18945672222222226,-0.01914323412698414,3
90
+ c10,c,arf,ARF,0.8894215833333333,1.0,0.9614447777777778,24.0,12.0,9.0,0.950288787037037,0.980722388888889,0.038555222222222185,-0.09130080555555564,3
91
+ c10,c,bayesnet,BayesNet,0.8887675833333333,1.0,0.9527777777777777,24.0,12.0,9.0,0.9471817870370369,0.9763888888888889,0.047222222222222276,-0.08762130555555558,3
92
+ c10,c,ctgan,CTGAN,0.8053142083333333,0.9500000000000001,0.822856,24.0,12.0,9.0,0.8593900694444446,0.886428,0.12714400000000003,-0.08111379166666666,3
93
+ c10,c,forestdiffusion,ForestDiffusion,0.886537,1.0,0.9527777777777777,24.0,12.0,9.0,0.9464382592592594,0.9763888888888889,0.047222222222222276,-0.08985188888888884,3
94
+ c10,c,realtabformer,RealTabFormer,1.0,1.0,1.0,24.0,12.0,9.0,1.0,1.0,0.0,0.0,3
95
+ c10,c,tabbyflow,TabbyFlow,0.8748426666666668,0.9833333333333334,0.9402649999999999,24.0,12.0,9.0,0.9328136666666668,0.9617991666666666,0.043068333333333486,-0.08695649999999988,3
96
+ c10,c,tabddpm,TabDDPM,0.8933833333333333,1.0,0.952347111111111,24.0,12.0,9.0,0.9485768148148148,0.9761735555555555,0.04765288888888897,-0.08279022222222221,3
97
+ c10,c,tabdiff,TabDiff,0.8930760833333333,1.0,0.9577692222222223,24.0,12.0,9.0,0.9502817685185185,0.9788846111111111,0.04223077777777773,-0.08580852777777781,3
98
+ c10,c,tabpfgen,TabPFGen,0.7991980416666666,0.9583333333333334,0.7716853333333333,24.0,12.0,9.0,0.843072236111111,0.8650093333333333,0.18664800000000004,-0.06581129166666666,3
99
+ c10,c,tvae,TVAE,0.7343536249999999,0.89230775,0.7336876666666666,24.0,12.0,9.0,0.7867830138888888,0.8129977083333333,0.15862008333333333,-0.07864408333333339,3
100
+ c11,c,arf,ARF,0.9814815,0.9393004444444444,0.8564814444444444,18.0,27.0,9.0,0.9257544629629629,0.8978909444444444,0.08281899999999998,0.08359055555555561,3
101
+ c11,c,bayesnet,BayesNet,0.9814815,0.9341564444444445,0.9506173333333332,18.0,27.0,9.0,0.9554184259259259,0.9423868888888889,-0.016460888888888747,0.03909461111111112,3
102
+ c11,c,ctgan,CTGAN,0.9814815,0.9341564444444445,0.8287036666666666,18.0,27.0,9.0,0.914780537037037,0.8814300555555555,0.10545277777777784,0.10005144444444447,3
103
+ c11,c,forestdiffusion,ForestDiffusion,0.9691358333333334,0.9393004444444444,0.8130511111111112,18.0,27.0,9.0,0.907162462962963,0.8761757777777778,0.1262493333333332,0.09296005555555564,3
104
+ c11,c,realtabformer,RealTabFormer,1.0,1.0,1.0,18.0,27.0,9.0,1.0,1.0,0.0,0.0,3
105
+ c11,c,tabbyflow,TabbyFlow,0.9814815,0.9753085925925925,0.968254,18.0,27.0,9.0,0.9750146975308641,0.9717812962962962,0.007054592592592557,0.009700203703703836,3
106
+ c11,c,tabddpm,TabDDPM,0.9814815,0.9629629259259259,0.9814814444444444,18.0,27.0,9.0,0.9753086234567901,0.9722221851851851,-0.01851851851851849,0.0092593148148149,3
107
+ c11,c,tabdiff,TabDiff,0.9876543333333334,0.9876542962962963,0.9179893333333333,18.0,27.0,9.0,0.9644326543209877,0.9528218148148149,0.06966496296296298,0.03483251851851854,3
108
+ c11,c,tabpfgen,TabPFGen,1.0,0.9753086296296296,1.0,18.0,27.0,9.0,0.9917695432098764,0.9876543148148148,-0.02469137037037039,0.012345685185185196,3
109
+ c11,c,tabsyn,TabSyn,0.9814815,0.9351852222222222,0.9537036666666666,18.0,27.0,9.0,0.9567901296296296,0.9444444444444444,-0.018518444444444393,0.03703705555555559,3
110
+ c11,c,tvae,TVAE,0.9814815,0.9876542962962963,0.968254,18.0,27.0,9.0,0.9791299320987653,0.9779541481481482,0.01940029629629636,0.003527351851851823,3
111
+ c12,c,arf,ARF,0.1539865,,,2.0,,,0.1539865,,,,1
112
+ c12,c,bayesnet,BayesNet,0.409747,,,2.0,,,0.409747,,,,1
113
+ c12,c,ctgan,CTGAN,0.3362465,,,2.0,,,0.3362465,,,,1
114
+ c12,c,forestdiffusion,ForestDiffusion,0.0266285,,,2.0,,,0.0266285,,,,1
115
+ c12,c,realtabformer,RealTabFormer,0.6854435,,,2.0,,,0.6854435,,,,1
116
+ c12,c,tabpfgen,TabPFGen,0.128909,,,2.0,,,0.128909,,,,1
117
+ c12,c,tabsyn,TabSyn,0.3028675,,,2.0,,,0.3028675,,,,1
118
+ c12,c,tvae,TVAE,0.37351900000000005,,,2.0,,,0.37351900000000005,,,,1
119
+ c13,c,arf,ARF,0.0,,,4.0,,,0.0,,,,1
120
+ c13,c,bayesnet,BayesNet,0.0,,,4.0,,,0.0,,,,1
121
+ c13,c,ctgan,CTGAN,0.104409,,,4.0,,,0.104409,,,,1
122
+ c13,c,forestdiffusion,ForestDiffusion,0.0,,,4.0,,,0.0,,,,1
123
+ c13,c,realtabformer,RealTabFormer,0.28305175,,,4.0,,,0.28305175,,,,1
124
+ c13,c,tabbyflow,TabbyFlow,0.0,,,4.0,,,0.0,,,,1
125
+ c13,c,tabddpm,TabDDPM,0.0,,,4.0,,,0.0,,,,1
126
+ c13,c,tabdiff,TabDiff,0.0,,,4.0,,,0.0,,,,1
127
+ c13,c,tabpfgen,TabPFGen,0.0,,,4.0,,,0.0,,,,1
128
+ c13,c,tabsyn,TabSyn,0.0,,,4.0,,,0.0,,,,1
129
+ c13,c,tvae,TVAE,0.12581475,,,4.0,,,0.12581475,,,,1
130
+ c14,c,arf,ARF,0.653744423076923,1.0,1.0,26.0,13.0,9.0,0.8845814743589743,1.0,0.0,-0.34625557692307696,3
131
+ c14,c,bayesnet,BayesNet,0.29366703846153847,1.0,1.0,26.0,13.0,9.0,0.7645556794871795,1.0,0.0,-0.7063329615384615,3
132
+ c14,c,ctgan,CTGAN,0.5006375384615385,1.0,0.8148147777777778,26.0,13.0,9.0,0.7718174387464387,0.9074073888888889,0.18518522222222222,-0.4067698504273505,3
133
+ c14,c,forestdiffusion,ForestDiffusion,0.21794873076923077,0.8076923076923077,0.3055555555555556,26.0,13.0,9.0,0.443732198005698,0.5566239316239316,0.5021367521367521,-0.3386752008547009,3
134
+ c14,c,realtabformer,RealTabFormer,0.6700410384615385,1.0,1.0,26.0,13.0,9.0,0.8900136794871795,1.0,0.0,-0.3299589615384615,3
135
+ c14,c,tabbyflow,TabbyFlow,0.22662723076923078,1.0,1.0,26.0,13.0,9.0,0.742209076923077,1.0,0.0,-0.7733727692307693,3
136
+ c14,c,tabddpm,TabDDPM,0.05187376923076922,0.3974359230769231,0.18055555555555555,26.0,13.0,9.0,0.20995508262108264,0.28899573931623934,0.21688036752136755,-0.23712197008547012,3
137
+ c14,c,tabdiff,TabDiff,0.23076923076923078,1.0,1.0,26.0,13.0,9.0,0.7435897435897436,1.0,0.0,-0.7692307692307692,3
138
+ c14,c,tabpfgen,TabPFGen,0.6575195769230769,1.0,1.0,26.0,13.0,9.0,0.885839858974359,1.0,0.0,-0.34248042307692306,3
139
+ c14,c,tabsyn,TabSyn,0.23076923076923078,1.0,1.0,26.0,13.0,9.0,0.7435897435897436,1.0,0.0,-0.7692307692307692,3
140
+ c14,c,tvae,TVAE,0.24778442307692308,0.820512923076923,0.4537036666666666,26.0,13.0,9.0,0.5073336709401709,0.6371082948717948,0.3668092564102564,-0.3893238717948717,3
141
+ c15,c,arf,ARF,0.6374143461538462,0.9166667500000001,0.9333333333333333,26.0,12.0,9.0,0.8291381431623931,0.9250000416666667,-0.016666583333333262,-0.28758569551282054,3
142
+ c15,c,bayesnet,BayesNet,0.5038798076923077,0.7735616666666667,0.5243387777777778,26.0,12.0,9.0,0.6005934173789175,0.6489502222222223,0.24922288888888888,-0.14507041452991465,3
143
+ c15,c,ctgan,CTGAN,0.5106774230769231,0.8333332499999999,0.5555555555555556,26.0,12.0,9.0,0.6331887428774928,0.6944444027777777,0.27777769444444433,-0.18376697970085465,3
144
+ c15,c,forestdiffusion,ForestDiffusion,0.18066723076923077,0.6413866666666667,0.1059061111111111,26.0,12.0,9.0,0.30932000284900285,0.3736463888888889,0.5354805555555555,-0.19297915811965813,3
145
+ c15,c,realtabformer,RealTabFormer,0.6623377692307693,1.0,1.0,26.0,12.0,9.0,0.887445923076923,1.0,0.0,-0.33766223076923074,3
146
+ c15,c,tabbyflow,TabbyFlow,0.16266623076923076,0.6781513333333334,0.41303311111111113,26.0,12.0,9.0,0.4179502250712251,0.5455922222222223,0.2651182222222223,-0.3829259914529915,3
147
+ c15,c,tabdiff,TabDiff,0.18066723076923077,0.6830533333333334,0.41303311111111113,26.0,12.0,9.0,0.4255845584045584,0.5480432222222222,0.2700202222222223,-0.3673759914529915,3
148
+ c15,c,tabpfgen,TabPFGen,0.4957123461538462,0.7735616666666667,0.5243387777777778,26.0,12.0,9.0,0.5978709301994303,0.6489502222222223,0.24922288888888888,-0.15323787606837613,3
149
+ c15,c,tabsyn,TabSyn,0.18066723076923077,0.6830533333333334,0.41303311111111113,26.0,12.0,9.0,0.4255845584045584,0.5480432222222222,0.2700202222222223,-0.3673759914529915,3
150
+ c15,c,tvae,TVAE,0.12212961538461539,0.5369543333333333,0.18395066666666668,26.0,12.0,9.0,0.2810115384615385,0.3604525,0.3530036666666666,-0.23832288461538462,3
151
+ c16,c,arf,ARF,0.3308031724137931,0.875,0.609646,29.0,16.0,9.0,0.605149724137931,0.7423230000000001,0.265354,-0.411519827586207,3
152
+ c16,c,bayesnet,BayesNet,0.3148933448275862,0.6586805,0.3335896666666667,29.0,16.0,9.0,0.4357211704980843,0.49613508333333334,0.32509083333333333,-0.18124173850574715,3
153
+ c16,c,ctgan,CTGAN,0.2670693793103448,0.875,0.3133617777777778,29.0,16.0,9.0,0.48514371902937414,0.5941808888888889,0.5616382222222223,-0.32711150957854407,3
154
+ c16,c,forestdiffusion,ForestDiffusion,0.16091955172413794,0.6687500625,0.14658855555555558,29.0,16.0,9.0,0.32541938992656455,0.4076693090277778,0.5221615069444444,-0.24674975730363988,3
155
+ c16,c,realtabformer,RealTabFormer,0.43761003448275865,0.8378930625000001,0.5993817777777778,29.0,16.0,9.0,0.6249616249201789,0.718637420138889,0.23851128472222227,-0.28102738565613034,3
156
+ c16,c,tabbyflow,TabbyFlow,0.05686631034482758,0.3247806875,0.031420444444444445,29.0,16.0,9.0,0.13768914742975735,0.17810056597222224,0.2933602430555555,-0.12123425562739465,3
157
+ c16,c,tabdiff,TabDiff,0.15577737931034483,0.583443,0.23866833333333334,29.0,16.0,9.0,0.3259629042145594,0.4110556666666667,0.3447746666666667,-0.25527828735632185,3
158
+ c16,c,tabsyn,TabSyn,0.12915913793103448,0.6008225625,0.2395587777777778,29.0,16.0,9.0,0.32318015940293743,0.4201906701388889,0.3612637847222222,-0.2910315322078544,3
159
+ c16,c,tvae,TVAE,0.1313233448275862,0.43890687500000003,0.11237366666666666,29.0,16.0,9.0,0.22753462883141765,0.27564027083333337,0.3265332083333334,-0.14431692600574716,3
160
+ c17,c,arf,ARF,0.5076849999999999,0.32122639999999997,0.6467094666666667,25.0,15.0,15.0,0.4918736222222222,0.4839679333333333,-0.32548306666666676,0.02371706666666662,3
161
+ c17,c,bayesnet,BayesNet,0.55681272,0.3215408666666667,0.6828321333333334,25.0,15.0,15.0,0.52039524,0.5021865000000001,-0.36129126666666667,0.05462621999999995,3
162
+ c17,c,ctgan,CTGAN,0.44405192,0.8915662,0.7646584666666667,25.0,15.0,15.0,0.7000921955555555,0.8281123333333333,0.12690773333333327,-0.38406041333333335,3
163
+ c17,c,forestdiffusion,ForestDiffusion,0.28272828,0.24166666666666667,0.5434384,25.0,15.0,15.0,0.35594444888888893,0.39255253333333334,-0.3017717333333333,-0.10982425333333334,3
164
+ c17,c,realtabformer,RealTabFormer,0.27521104,0.3790034666666667,0.4499386,25.0,15.0,15.0,0.3680510355555556,0.41447103333333335,-0.07093513333333334,-0.13925999333333333,3
165
+ c17,c,tabbyflow,TabbyFlow,0.1724814,0.14166666666666666,0.2884683333333333,25.0,15.0,15.0,0.20087213333333334,0.2150675,-0.14680166666666666,-0.04258609999999999,3
166
+ c17,c,tabdiff,TabDiff,0.30946999999999997,0.25098040000000005,0.5783262666666666,25.0,15.0,15.0,0.3795922222222223,0.4146533333333333,-0.3273458666666666,-0.10518333333333335,3
167
+ c17,c,tabpfgen,TabPFGen,0.45091556,0.31776726666666666,0.6816842,25.0,15.0,15.0,0.4834556755555555,0.4997257333333333,-0.3639169333333333,-0.04881017333333332,3
168
+ c17,c,tabsyn,TabSyn,0.30884676,0.2431372,0.5922299333333334,25.0,15.0,15.0,0.38140463111111117,0.41768356666666673,-0.3490927333333334,-0.10883680666666673,3
169
+ c17,c,tvae,TVAE,0.35965072,0.8384903333333333,0.6464926666666667,25.0,15.0,15.0,0.6148779066666666,0.7424915000000001,0.19199766666666662,-0.3828407800000001,3
170
+ c18,c,arf,ARF,0.2393662608695652,0.42769041666666663,0.03838444444444444,23.0,12.0,9.0,0.23514704066022543,0.23303743055555554,0.3893059722222222,0.006328830314009659,3
171
+ c18,c,bayesnet,BayesNet,0.1697585652173913,0.4040223333333333,0.04309611111111111,23.0,12.0,9.0,0.2056256698872786,0.22355922222222221,0.3609262222222222,-0.053800657004830915,3
172
+ c18,c,ctgan,CTGAN,0.20303756521739127,0.44963816666666667,0.08297,23.0,12.0,9.0,0.24521524396135264,0.26630408333333333,0.3666681666666667,-0.06326651811594206,3
173
+ c18,c,forestdiffusion,ForestDiffusion,0.11476295652173914,0.4891980833333333,0.01960133333333333,23.0,12.0,9.0,0.20785412439613526,0.2543997083333333,0.46959675,-0.13963675181159418,3
174
+ c18,c,realtabformer,RealTabFormer,0.7022593913043479,0.6857498333333334,0.5696074444444444,23.0,12.0,9.0,0.6525388896940418,0.6276786388888889,0.11614238888888895,0.07458075241545903,3
175
+ c18,c,tabbyflow,TabbyFlow,0.06577921739130435,0.29662041666666666,0.04997822222222222,23.0,12.0,9.0,0.13745928542673108,0.17329931944444443,0.24664219444444443,-0.10752010205314008,3
176
+ c18,c,tvae,TVAE,0.20831860869565216,0.46769558333333333,0.10203277777777778,23.0,12.0,9.0,0.25934898993558775,0.28486418055555557,0.3656628055555555,-0.0765455718599034,3
177
+ c19,c,arf,ARF,0.8284340384615384,1.0,0.962963,26.0,13.0,9.0,0.9304656794871796,0.9814815,0.03703699999999999,-0.1530474615384616,3
178
+ c19,c,bayesnet,BayesNet,0.3196203076923077,1.0,0.6670978888888889,26.0,13.0,9.0,0.6622393988603988,0.8335489444444444,0.3329021111111111,-0.5139286367521367,3
179
+ c19,c,ctgan,CTGAN,0.33464130769230765,0.8653846153846154,0.24153444444444444,26.0,13.0,9.0,0.4805201225071225,0.55345952991453,0.6238501709401709,-0.2188182222222223,3
180
+ c19,c,forestdiffusion,ForestDiffusion,0.13058546153846154,0.8846153846153846,0.2830331111111111,26.0,13.0,9.0,0.43274465242165244,0.5838242478632478,0.6015822735042735,-0.4532387863247863,3
181
+ c19,c,realtabformer,RealTabFormer,0.2109588076923077,0.5192307692307693,0.48886466666666667,26.0,13.0,9.0,0.4063514145299145,0.5040477179487179,0.030366102564102604,-0.29308891025641026,3
182
+ c19,c,tabbyflow,TabbyFlow,0.10291796153846154,0.6346153846153846,0.2281567777777778,26.0,13.0,9.0,0.321896707977208,0.4313860811965812,0.4064586068376068,-0.3284681196581196,3
183
+ c19,c,tabdiff,TabDiff,0.12529626923076922,0.8846153846153846,0.28649544444444447,26.0,13.0,9.0,0.43213569943019947,0.5855554145299146,0.5981199401709401,-0.46025914529914536,3
184
+ c19,c,tabpfgen,TabPFGen,0.5555224615384616,1.0,0.7086243333333333,26.0,13.0,9.0,0.7547155982905983,0.8543121666666667,0.2913756666666667,-0.298789705128205,3
185
+ c19,c,tabsyn,TabSyn,0.2675277692307692,0.7596153846153846,0.4709876666666667,26.0,13.0,9.0,0.4993769401709402,0.6153015256410257,0.2886277179487179,-0.3477737564102565,3
186
+ c19,c,tvae,TVAE,0.29332326923076923,0.875,0.25343922222222226,26.0,13.0,9.0,0.4739208304843305,0.5642196111111111,0.6215607777777777,-0.27089634188034184,3
187
+ c20,c,arf,ARF,0.8023807999999999,,,5.0,,,0.8023807999999999,,,,1
188
+ c20,c,bayesnet,BayesNet,0.8023807999999999,,,5.0,,,0.8023807999999999,,,,1
189
+ c20,c,ctgan,CTGAN,0.7037036000000001,,,5.0,,,0.7037036000000001,,,,1
190
+ c20,c,forestdiffusion,ForestDiffusion,0.7589742,,,5.0,,,0.7589742,,,,1
191
+ c20,c,realtabformer,RealTabFormer,0.754,,,5.0,,,0.754,,,,1
192
+ c20,c,tabbyflow,TabbyFlow,0.754,,,5.0,,,0.754,,,,1
193
+ c20,c,tabddpm,TabDDPM,0.38814800000000005,,,5.0,,,0.38814800000000005,,,,1
194
+ c20,c,tabpfgen,TabPFGen,0.7666666,,,5.0,,,0.7666666,,,,1
195
+ c20,c,tabsyn,TabSyn,0.6936508,,,5.0,,,0.6936508,,,,1
196
+ c20,c,tvae,TVAE,0.6951612,,,5.0,,,0.6951612,,,,1
197
+ m1,m,arf,ARF,0.40099066666666666,1.0,1.0,27.0,17.0,9.0,0.8003302222222223,1.0,0.0,-0.5990093333333333,3
198
+ m1,m,bayesnet,BayesNet,0.5815514444444444,1.0,1.0,27.0,17.0,9.0,0.8605171481481482,1.0,0.0,-0.4184485555555556,3
199
+ m1,m,ctgan,CTGAN,0.5230874074074074,1.0,0.9888888888888889,27.0,17.0,9.0,0.8373254320987655,0.9944444444444445,0.011111111111111072,-0.471357037037037,3
200
+ m1,m,forestdiffusion,ForestDiffusion,0.26354118518518516,0.9431372352941176,0.8388888888888889,27.0,17.0,9.0,0.6818557697893972,0.8910130620915033,0.10424834640522873,-0.6274718769063181,3
201
+ m1,m,realtabformer,RealTabFormer,0.28689403703703703,0.9215685882352941,0.6981481111111111,27.0,17.0,9.0,0.6355369121278142,0.8098583496732026,0.223420477124183,-0.5229643126361656,3
202
+ m1,m,tabbyflow,TabbyFlow,0.2791441851851852,0.9901960588235293,0.8666666666666667,27.0,17.0,9.0,0.7120023035584605,0.928431362745098,0.12352939215686265,-0.6492871775599127,3
203
+ m1,m,tabddpm,TabDDPM,0.12989522222222222,0.8588235294117647,0.7851852222222222,27.0,17.0,9.0,0.5913013246187363,0.8220043758169935,0.07363830718954245,-0.6921091535947712,3
204
+ m1,m,tabdiff,TabDiff,0.2868574814814815,1.0,0.8833333333333333,27.0,17.0,9.0,0.7233969382716049,0.9416666666666667,0.1166666666666667,-0.6548091851851852,3
205
+ m1,m,tabpfgen,TabPFGen,0.3719654074074074,0.960784294117647,1.0,27.0,17.0,9.0,0.7775832338416849,0.9803921470588235,-0.039215705882353014,-0.608426739651416,3
206
+ m1,m,tabsyn,TabSyn,0.2649444814814815,1.0,0.8888888888888888,27.0,17.0,9.0,0.7179444567901235,0.9444444444444444,0.11111111111111116,-0.679499962962963,3
207
+ m1,m,tvae,TVAE,0.3661480740740741,0.667647,0.5777777777777778,27.0,17.0,9.0,0.537190950617284,0.6227123888888889,0.08986922222222216,-0.2565643148148148,3
208
+ m2,m,arf,ARF,0.3451810625,0.51216128,0.33852910526315794,32.0,25.0,19.0,0.39862381592105267,0.425345192631579,0.17363217473684212,-0.08016413013157897,3
209
+ m2,m,bayesnet,BayesNet,0.373383375,0.54814372,0.3381604210526316,32.0,25.0,19.0,0.4198958386842106,0.4431520705263158,0.2099832989473684,-0.06976869552631576,3
210
+ m2,m,ctgan,CTGAN,0.33162825,0.50778816,0.33798547368421056,32.0,25.0,19.0,0.39246729456140356,0.4228868168421053,0.1698026863157895,-0.09125856684210526,3
211
+ m2,m,forestdiffusion,ForestDiffusion,0.26402471875,0.47979488000000003,0.34382178947368425,32.0,25.0,19.0,0.3625471294078948,0.41180833473684214,0.1359730905263158,-0.14778361598684214,3
212
+ m2,m,realtabformer,RealTabFormer,0.371734625,0.55924984,0.43772373684210525,32.0,25.0,19.0,0.45623606728070176,0.49848678842105265,0.12152610315789475,-0.12675216342105267,3
213
+ m2,m,tabbyflow,TabbyFlow,0.33210978125,0.51787408,0.35495868421052634,32.0,25.0,19.0,0.4016475151535088,0.4364163821052632,0.16291539578947367,-0.10430660085526317,3
214
+ m2,m,tabddpm,TabDDPM,0.252013125,0.46586980000000006,0.3450908947368421,32.0,25.0,19.0,0.3543246065789474,0.4054803473684211,0.12077890526315793,-0.15346722236842109,3
215
+ m2,m,tabpfgen,TabPFGen,0.38784646875,0.5601446800000001,0.43105263157894735,32.0,25.0,19.0,0.45968126010964916,0.4955986557894737,0.1290920484210527,-0.1077521870394737,3
216
+ m2,m,tabsyn,TabSyn,0.38889640625,0.53235064,0.36390078947368426,32.0,25.0,19.0,0.4283826119078948,0.44812571473684215,0.16844985052631573,-0.05922930848684216,3
217
+ m2,m,tvae,TVAE,0.3261158125,0.49764196000000005,0.33873352631578946,32.0,25.0,19.0,0.3874970996052632,0.41818774315789475,0.1589084336842106,-0.09207193065789476,3
218
+ m4,m,arf,ARF,0.28,1.0,0.9828283333333334,25.0,18.0,15.0,0.754276111111111,0.9914141666666667,0.017171666666666585,-0.7114141666666667,3
219
+ m4,m,bayesnet,BayesNet,0.28,1.0,0.9777778,25.0,18.0,15.0,0.7525926,0.9888889000000001,0.02222219999999997,-0.7088889,3
220
+ m4,m,ctgan,CTGAN,0.39361928,0.6296297777777777,0.7475757333333334,25.0,18.0,15.0,0.5902749303703704,0.6886027555555556,-0.11794595555555565,-0.2949834755555556,3
221
+ m4,m,forestdiffusion,ForestDiffusion,0.28,1.0,0.8503788,25.0,18.0,15.0,0.7101262666666667,0.9251894,0.1496212,-0.6451894,3
222
+ m4,m,realtabformer,RealTabFormer,0.58176604,1.0,0.9878788000000001,25.0,18.0,15.0,0.85654828,0.9939394,0.012121199999999943,-0.41217336000000004,3
223
+ m4,m,tabbyflow,TabbyFlow,0.28,1.0,0.9722221999999999,25.0,18.0,15.0,0.7507407333333332,0.9861111,0.027777800000000075,-0.7061111,3
224
+ m4,m,tabddpm,TabDDPM,0.28,0.9259257777777778,0.7026515333333333,25.0,18.0,15.0,0.6361924370370371,0.8142886555555555,0.22327424444444455,-0.5342886555555555,3
225
+ m4,m,tabdiff,TabDiff,0.2800572,1.0,0.9722221999999999,25.0,18.0,15.0,0.7507598,0.9861111,0.027777800000000075,-0.7060539,3
226
+ m4,m,tabpfgen,TabPFGen,0.28,1.0,0.9842172,25.0,18.0,15.0,0.7547390666666667,0.9921086,0.015782799999999986,-0.7121086,3
227
+ m4,m,tabsyn,TabSyn,0.28,1.0,0.9823232666666667,25.0,18.0,15.0,0.7541077555555556,0.9911616333333333,0.017676733333333305,-0.7111616333333333,3
228
+ m4,m,tvae,TVAE,0.39194567999999996,0.6296297777777777,0.7075757333333333,25.0,18.0,15.0,0.5763837303703704,0.6686027555555556,-0.07794595555555561,-0.27665707555555563,3
229
+ m5,m,arf,ARF,0.3185436875,0.48799080000000006,0.3267096842105263,32.0,25.0,19.0,0.3777480572368421,0.40735024210526316,0.16128111578947374,-0.08880655460526315,3
230
+ m5,m,bayesnet,BayesNet,0.30602121875,0.46968924,0.32519331578947375,32.0,25.0,19.0,0.3669679248464912,0.3974412778947369,0.14449592421052626,-0.09142005914473689,3
231
+ m5,m,ctgan,CTGAN,0.21050071875,0.26872576000000004,0.1910978947368421,32.0,25.0,19.0,0.2234414578289474,0.22991182736842108,0.07762786526315793,-0.019411108618421075,3
232
+ m5,m,forestdiffusion,ForestDiffusion,0.2589626875,0.40024256,0.2966205263157895,32.0,25.0,19.0,0.31860859127192986,0.34843154315789476,0.10362203368421052,-0.08946885565789475,3
233
+ m5,m,realtabformer,RealTabFormer,0.50289403125,0.59809948,0.5158385789473684,32.0,25.0,19.0,0.5389440300657894,0.5569690294736842,0.08226090105263162,-0.05407499822368422,3
234
+ m5,m,tabbyflow,TabbyFlow,0.34733556250000003,0.47847056000000004,0.33803110526315794,32.0,25.0,19.0,0.38794574258771936,0.408250832631579,0.1404394547368421,-0.06091527013157899,3
235
+ m5,m,tabddpm,TabDDPM,0.21973475,0.33046072000000004,0.24766847368421055,32.0,25.0,19.0,0.26595464789473683,0.2890645968421053,0.08279224631578949,-0.06932984684210527,3
236
+ m5,m,tabdiff,TabDiff,0.30302253125,0.36406064,0.2645431052631579,32.0,25.0,19.0,0.31054209217105266,0.31430187263157894,0.0995175347368421,-0.011279341381578933,3
237
+ m5,m,tabpfgen,TabPFGen,0.343667625,0.49893552,0.3603591052631579,32.0,25.0,19.0,0.40098741675438593,0.42964731263157896,0.13857641473684212,-0.08597968763157898,3
238
+ m5,m,tabsyn,TabSyn,0.3385661875,0.45839232,0.3378898947368421,32.0,25.0,19.0,0.37828280074561405,0.39814110736842107,0.12050242526315791,-0.05957491986842106,3
239
+ m5,m,tvae,TVAE,0.197794125,0.2678354,0.1760038947368421,32.0,25.0,19.0,0.21387780657894737,0.22191964736842107,0.09183150526315789,-0.024125522368421082,3
240
+ m6,m,arf,ARF,0.8091068,0.990934,0.9672977500000001,30.0,14.0,12.0,0.9224461833333334,0.979115875,0.023636249999999914,-0.17000907499999995,3
241
+ m6,m,bayesnet,BayesNet,0.6094795333333334,0.9947090000000001,0.9392883333333333,30.0,14.0,12.0,0.8478256222222221,0.9669986666666667,0.055420666666666785,-0.3575191333333333,3
242
+ m6,m,ctgan,CTGAN,0.25773236666666666,0.43229557142857145,0.37008233333333335,30.0,14.0,12.0,0.3533700904761905,0.4011889523809524,0.0622132380952381,-0.14345658571428577,3
243
+ m6,m,forestdiffusion,ForestDiffusion,0.42536963333333333,0.7508547142857143,0.6804329166666667,30.0,14.0,12.0,0.6188857547619048,0.7156438154761905,0.07042179761904754,-0.29027418214285716,3
244
+ m6,m,realtabformer,RealTabFormer,0.6629901666666667,0.9799450714285715,0.949674,30.0,14.0,12.0,0.8642030793650793,0.9648095357142857,0.03027107142857144,-0.3018193690476191,3
245
+ m6,m,tabbyflow,TabbyFlow,0.5688450666666667,0.8571428571428571,0.8407713333333332,30.0,14.0,12.0,0.7555864190476189,0.8489570952380951,0.01637152380952389,-0.2801120285714285,3
246
+ m6,m,tabddpm,TabDDPM,0.4233788,0.7472832857142857,0.7124118333333334,30.0,14.0,12.0,0.6276913063492063,0.7298475595238095,0.03487145238095235,-0.30646875952380953,3
247
+ m6,m,tabdiff,TabDiff,0.6235681666666667,0.8571428571428571,0.8344749166666666,30.0,14.0,12.0,0.7717286468253968,0.8458088869047619,0.022667940476190473,-0.22224072023809516,3
248
+ m6,m,tabpfgen,TabPFGen,0.5004732666666667,0.8480769285714286,0.8042334166666666,30.0,14.0,12.0,0.7175945373015873,0.8261551726190476,0.04384351190476199,-0.3256819059523809,3
249
+ m6,m,tabsyn,TabSyn,0.6062685,0.8571428571428571,0.833524,30.0,14.0,12.0,0.765645119047619,0.8453334285714286,0.023618857142857053,-0.23906492857142858,3
250
+ m6,m,tvae,TVAE,0.2242718,0.3982295714285714,0.32006816666666665,30.0,14.0,12.0,0.31418984603174605,0.359148869047619,0.07816140476190475,-0.134877069047619,3
251
+ m7,m,arf,ARF,0.4573732258064516,1.0,0.98002,31.0,20.0,11.0,0.8124644086021505,0.9900100000000001,0.019979999999999998,-0.5326367741935485,3
252
+ m7,m,bayesnet,BayesNet,0.4548982580645161,1.0,1.0,31.0,20.0,11.0,0.8182994193548386,1.0,0.0,-0.5451017419354839,3
253
+ m7,m,ctgan,CTGAN,0.4593911612903226,1.0,0.8914141818181818,31.0,20.0,11.0,0.7836017810361682,0.9457070909090909,0.10858581818181823,-0.4863159296187683,3
254
+ m7,m,forestdiffusion,ForestDiffusion,0.4564588387096774,1.0,0.993007,31.0,20.0,11.0,0.8164886129032257,0.9965035,0.006993000000000027,-0.5400446612903226,3
255
+ m7,m,realtabformer,RealTabFormer,0.6208770322580646,1.0,1.0,31.0,20.0,11.0,0.8736256774193549,1.0,0.0,-0.37912296774193543,3
256
+ m7,m,tabbyflow,TabbyFlow,0.4573732258064516,1.0,0.9898990000000001,31.0,20.0,11.0,0.8157574086021505,0.9949495,0.010100999999999916,-0.5375762741935484,3
257
+ m7,m,tabddpm,TabDDPM,0.4568418709677419,1.0,1.0,31.0,20.0,11.0,0.8189472903225807,1.0,0.0,-0.543158129032258,3
258
+ m7,m,tabdiff,TabDiff,0.45741419354838714,1.0,0.9294372727272727,31.0,20.0,11.0,0.7956171554252199,0.9647186363636364,0.07056272727272728,-0.5073044428152493,3
259
+ m7,m,tabpfgen,TabPFGen,0.41945329032258066,0.9,0.7727272727272727,31.0,20.0,11.0,0.6973935210166178,0.8363636363636364,0.12727272727272732,-0.41691034604105576,3
260
+ m7,m,tabsyn,TabSyn,0.45600270967741935,1.0,0.987013,31.0,20.0,11.0,0.8143385698924731,0.9935065000000001,0.01298699999999997,-0.5375037903225808,3
261
+ m7,m,tvae,TVAE,0.41563348387096777,0.96,0.525938,31.0,20.0,11.0,0.6338571612903227,0.742969,0.43406199999999995,-0.3273355161290322,3
262
+ m8,m,arf,ARF,0.1973623125,0.45047312000000006,0.42899036842105265,32.0,25.0,19.0,0.35894193364035093,0.43973174421052635,0.021482751578947412,-0.24236943171052636,3
263
+ m8,m,bayesnet,BayesNet,0.19418490625,0.45014212,0.43347131578947373,32.0,25.0,19.0,0.3592661140131579,0.44180671789473686,0.016670804210526247,-0.24762181164473684,3
264
+ m8,m,ctgan,CTGAN,0.21339903125,0.45813284000000004,0.4349717894736842,32.0,25.0,19.0,0.3688345535745614,0.4465523147368421,0.02316105052631584,-0.23315328348684208,3
265
+ m8,m,forestdiffusion,ForestDiffusion,0.19866478125,0.45026984000000003,0.4281918421052632,32.0,25.0,19.0,0.3590421544517544,0.4392308410526316,0.022077997894736856,-0.2405660598026316,3
266
+ m8,m,realtabformer,RealTabFormer,0.49798296875000003,0.5855268,0.5810588421052632,32.0,25.0,19.0,0.554856203618421,0.5832928210526316,0.0044679578947368626,-0.08530985230263155,3
267
+ m8,m,tabbyflow,TabbyFlow,0.21738296875000002,0.45143488000000004,0.4422726842105263,32.0,25.0,19.0,0.3703635109868421,0.44685378210526316,0.009162195789473748,-0.22947081335526315,3
268
+ m8,m,tabddpm,TabDDPM,0.224717375,0.45193088000000003,0.4453282105263159,32.0,25.0,19.0,0.3739921551754386,0.44862954526315796,0.006602669473684153,-0.22391217026315796,3
269
+ m8,m,tabdiff,TabDiff,0.21384484375,0.45154856000000004,0.447157,32.0,25.0,19.0,0.3708501345833333,0.44935278,0.0043915600000000166,-0.23550793625,3
270
+ m8,m,tabpfgen,TabPFGen,0.19736940625000002,0.4501522,0.4291395263157895,32.0,25.0,19.0,0.3588870441885965,0.4396458631578948,0.021012673684210503,-0.24227645690789476,3
271
+ m8,m,tabsyn,TabSyn,0.21320125,0.4514904,0.44148715789473686,32.0,25.0,19.0,0.3687262692982456,0.44648877894736844,0.010003242105263155,-0.23328752894736843,3
272
+ m8,m,tvae,TVAE,0.2114201875,0.43065696000000003,0.3629206842105263,32.0,25.0,19.0,0.33499927723684214,0.3967888221052632,0.06773627578947372,-0.18536863460526318,3
273
+ m9,m,arf,ARF,0.4699181379310345,0.9475045789473683,0.7128722307692308,29.0,19.0,13.0,0.7100983158825445,0.8301884048582995,0.2346323481781375,-0.360270266927265,3
274
+ m9,m,bayesnet,BayesNet,0.4722176206896552,0.9323308421052632,0.8283105384615385,29.0,19.0,13.0,0.7442863337521524,0.8803206902834009,0.10402030364372472,-0.40810306959374565,3
275
+ m9,m,ctgan,CTGAN,0.48757348275862067,0.9392712631578947,0.8092250000000001,29.0,19.0,13.0,0.7453565819721718,0.8742481315789474,0.13004626315789458,-0.38667464882032676,3
276
+ m9,m,forestdiffusion,ForestDiffusion,0.2620823103448276,0.6794968421052632,0.6354172307692308,29.0,19.0,13.0,0.5256654610731072,0.657457036437247,0.04407961133603233,-0.39537472609241936,3
277
+ m9,m,realtabformer,RealTabFormer,0.7083698275862069,0.9726359473684211,0.9289329230769231,29.0,19.0,13.0,0.869979566010517,0.9507844352226721,0.04370302429149797,-0.24241460763646516,3
278
+ m9,m,tabbyflow,TabbyFlow,0.2107960344827586,0.5598551578947368,0.36618046153846157,29.0,19.0,13.0,0.37894388463865236,0.4630178097165992,0.19367469635627527,-0.2522217752338406,3
279
+ m9,m,tabddpm,TabDDPM,0.2716961724137931,0.6794968421052632,0.6452884615384615,29.0,19.0,13.0,0.5321604920191726,0.6623926518218624,0.034208380566801644,-0.39069647940806923,3
280
+ m9,m,tabdiff,TabDiff,0.28835596551724135,0.6465247894736842,0.6163450769230768,29.0,19.0,13.0,0.5170752773046674,0.6314349331983805,0.030179712550607363,-0.34307896768113916,3
281
+ m9,m,tabpfgen,TabPFGen,0.4145716551724138,0.7988722105263159,0.7138677692307692,29.0,19.0,13.0,0.6424372116431663,0.7563699898785425,0.08500444129554663,-0.34179833470612875,3
282
+ m9,m,tabsyn,TabSyn,0.28671755172413793,0.6626817368421053,0.6199112307692308,29.0,19.0,13.0,0.523103506445158,0.6412964838056681,0.04277050607287447,-0.35457893208153013,3
283
+ m9,m,tvae,TVAE,0.35243993103448273,0.6077695263157894,0.490421923076923,29.0,19.0,13.0,0.4835437934757317,0.5490957246963561,0.1173476032388664,-0.1966557936618734,3
284
+ m10,m,arf,ARF,0.3380742666666666,0.8125,0.78222375,30.0,16.0,12.0,0.6442660055555556,0.797361875,0.030276250000000005,-0.4592876083333334,3
285
+ m10,m,bayesnet,BayesNet,0.4643092,1.0,0.8765696666666667,30.0,16.0,12.0,0.7802929555555554,0.9382848333333333,0.12343033333333331,-0.47397563333333337,3
286
+ m10,m,ctgan,CTGAN,0.4223115,0.953125,0.834104,30.0,16.0,12.0,0.7365135,0.8936145,0.11902100000000004,-0.47130299999999997,3
287
+ m10,m,forestdiffusion,ForestDiffusion,0.3337816,0.8125,0.7895515,30.0,16.0,12.0,0.6452777,0.80102575,0.02294850000000004,-0.46724414999999997,3
288
+ m10,m,realtabformer,RealTabFormer,0.6253964333333334,1.0,0.97502575,30.0,16.0,12.0,0.8668073944444444,0.987512875,0.024974249999999976,-0.36211644166666657,3
289
+ m10,m,tabbyflow,TabbyFlow,0.3450314,0.8125,0.7963303333333333,30.0,16.0,12.0,0.6512872444444443,0.8044151666666666,0.01616966666666675,-0.4593837666666666,3
290
+ m10,m,tabddpm,TabDDPM,0.295043,0.778728,0.4009308333333333,30.0,16.0,12.0,0.49156727777777776,0.5898294166666667,0.3777971666666667,-0.29478641666666666,3
291
+ m10,m,tabdiff,TabDiff,0.34448439999999997,0.8125,0.7902106666666667,30.0,16.0,12.0,0.6490650222222222,0.8013553333333334,0.022289333333333272,-0.45687093333333345,3
292
+ m10,m,tabpfgen,TabPFGen,0.3456986333333333,0.8125,0.8141813333333333,30.0,16.0,12.0,0.6574599888888889,0.8133406666666667,-0.0016813333333333125,-0.46764203333333343,3
293
+ m10,m,tabsyn,TabSyn,0.3444816333333333,0.8125,0.7636155833333333,30.0,16.0,12.0,0.6401990722222223,0.7880577916666667,0.04888441666666665,-0.44357615833333336,3
294
+ m10,m,tvae,TVAE,0.4453088333333334,0.958333375,0.7988325833333333,30.0,16.0,12.0,0.7341582638888888,0.8785829791666666,0.15950079166666675,-0.43327414583333324,3
295
+ m11,m,arf,ARF,0.277200875,0.32005596000000003,0.38612652631578953,32.0,25.0,19.0,0.3277944537719299,0.35309124315789475,-0.0660705663157895,-0.07589036815789474,3
296
+ m11,m,bayesnet,BayesNet,0.2733346875,0.32001896,0.38530405263157896,32.0,25.0,19.0,0.326219233377193,0.3526615063157895,-0.06528509263157894,-0.07932681881578951,3
297
+ m11,m,ctgan,CTGAN,0.40162375,0.37545868,0.49313199999999996,32.0,25.0,19.0,0.42340481,0.43429534,-0.11767331999999997,-0.03267158999999997,3
298
+ m11,m,forestdiffusion,ForestDiffusion,0.27523665625,0.32002020000000003,0.3854097368421053,32.0,25.0,19.0,0.3268888643640351,0.35271496842105265,-0.06538953684210524,-0.07747831217105267,3
299
+ m11,m,realtabformer,RealTabFormer,0.53101253125,0.5767028000000001,0.5436746842105263,32.0,25.0,19.0,0.5504633384868421,0.5601887421052631,0.03302811578947373,-0.02917621085526312,3
300
+ m11,m,tabbyflow,TabbyFlow,0.27586634375,0.32073,0.38995700000000005,32.0,25.0,19.0,0.3288511145833333,0.35534350000000003,-0.06922700000000004,-0.07947715625000001,3
301
+ m11,m,tabddpm,TabDDPM,0.27924665625,0.32077956,0.40216563157894736,32.0,25.0,19.0,0.3340639492763158,0.36147259578947366,-0.08138607157894734,-0.08222593953947366,3
302
+ m11,m,tabdiff,TabDiff,0.28005421875000003,0.32088640000000007,0.39798468421052635,32.0,25.0,19.0,0.3329751009868422,0.3594355421052632,-0.07709828421052628,-0.07938132335526316,3
303
+ m11,m,tabpfgen,TabPFGen,0.273865625,0.32003356000000005,0.36168773684210526,32.0,25.0,19.0,0.31852897394736845,0.3408606484210527,-0.041654176842105206,-0.06699502342105268,3
304
+ m11,m,tabsyn,TabSyn,0.2777555,0.32100008,0.38666826315789476,32.0,25.0,19.0,0.3284746143859649,0.35383417157894737,-0.06566818315789474,-0.07607867157894738,3
305
+ m11,m,tvae,TVAE,0.38122640625,0.37118196000000003,0.45227168421052627,32.0,25.0,19.0,0.40156001682017545,0.4117268221052631,-0.08108972421052624,-0.03050041585526314,3
306
+ m12,m,arf,ARF,0.21667699999999998,0.777827375,0.06349211111111111,26.0,16.0,9.0,0.35266549537037034,0.42065974305555554,0.7143352638888889,-0.20398274305555555,3
307
+ m12,m,bayesnet,BayesNet,0.2540605384615385,0.8458333125,0.25,26.0,16.0,9.0,0.44996461698717954,0.54791665625,0.5958333125,-0.2938561177884615,3
308
+ m12,m,ctgan,CTGAN,0.27091030769230773,0.7661034375,0.17559633333333333,26.0,16.0,9.0,0.404203359508547,0.47084988541666667,0.5905071041666666,-0.19993957772435894,3
309
+ m12,m,forestdiffusion,ForestDiffusion,0.12829476923076924,0.7104166875,0.05555555555555555,26.0,16.0,9.0,0.2980890040954416,0.3829861215277778,0.6548611319444444,-0.25469135229700857,3
310
+ m12,m,realtabformer,RealTabFormer,0.700401423076923,0.9565603125,0.8565951111111111,26.0,16.0,9.0,0.8378522822293446,0.9065777118055556,0.09996520138888887,-0.20617628872863258,3
311
+ m12,m,tabbyflow,TabbyFlow,0.16925376923076924,0.7696429375,0.3111111111111111,26.0,16.0,9.0,0.4166692726139601,0.5403770243055556,0.4585318263888889,-0.37112325507478633,3
312
+ m12,m,tabdiff,TabDiff,0.225798,0.8183035,0.1904762222222222,26.0,16.0,9.0,0.4115259074074074,0.5043898611111111,0.6278272777777778,-0.27859186111111106,3
313
+ m12,m,tabpfgen,TabPFGen,0.18700123076923078,0.817113125,0.2222222222222222,26.0,16.0,9.0,0.40877885933048425,0.5196676736111111,0.5948909027777778,-0.3326664428418803,3
314
+ m12,m,tabsyn,TabSyn,0.23150492307692308,0.734821375,0.15740744444444443,26.0,16.0,9.0,0.3745779141737892,0.4461144097222222,0.5774139305555556,-0.21460948664529914,3
315
+ m12,m,tvae,TVAE,0.2076793846153846,0.6933355,0.23359133333333335,26.0,16.0,9.0,0.3782020726495727,0.4634634166666667,0.4597441666666666,-0.2557840320512821,3
316
+ n1,n,arf,ARF,0.25981396296296294,1.0,1.0,27.0,19.0,8.0,0.7532713209876544,1.0,0.0,-0.740186037037037,3
317
+ n1,n,bayesnet,BayesNet,0.25925925925925924,1.0,1.0,27.0,19.0,8.0,0.7530864197530865,1.0,0.0,-0.7407407407407407,3
318
+ n1,n,ctgan,CTGAN,0.25925925925925924,1.0,1.0,27.0,19.0,8.0,0.7530864197530865,1.0,0.0,-0.7407407407407407,3
319
+ n1,n,forestdiffusion,ForestDiffusion,0.25925925925925924,1.0,1.0,27.0,19.0,8.0,0.7530864197530865,1.0,0.0,-0.7407407407407407,3
320
+ n1,n,realtabformer,RealTabFormer,0.26191785185185185,1.0,1.0,27.0,19.0,8.0,0.7539726172839506,1.0,0.0,-0.7380821481481481,3
321
+ n1,n,tabbyflow,TabbyFlow,0.12962962962962962,0.5,0.5,27.0,19.0,8.0,0.37654320987654327,0.5,0.0,-0.37037037037037035,3
322
+ n1,n,tabddpm,TabDDPM,0.2598714074074074,1.0,1.0,27.0,19.0,8.0,0.7532904691358024,1.0,0.0,-0.7401285925925927,3
323
+ n1,n,tabdiff,TabDiff,0.2605367037037037,1.0,1.0,27.0,19.0,8.0,0.7535122345679012,1.0,0.0,-0.7394632962962964,3
324
+ n1,n,tabpfgen,TabPFGen,0.25925925925925924,1.0,1.0,27.0,19.0,8.0,0.7530864197530865,1.0,0.0,-0.7407407407407407,3
325
+ n1,n,tabsyn,TabSyn,0.25925925925925924,1.0,1.0,27.0,19.0,8.0,0.7530864197530865,1.0,0.0,-0.7407407407407407,3
326
+ n1,n,tvae,TVAE,0.25925925925925924,1.0,1.0,27.0,19.0,8.0,0.7530864197530865,1.0,0.0,-0.7407407407407407,3
327
+ n2,n,arf,ARF,0.20380433333333334,1.0,1.0,24.0,20.0,8.0,0.7346014444444444,1.0,0.0,-0.7961956666666666,3
328
+ n2,n,bayesnet,BayesNet,0.17972583333333333,1.0,1.0,24.0,20.0,8.0,0.7265752777777778,1.0,0.0,-0.8202741666666666,3
329
+ n2,n,ctgan,CTGAN,0.17838766666666664,1.0,1.0,24.0,20.0,8.0,0.7261292222222222,1.0,0.0,-0.8216123333333334,3
330
+ n2,n,forestdiffusion,ForestDiffusion,0.044309999999999995,0.25,0.25,24.0,20.0,8.0,0.1814366666666667,0.25,0.0,-0.20569,3
331
+ n2,n,realtabformer,RealTabFormer,0.5670209166666667,1.0,1.0,24.0,20.0,8.0,0.8556736388888888,1.0,0.0,-0.43297908333333335,3
332
+ n2,n,tabbyflow,TabbyFlow,0.04830891666666667,0.25,0.25,24.0,20.0,8.0,0.18276963888888886,0.25,0.0,-0.20169108333333333,3
333
+ n2,n,tabddpm,TabDDPM,0.08182733333333334,0.25,0.25,24.0,20.0,8.0,0.19394244444444445,0.25,0.0,-0.16817266666666666,3
334
+ n2,n,tabdiff,TabDiff,0.047967249999999996,0.25,0.25,24.0,20.0,8.0,0.18265575,0.25,0.0,-0.20203275,3
335
+ n2,n,tabpfgen,TabPFGen,0.1780555,1.0,1.0,24.0,20.0,8.0,0.7260185,1.0,0.0,-0.8219445,3
336
+ n2,n,tvae,TVAE,0.17896783333333333,1.0,1.0,24.0,20.0,8.0,0.7263226111111111,1.0,0.0,-0.8210321666666667,3
337
+ n3,n,arf,ARF,0.19898421428571428,0.32112638095238094,0.1760009375,28.0,21.0,16.0,0.23203717757936507,0.24856365922619048,0.14512544345238093,-0.0495794449404762,3
338
+ n3,n,bayesnet,BayesNet,0.1969215,0.3202072857142857,0.1760670625,28.0,21.0,16.0,0.23106528273809523,0.24813717410714287,0.14414022321428568,-0.05121567410714287,3
339
+ n3,n,ctgan,CTGAN,0.14063832142857144,0.1365337619047619,0.1202753125,28.0,21.0,16.0,0.13248246527777777,0.12840453720238096,0.016258449404761913,0.01223378422619048,3
340
+ n3,n,forestdiffusion,ForestDiffusion,0.16839275,0.22846919047619046,0.15104,28.0,21.0,16.0,0.18263398015873014,0.18975459523809524,0.07742919047619046,-0.02136184523809523,3
341
+ n3,n,realtabformer,RealTabFormer,0.4425426428571429,0.5851781428571429,0.4889740625,28.0,21.0,16.0,0.5055649494047619,0.5370761026785714,0.0962040803571429,-0.09453345982142852,3
342
+ n3,n,tabbyflow,TabbyFlow,0.2097585,0.24597538095238095,0.18664125,28.0,21.0,16.0,0.21412504365079366,0.21630831547619048,0.05933413095238094,-0.00654981547619049,3
343
+ n3,n,tabddpm,TabDDPM,0.17744382142857143,0.23465938095238095,0.162273875,28.0,21.0,16.0,0.19145902579365082,0.19846662797619047,0.07238550595238094,-0.02102280654761904,3
344
+ n3,n,tabdiff,TabDiff,0.20965032142857143,0.24584380952380952,0.186090875,28.0,21.0,16.0,0.21386166865079362,0.21596734226190475,0.05975293452380953,-0.0063170208333333255,3
345
+ n3,n,tabpfgen,TabPFGen,0.15961210714285715,0.1977807619047619,0.142851875,28.0,21.0,16.0,0.16674824801587299,0.17031631845238093,0.054928886904761914,-0.010704211309523787,3
346
+ n3,n,tabsyn,TabSyn,0.24112339285714285,0.33883180952380954,0.2264458125,28.0,21.0,16.0,0.2688003382936508,0.2826388110119048,0.11238599702380953,-0.04151541815476195,3
347
+ n3,n,tvae,TVAE,0.14063832142857144,0.1365337619047619,0.11918025,28.0,21.0,16.0,0.13211744444444443,0.12785700595238095,0.017353511904761906,0.012781315476190491,3
348
+ n4,n,arf,ARF,0.21436823333333335,0.578882875,0.299087052631579,30.0,24.0,19.0,0.36411272032163744,0.4389849638157895,0.27979582236842104,-0.22461673048245615,3
349
+ n4,n,bayesnet,BayesNet,0.21447826666666667,0.5786145,0.29142489473684213,30.0,24.0,19.0,0.36150588713450293,0.43501969736842105,0.2871896052631579,-0.2205414307017544,3
350
+ n4,n,ctgan,CTGAN,0.1520217,0.26091516666666664,0.16379257894736843,30.0,24.0,19.0,0.1922431485380117,0.21235387280701754,0.09712258771929821,-0.060332172807017526,3
351
+ n4,n,forestdiffusion,ForestDiffusion,0.22597143333333333,0.5789244583333334,0.27297068421052634,30.0,24.0,19.0,0.359288858625731,0.42594757127192984,0.30595377412280705,-0.1999761379385965,3
352
+ n4,n,realtabformer,RealTabFormer,0.39579,0.6807077083333333,0.4233926315789474,30.0,24.0,19.0,0.4999634466374268,0.5520501699561403,0.25731507675438586,-0.15626016995614034,3
353
+ n4,n,tabbyflow,TabbyFlow,0.2291326,0.5801620416666667,0.3155315263157895,30.0,24.0,19.0,0.3749420559941521,0.4478467839912281,0.2646305153508772,-0.21871418399122813,3
354
+ n4,n,tabddpm,TabDDPM,0.1275530666666667,0.39491775,0.15479936842105263,30.0,24.0,19.0,0.22575672836257313,0.2748585592105263,0.24011838157894738,-0.14730549254385963,3
355
+ n4,n,tabdiff,TabDiff,0.23115420000000003,0.57937375,0.30210342105263155,30.0,24.0,19.0,0.37087712368421055,0.4407385855263158,0.27727032894736847,-0.20958438552631575,3
356
+ n4,n,tabpfgen,TabPFGen,0.21695746666666665,0.5793452916666667,0.3173844736842105,30.0,24.0,19.0,0.3712290773391813,0.4483648826754386,0.2619608179824562,-0.23140741600877196,3
357
+ n4,n,tvae,TVAE,0.16657603333333335,0.34923270833333336,0.19983747368421054,30.0,24.0,19.0,0.23854873845029242,0.27453509100877194,0.14939523464912283,-0.10795905767543859,3
358
+ n5,n,arf,ARF,0.06319404545454545,0.26935322222222224,0.09178688888888889,22.0,9.0,9.0,0.14144471885521884,0.18057005555555555,0.17756633333333335,-0.1173760101010101,3
359
+ n5,n,bayesnet,BayesNet,0.05781613636363636,0.318654,0.09568055555555556,22.0,9.0,9.0,0.15738356397306397,0.20716727777777777,0.22297344444444445,-0.1493511414141414,3
360
+ n5,n,ctgan,CTGAN,0.031478545454545453,0.27470255555555556,0.068153,22.0,9.0,9.0,0.12477803367003366,0.1714277777777778,0.20654955555555554,-0.13994923232323234,3
361
+ n5,n,forestdiffusion,ForestDiffusion,0.043924727272727275,0.2222222222222222,0.006901222222222222,22.0,9.0,9.0,0.09101605723905724,0.11456172222222222,0.21532099999999998,-0.07063699494949494,3
362
+ n5,n,realtabformer,RealTabFormer,0.11041295454545455,0.3917781111111111,0.40648266666666666,22.0,9.0,9.0,0.3028912441077441,0.39913038888888885,-0.014704555555555554,-0.28871743434343433,3
363
+ n5,n,tabbyflow,TabbyFlow,0.07063913636363638,0.20825988888888888,0.1416091111111111,22.0,9.0,9.0,0.1401693787878788,0.1749345,0.06665077777777778,-0.10429536363636362,3
364
+ n5,n,tabddpm,TabDDPM,0.0039925,0.08281222222222223,0.009108333333333335,22.0,9.0,9.0,0.03197101851851852,0.04596027777777778,0.0737038888888889,-0.04196777777777778,3
365
+ n5,n,tabdiff,TabDiff,0.052973909090909085,0.22335255555555555,0.11141755555555556,22.0,9.0,9.0,0.12924800673400674,0.16738505555555555,0.11193499999999999,-0.11441114646464647,3
366
+ n5,n,tabpfgen,TabPFGen,0.05459068181818182,0.2222222222222222,0.0017670000000000001,22.0,9.0,9.0,0.09285996801346802,0.1119946111111111,0.22045522222222222,-0.05740392929292928,3
367
+ n5,n,tvae,TVAE,0.0315615,0.2709912222222222,0.0878788888888889,22.0,9.0,9.0,0.13014387037037037,0.17943505555555556,0.18311233333333332,-0.14787355555555556,3
368
+ n6,n,arf,ARF,0.39606932142857143,0.8285714285714285,0.55,28.0,21.0,8.0,0.5915469166666666,0.6892857142857143,0.27857142857142847,-0.29321639285714285,3
369
+ n6,n,bayesnet,BayesNet,0.5149335357142857,0.8285714285714285,0.55,28.0,21.0,8.0,0.6311683214285714,0.6892857142857143,0.27857142857142847,-0.1743521785714286,3
370
+ n6,n,ctgan,CTGAN,0.22013782142857144,0.28214285714285714,0.2125,28.0,21.0,8.0,0.23826022619047618,0.24732142857142858,0.06964285714285715,-0.02718360714285714,3
371
+ n6,n,forestdiffusion,ForestDiffusion,0.3917604642857143,0.8285714285714285,0.55,28.0,21.0,8.0,0.5901106309523809,0.6892857142857143,0.27857142857142847,-0.29752524999999996,3
372
+ n6,n,realtabformer,RealTabFormer,0.5941826071428571,0.8285714285714285,0.55,28.0,21.0,8.0,0.6575846785714285,0.6892857142857143,0.27857142857142847,-0.09510310714285719,3
373
+ n6,n,tabbyflow,TabbyFlow,0.4045123571428571,0.8285714285714285,0.55,28.0,21.0,8.0,0.5943612619047619,0.6892857142857143,0.27857142857142847,-0.2847733571428572,3
374
+ n6,n,tabddpm,TabDDPM,0.40493300000000004,0.8285714285714285,0.55,28.0,21.0,8.0,0.5945014761904762,0.6892857142857143,0.27857142857142847,-0.28435271428571424,3
375
+ n6,n,tabdiff,TabDiff,0.40235021428571427,0.8285714285714285,0.55,28.0,21.0,8.0,0.5936405476190476,0.6892857142857143,0.27857142857142847,-0.2869355,3
376
+ n6,n,tabpfgen,TabPFGen,0.39520592857142856,0.8285714285714285,0.55,28.0,21.0,8.0,0.5912591190476191,0.6892857142857143,0.27857142857142847,-0.2940797857142857,3
377
+ n6,n,tabsyn,TabSyn,0.405494,0.8285714285714285,0.55,28.0,21.0,8.0,0.5946884761904762,0.6892857142857143,0.27857142857142847,-0.28379171428571426,3
378
+ n6,n,tvae,TVAE,0.2284604642857143,0.28214285714285714,0.2125,28.0,21.0,8.0,0.2410344404761905,0.24732142857142858,0.06964285714285715,-0.018860964285714293,3
379
+ n7,n,arf,ARF,0.41501846428571426,0.6571428571428571,0.37143956250000004,28.0,21.0,16.0,0.48120029464285713,0.5142912098214286,0.2857032946428571,-0.09927274553571436,3
380
+ n7,n,bayesnet,BayesNet,0.4796774285714286,0.8114285714285714,0.5519301875,28.0,21.0,16.0,0.6143453958333334,0.6816793794642857,0.2594983839285714,-0.2020019508928571,3
381
+ n7,n,ctgan,CTGAN,0.3920577857142857,0.6759398095238096,0.39136518750000004,28.0,21.0,16.0,0.48645426091269844,0.5336524985119049,0.28457462202380956,-0.1415947127976192,3
382
+ n7,n,forestdiffusion,ForestDiffusion,0.41329664285714285,0.6740243333333333,0.3992688125,28.0,21.0,16.0,0.495529929563492,0.5366465729166667,0.2747555208333333,-0.12334993005952388,3
383
+ n7,n,realtabformer,RealTabFormer,0.44521353571428574,0.8114285714285714,0.536919625,28.0,21.0,16.0,0.5978539107142856,0.6741740982142856,0.2745089464285714,-0.2289605624999999,3
384
+ n7,n,tabbyflow,TabbyFlow,0.44807182142857144,0.7698535238095239,0.5023438125,28.0,21.0,16.0,0.5734230525793652,0.636098668154762,0.26750971130952383,-0.18802684672619058,3
385
+ n7,n,tabddpm,TabDDPM,0.30329907142857143,0.6345700952380953,0.3851255625,28.0,21.0,16.0,0.4409982430555556,0.5098478288690477,0.24944453273809525,-0.20654875744047624,3
386
+ n7,n,tabdiff,TabDiff,0.41057575,0.6605262857142857,0.383807125,28.0,21.0,16.0,0.4849697202380952,0.5221667053571428,0.2767191607142857,-0.11159095535714281,3
387
+ n7,n,tabpfgen,TabPFGen,0.4504502857142857,0.8114285714285714,0.55,28.0,21.0,16.0,0.603959619047619,0.6807142857142857,0.26142857142857134,-0.23026400000000002,3
388
+ n7,n,tvae,TVAE,0.4125495,0.6593984761904762,0.38861875,28.0,21.0,16.0,0.4868555753968254,0.5240086130952382,0.2707797261904762,-0.11145911309523815,3
389
+ n8,n,arf,ARF,0.0,0.58333325,0.41666650000000005,15.0,4.0,4.0,0.33333325,0.49999987500000004,0.16666674999999997,-0.49999987500000004,3
390
+ n8,n,bayesnet,BayesNet,0.0,0.5555555,0.41666650000000005,15.0,4.0,4.0,0.32407400000000003,0.486111,0.13888899999999993,-0.486111,3
391
+ n8,n,ctgan,CTGAN,0.0,0.1842105,0.0,15.0,4.0,4.0,0.0614035,0.09210525,0.1842105,-0.09210525,3
392
+ n8,n,forestdiffusion,ForestDiffusion,0.0,0.47368425000000003,0.0,15.0,4.0,4.0,0.15789475,0.23684212500000001,0.47368425000000003,-0.23684212500000001,3
393
+ n8,n,realtabformer,RealTabFormer,0.12465546666666666,0.34722225,0.628205,15.0,4.0,4.0,0.3666942388888889,0.48771362500000004,-0.28098275,-0.3630581583333334,3
394
+ n8,n,tabbyflow,TabbyFlow,0.0011036666666666666,0.38888900000000004,0.18749975,15.0,4.0,4.0,0.19249747222222224,0.288194375,0.20138925000000005,-0.28709070833333333,3
395
+ n8,n,tabdiff,TabDiff,0.0007932666666666667,0.388158,0.0,15.0,4.0,4.0,0.12965042222222223,0.194079,0.388158,-0.19328573333333335,3
396
+ n8,n,tabsyn,TabSyn,0.0002543333333333333,0.388158,0.0,15.0,4.0,4.0,0.1294707777777778,0.194079,0.388158,-0.19382466666666667,3
397
+ n8,n,tvae,TVAE,0.0,0.375,0.0,15.0,4.0,4.0,0.125,0.1875,0.375,-0.1875,3
398
+ n9,n,arf,ARF,0.0,0.0,0.0,28.0,16.0,10.0,0.0,0.0,0.0,0.0,3
399
+ n9,n,bayesnet,BayesNet,0.0,0.0,0.0,28.0,16.0,10.0,0.0,0.0,0.0,0.0,3
400
+ n9,n,ctgan,CTGAN,0.0,0.0,0.0,28.0,16.0,10.0,0.0,0.0,0.0,0.0,3
401
+ n9,n,forestdiffusion,ForestDiffusion,0.0,0.0,0.0,28.0,16.0,10.0,0.0,0.0,0.0,0.0,3
402
+ n9,n,realtabformer,RealTabFormer,0.0,0.0,0.0,28.0,16.0,10.0,0.0,0.0,0.0,0.0,3
403
+ n9,n,tabbyflow,TabbyFlow,0.0,0.0,0.0,28.0,16.0,10.0,0.0,0.0,0.0,0.0,3
404
+ n9,n,tabddpm,TabDDPM,0.0,0.0,0.0,28.0,16.0,10.0,0.0,0.0,0.0,0.0,3
405
+ n9,n,tabdiff,TabDiff,0.0,0.0,0.0,28.0,16.0,10.0,0.0,0.0,0.0,0.0,3
406
+ n9,n,tabpfgen,TabPFGen,0.0,0.0,0.0,28.0,16.0,10.0,0.0,0.0,0.0,0.0,3
407
+ n9,n,tvae,TVAE,0.0,0.0,0.0,28.0,16.0,10.0,0.0,0.0,0.0,0.0,3
408
+ n10,n,arf,ARF,0.23076923076923078,1.0,1.0,26.0,20.0,8.0,0.7435897435897436,1.0,0.0,-0.7692307692307692,3
409
+ n10,n,bayesnet,BayesNet,0.234125,1.0,1.0,26.0,20.0,8.0,0.7447083333333332,1.0,0.0,-0.765875,3
410
+ n10,n,ctgan,CTGAN,0.23326453846153847,1.0,1.0,26.0,20.0,8.0,0.7444215128205128,1.0,0.0,-0.7667354615384615,3
411
+ n10,n,forestdiffusion,ForestDiffusion,0.23076923076923078,1.0,1.0,26.0,20.0,8.0,0.7435897435897436,1.0,0.0,-0.7692307692307692,3
412
+ n10,n,realtabformer,RealTabFormer,0.236235,1.0,1.0,26.0,20.0,8.0,0.7454116666666666,1.0,0.0,-0.763765,3
413
+ n10,n,tabbyflow,TabbyFlow,0.23076923076923078,1.0,1.0,26.0,20.0,8.0,0.7435897435897436,1.0,0.0,-0.7692307692307692,3
414
+ n10,n,tabddpm,TabDDPM,0.23076923076923078,1.0,1.0,26.0,20.0,8.0,0.7435897435897436,1.0,0.0,-0.7692307692307692,3
415
+ n10,n,tabdiff,TabDiff,0.23076923076923078,1.0,1.0,26.0,20.0,8.0,0.7435897435897436,1.0,0.0,-0.7692307692307692,3
416
+ n10,n,tabpfgen,TabPFGen,0.23076923076923078,1.0,1.0,26.0,20.0,8.0,0.7435897435897436,1.0,0.0,-0.7692307692307692,3
417
+ n10,n,tvae,TVAE,0.23383430769230767,1.0,1.0,26.0,20.0,8.0,0.744611435897436,1.0,0.0,-0.7661656923076923,3
418
+ n11,n,arf,ARF,0.2,1.0,1.0,25.0,20.0,8.0,0.7333333333333334,1.0,0.0,-0.8,3
419
+ n11,n,bayesnet,BayesNet,0.2,1.0,1.0,25.0,20.0,8.0,0.7333333333333334,1.0,0.0,-0.8,3
420
+ n11,n,ctgan,CTGAN,0.2,1.0,1.0,25.0,20.0,8.0,0.7333333333333334,1.0,0.0,-0.8,3
421
+ n11,n,forestdiffusion,ForestDiffusion,0.2,1.0,1.0,25.0,20.0,8.0,0.7333333333333334,1.0,0.0,-0.8,3
422
+ n11,n,realtabformer,RealTabFormer,0.31826876,1.0,1.0,25.0,20.0,8.0,0.7727562533333333,1.0,0.0,-0.68173124,3
423
+ n11,n,tabbyflow,TabbyFlow,0.20007748,1.0,1.0,25.0,20.0,8.0,0.73335916,1.0,0.0,-0.79992252,3
424
+ n11,n,tabddpm,TabDDPM,0.2,1.0,1.0,25.0,20.0,8.0,0.7333333333333334,1.0,0.0,-0.8,3
425
+ n11,n,tabdiff,TabDiff,0.20009648,1.0,1.0,25.0,20.0,8.0,0.7333654933333333,1.0,0.0,-0.79990352,3
426
+ n11,n,tabpfgen,TabPFGen,0.20007587999999998,1.0,1.0,25.0,20.0,8.0,0.7333586266666666,1.0,0.0,-0.79992412,3
427
+ n11,n,tabsyn,TabSyn,0.20009584,1.0,1.0,25.0,20.0,8.0,0.73336528,1.0,0.0,-0.79990416,3
428
+ n11,n,tvae,TVAE,0.2,1.0,1.0,25.0,20.0,8.0,0.7333333333333334,1.0,0.0,-0.8,3
429
+ n12,n,arf,ARF,0.0,0.25,0.0,24.0,16.0,13.0,0.08333333333333333,0.125,0.25,-0.125,3
430
+ n12,n,bayesnet,BayesNet,0.0,0.25,0.0,24.0,16.0,13.0,0.08333333333333333,0.125,0.25,-0.125,3
431
+ n12,n,ctgan,CTGAN,0.5669999166666667,0.906245875,0.6532696923076924,24.0,16.0,13.0,0.7088384946581198,0.7797577836538462,0.2529761826923076,-0.21275786698717947,3
432
+ n12,n,forestdiffusion,ForestDiffusion,0.0,0.125,0.0,24.0,16.0,13.0,0.041666666666666664,0.0625,0.125,-0.0625,3
433
+ n12,n,realtabformer,RealTabFormer,0.6993810416666667,0.9686675,0.7971200769230768,24.0,16.0,13.0,0.8217228728632479,0.8828937884615384,0.17154742307692317,-0.18351274679487173,3
434
+ n12,n,tabbyflow,TabbyFlow,0.0,0.125,0.0,24.0,16.0,13.0,0.041666666666666664,0.0625,0.125,-0.0625,3
435
+ n12,n,tabddpm,TabDDPM,0.0,0.125,0.0,24.0,16.0,13.0,0.041666666666666664,0.0625,0.125,-0.0625,3
436
+ n12,n,tabdiff,TabDiff,0.0,0.125,0.0,24.0,16.0,13.0,0.041666666666666664,0.0625,0.125,-0.0625,3
437
+ n12,n,tabpfgen,TabPFGen,0.0,0.125,0.0,24.0,16.0,13.0,0.041666666666666664,0.0625,0.125,-0.0625,3
438
+ n12,n,tvae,TVAE,0.5888093333333334,0.928026375,0.6780015384615384,24.0,16.0,13.0,0.7316124155982906,0.8030139567307693,0.2500248365384615,-0.21420462339743584,3
439
+ n14,n,arf,ARF,,,0.005342,,,1.0,0.005342,0.005342,,,1
440
+ n14,n,bayesnet,BayesNet,,,0.001813,,,1.0,0.001813,0.001813,,,1
441
+ n14,n,ctgan,CTGAN,,,0.0,,,1.0,0.0,0.0,,,1
442
+ n14,n,forestdiffusion,ForestDiffusion,,,0.0,,,1.0,0.0,0.0,,,1
443
+ n14,n,realtabformer,RealTabFormer,,,0.0,,,1.0,0.0,0.0,,,1
444
+ n14,n,tabddpm,TabDDPM,,,0.0,,,1.0,0.0,0.0,,,1
445
+ n14,n,tabdiff,TabDiff,,,0.081967,,,1.0,0.081967,0.081967,,,1
446
+ n14,n,tabpfgen,TabPFGen,,,0.0,,,1.0,0.0,0.0,,,1
447
+ n14,n,tabsyn,TabSyn,,,0.025641,,,1.0,0.025641,0.025641,,,1
448
+ n14,n,tvae,TVAE,,,0.0,,,1.0,0.0,0.0,,,1
449
+ n15,n,arf,ARF,0.08333333333333333,0.9903846153846154,0.0,24.0,13.0,9.0,0.3579059829059829,0.4951923076923077,0.9903846153846154,-0.4118589743589744,3
450
+ n15,n,bayesnet,BayesNet,0.6306489166666667,1.0,0.4278046666666666,24.0,13.0,9.0,0.6861511944444444,0.7139023333333333,0.5721953333333334,-0.08325341666666664,3
451
+ n15,n,ctgan,CTGAN,0.046627416666666664,0.1846153846153846,0.03160488888888889,24.0,13.0,9.0,0.08761589672364672,0.10811013675213674,0.15301049572649572,-0.06148272008547007,3
452
+ n15,n,forestdiffusion,ForestDiffusion,0.078125,0.9717033076923076,0.0,24.0,13.0,9.0,0.3499427692307692,0.4858516538461538,0.9717033076923076,-0.4077266538461538,3
453
+ n15,n,realtabformer,RealTabFormer,0.65000525,0.9403846153846154,0.40584044444444445,24.0,13.0,9.0,0.6654101032763533,0.67311252991453,0.5345441709401709,-0.023107279914529988,3
454
+ n15,n,tabbyflow,TabbyFlow,0.057291666666666664,0.7469779999999999,0.0,24.0,13.0,9.0,0.26808988888888885,0.37348899999999996,0.7469779999999999,-0.3161973333333333,3
455
+ n15,n,tabddpm,TabDDPM,0.027083333333333334,0.33956046153846153,0.0,24.0,13.0,9.0,0.12221459829059829,0.16978023076923077,0.33956046153846153,-0.14269689743589742,3
456
+ n15,n,tabdiff,TabDiff,0.08333333333333333,1.0,0.0,24.0,13.0,9.0,0.3611111111111111,0.5,1.0,-0.4166666666666667,3
457
+ n15,n,tabpfgen,TabPFGen,0.078125,0.964011,0.0,24.0,13.0,9.0,0.34737866666666667,0.4820055,0.964011,-0.4038805,3
458
+ n15,n,tabsyn,TabSyn,0.08333333333333333,0.9574176153846155,0.0,24.0,13.0,9.0,0.3469169829059829,0.4787088076923077,0.9574176153846155,-0.3953754743589744,3
459
+ n15,n,tvae,TVAE,0.5270288333333334,0.7725274615384615,0.12741811111111112,24.0,13.0,9.0,0.4756581353276353,0.4499727863247863,0.6451093504273504,0.07705604700854707,3
460
+ n16,n,arf,ARF,0.2608832962962963,1.0,1.0,27.0,20.0,8.0,0.7536277654320989,1.0,0.0,-0.7391167037037036,3
461
+ n16,n,bayesnet,BayesNet,0.25925925925925924,1.0,1.0,27.0,20.0,8.0,0.7530864197530865,1.0,0.0,-0.7407407407407407,3
462
+ n16,n,ctgan,CTGAN,0.25925925925925924,1.0,1.0,27.0,20.0,8.0,0.7530864197530865,1.0,0.0,-0.7407407407407407,3
463
+ n16,n,forestdiffusion,ForestDiffusion,0.25925951851851853,1.0,1.0,27.0,20.0,8.0,0.7530865061728395,1.0,0.0,-0.7407404814814815,3
464
+ n16,n,realtabformer,RealTabFormer,0.29658703703703704,1.0,1.0,27.0,20.0,8.0,0.765529012345679,1.0,0.0,-0.703412962962963,3
465
+ n16,n,tabbyflow,TabbyFlow,0.25943796296296295,1.0,1.0,27.0,20.0,8.0,0.753145987654321,1.0,0.0,-0.740562037037037,3
466
+ n16,n,tabddpm,TabDDPM,0.25925996296296294,1.0,1.0,27.0,20.0,8.0,0.7530866543209876,1.0,0.0,-0.7407400370370371,3
467
+ n16,n,tabdiff,TabDiff,0.2594622962962963,1.0,1.0,27.0,20.0,8.0,0.753154098765432,1.0,0.0,-0.7405377037037038,3
468
+ n16,n,tabpfgen,TabPFGen,0.2593624074074074,1.0,1.0,27.0,20.0,8.0,0.7531208024691359,1.0,0.0,-0.7406375925925925,3
469
+ n16,n,tabsyn,TabSyn,0.2594459259259259,1.0,1.0,27.0,20.0,8.0,0.7531486419753085,1.0,0.0,-0.7405540740740741,3
470
+ n16,n,tvae,TVAE,0.25925925925925924,1.0,1.0,27.0,20.0,8.0,0.7530864197530865,1.0,0.0,-0.7407407407407407,3
471
+ n17,n,arf,ARF,0.0,0.11764705882352941,0.0,26.0,17.0,13.0,0.0392156862745098,0.058823529411764705,0.11764705882352941,-0.058823529411764705,3
472
+ n17,n,bayesnet,BayesNet,0.32578334615384613,0.6767332941176472,0.390467,26.0,17.0,13.0,0.46432788009049775,0.5336001470588236,0.28626629411764715,-0.2078168009049775,3
473
+ n17,n,ctgan,CTGAN,0.3096557692307692,0.5854812352941177,0.3961437692307692,26.0,17.0,13.0,0.43042692458521864,0.49081250226244344,0.18933746606334845,-0.18115673303167423,3
474
+ n17,n,forestdiffusion,ForestDiffusion,0.0,0.050420117647058824,0.0,26.0,17.0,13.0,0.016806705882352942,0.025210058823529412,0.050420117647058824,-0.025210058823529412,3
475
+ n17,n,realtabformer,RealTabFormer,0.4266759230769231,0.6052791176470588,0.5544041538461538,26.0,17.0,13.0,0.5287863981900452,0.5798416357466063,0.05087496380090495,-0.1531657126696832,3
476
+ n17,n,tabddpm,TabDDPM,0.0,0.10084035294117646,0.0,26.0,17.0,13.0,0.03361345098039215,0.05042017647058823,0.10084035294117646,-0.05042017647058823,3
477
+ n17,n,tabdiff,TabDiff,0.0,0.10084035294117646,0.0,26.0,17.0,13.0,0.03361345098039215,0.05042017647058823,0.10084035294117646,-0.05042017647058823,3
478
+ n17,n,tabpfgen,TabPFGen,0.0,0.11764705882352941,0.0,26.0,17.0,13.0,0.0392156862745098,0.058823529411764705,0.11764705882352941,-0.058823529411764705,3
479
+ n17,n,tabsyn,TabSyn,0.0,0.050420117647058824,0.0,26.0,17.0,13.0,0.016806705882352942,0.025210058823529412,0.050420117647058824,-0.025210058823529412,3
480
+ n17,n,tvae,TVAE,0.2909399615384615,0.5510456470588235,0.39608284615384615,26.0,17.0,13.0,0.4126894849170437,0.47356424660633484,0.15496280090497738,-0.18262428506787332,3
481
+ n18,n,arf,ARF,0.1927058620689655,0.12581579166666668,0.14419936842105263,29.0,24.0,19.0,0.15424034071889495,0.13500758004385965,-0.018383576754385955,0.05769828202510585,3
482
+ n18,n,bayesnet,BayesNet,0.19757555172413793,0.13550675,0.16710205263157896,29.0,24.0,19.0,0.16672811811857233,0.15130440131578948,-0.03159530263157895,0.04627115040834845,3
483
+ n18,n,ctgan,CTGAN,0.20360899999999998,0.14583737500000002,0.14796294736842105,29.0,24.0,19.0,0.16580310745614035,0.14690016118421054,-0.002125572368421036,0.05670883881578945,3
484
+ n18,n,forestdiffusion,ForestDiffusion,0.1958018275862069,0.12740508333333334,0.15981284210526317,29.0,24.0,19.0,0.16100658434160112,0.14360896271929824,-0.032407758771929834,0.05219286486690866,3
485
+ n18,n,realtabformer,RealTabFormer,0.2652468965517242,0.2515191666666667,0.2541938947368421,29.0,24.0,19.0,0.2569866526517443,0.2528565307017544,-0.002674728070175436,0.012390365849969776,3
486
+ n18,n,tabbyflow,TabbyFlow,0.20674368965517242,0.15336112500000001,0.18185036842105262,29.0,24.0,19.0,0.18065172769207502,0.1676057467105263,-0.028489243421052607,0.03913794294464612,3
487
+ n18,n,tabdiff,TabDiff,0.2010618275862069,0.14014175,0.16195178947368422,29.0,24.0,19.0,0.16771845568663038,0.1510467697368421,-0.021810039473684206,0.050015057849364775,3
488
+ n18,n,tabpfgen,TabPFGen,0.19093337931034485,0.12877170833333332,0.14863915789473683,29.0,24.0,19.0,0.15611474851280502,0.13870543311403508,-0.019867449561403516,0.05222794619630977,3
489
+ n18,n,tabsyn,TabSyn,0.22684562068965516,0.14673170833333335,0.1557862105263158,29.0,24.0,19.0,0.17645451318310146,0.1512589594298246,-0.009054502192982455,0.07558666125983057,3
490
+ n18,n,tvae,TVAE,0.19345206896551723,0.13788045833333334,0.1578704210526316,29.0,24.0,19.0,0.16306764945049404,0.14787543969298247,-0.01998996271929826,0.04557662927253475,3
491
+ n19,n,arf,ARF,0.0,0.0,0.0,19.0,4.0,6.0,0.0,0.0,0.0,0.0,3
492
+ n19,n,bayesnet,BayesNet,0.21084,0.0,0.160114,19.0,4.0,6.0,0.12365133333333334,0.080057,-0.160114,0.13078299999999998,3
493
+ n19,n,ctgan,CTGAN,0.26978094736842106,0.62473025,0.14042933333333332,19.0,4.0,6.0,0.34498017690058486,0.38257979166666667,0.48430091666666675,-0.1127988442982456,3
494
+ n19,n,forestdiffusion,ForestDiffusion,0.0,0.0,0.0,19.0,4.0,6.0,0.0,0.0,0.0,0.0,3
495
+ n19,n,realtabformer,RealTabFormer,0.12555052631578947,0.71343575,0.0957385,19.0,4.0,6.0,0.3115749254385965,0.40458712500000005,0.61769725,-0.2790365986842106,3
496
+ n19,n,tabbyflow,TabbyFlow,0.009704052631578948,0.0,0.0151515,19.0,4.0,6.0,0.008285184210526316,0.00757575,-0.0151515,0.0021283026315789483,3
497
+ n19,n,tabddpm,TabDDPM,0.0,0.0,0.0,19.0,4.0,6.0,0.0,0.0,0.0,0.0,3
498
+ n19,n,tabdiff,TabDiff,0.10587836842105264,0.0,0.09668399999999999,19.0,4.0,6.0,0.06752078947368421,0.048341999999999996,-0.09668399999999999,0.05753636842105264,3
499
+ n19,n,tabpfgen,TabPFGen,0.0,0.0,0.0,19.0,4.0,6.0,0.0,0.0,0.0,0.0,3
500
+ n19,n,tabsyn,TabSyn,0.10371668421052632,0.0,0.04869300000000001,19.0,4.0,6.0,0.05080322807017545,0.024346500000000004,-0.04869300000000001,0.07937018421052632,3
501
+ n19,n,tvae,TVAE,0.10475505263157894,0.7031952499999999,0.09838016666666667,19.0,4.0,6.0,0.3021101564327485,0.4007877083333333,0.6048150833333332,-0.2960326557017544,3
502
+ n20,n,arf,ARF,0.001429962962962963,0.003424684210526316,0.00346,27.0,19.0,8.0,0.0027715490578297595,0.0034423421052631577,-3.531578947368408e-05,-0.002012379142300195,3
503
+ n20,n,bayesnet,BayesNet,7.170370370370371e-05,0.00013373684210526315,0.00015125,27.0,19.0,8.0,0.00011889684860298894,0.00014249342105263156,-1.7513157894736843e-05,-7.078971734892785e-05,3
504
+ n20,n,ctgan,CTGAN,0.0,0.0,0.0,27.0,19.0,8.0,0.0,0.0,0.0,0.0,3
505
+ n20,n,forestdiffusion,ForestDiffusion,0.0,0.0,0.0,27.0,19.0,8.0,0.0,0.0,0.0,0.0,3
506
+ n20,n,realtabformer,RealTabFormer,0.5102963333333334,0.7153892631578948,0.75103375,27.0,19.0,8.0,0.6589064488304094,0.7332115065789474,-0.035644486842105305,-0.22291517324561405,3
507
+ n20,n,tabbyflow,TabbyFlow,0.00012140740740740741,0.00025573684210526313,0.00027325,27.0,19.0,8.0,0.0002167980831708902,0.00026449342105263154,-1.751315789473687e-05,-0.00014308601364522412,3
508
+ n20,n,tabddpm,TabDDPM,0.0,0.0,0.0,27.0,19.0,8.0,0.0,0.0,0.0,0.0,3
509
+ n20,n,tabpfgen,TabPFGen,0.0,0.0,0.0,27.0,19.0,8.0,0.0,0.0,0.0,0.0,3
510
+ n20,n,tabsyn,TabSyn,4.929629629629629e-05,0.00012099999999999999,0.000121,27.0,19.0,8.0,9.709876543209876e-05,0.00012099999999999999,-1.3552527156068805e-20,-7.17037037037037e-05,3
511
+ n20,n,tvae,TVAE,0.0,0.0,0.0,27.0,19.0,8.0,0.0,0.0,0.0,0.0,3
evaluation/query_family/conditional/data/dataset_model_subitems.csv ADDED
The diff for this file is too large to render. See raw diff
 
evaluation/query_family/conditional/data/dataset_summary.csv ADDED
@@ -0,0 +1,50 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ dataset_id,dataset_prefix,model_count,dependency_strength_similarity,direction_consistency,slice_level_consistency,conditional_dependency_structure_score,conditional_subgroup_score,direction_minus_slice,strength_minus_subgroup,subgroup_score_std_across_models
2
+ n9,n,10,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
3
+ n14,n,10,,,0.011476,0.011476,0.011476,,,0.026015
4
+ n20,n,10,0.051197,0.071932,0.075504,0.066211,0.073718,-0.003571,-0.022521,0.231725
5
+ n19,n,11,0.084566,0.185578,0.059563,0.109902,0.122571,0.126016,-0.038005,0.177433
6
+ n18,n,10,0.207398,0.149297,0.167937,0.174877,0.158617,-0.01864,0.048781,0.034252
7
+ c9,c,11,0.139285,0.246711,0.07986,0.155286,0.163286,0.166851,-0.024001,0.250785
8
+ n5,n,10,0.052058,0.248435,0.102079,0.134191,0.175257,0.146356,-0.123198,0.09169
9
+ n3,n,11,0.207791,0.271922,0.194167,0.224627,0.233045,0.077754,-0.025253,0.111783
10
+ n17,n,10,0.135305,0.295635,0.17371,0.20155,0.234673,0.121926,-0.099367,0.246907
11
+ c18,c,7,0.243326,0.460088,0.129381,0.277598,0.294735,0.330706,-0.051409,0.151109
12
+ n8,n,9,0.01409,0.409357,0.183226,0.202224,0.296292,0.22613,-0.282202,0.154997
13
+ n12,n,10,0.185519,0.392794,0.212839,0.263717,0.302817,0.179955,-0.117298,0.359963
14
+ m5,m,11,0.304277,0.420264,0.307269,0.343936,0.363766,0.112995,-0.05949,0.097037
15
+ m11,m,11,0.320584,0.353352,0.416762,0.363566,0.385057,-0.06341,-0.064473,0.064767
16
+ n4,n,10,0.2174,0.516108,0.274032,0.335847,0.39507,0.242075,-0.17767,0.104985
17
+ m2,m,10,0.337293,0.518102,0.362996,0.40613,0.440549,0.155106,-0.103255,0.032605
18
+ n15,n,11,0.213176,0.806144,0.090243,0.369854,0.448193,0.715901,-0.235017,0.181199
19
+ m8,m,11,0.234503,0.461978,0.443181,0.379887,0.452579,0.018797,-0.218077,0.045779
20
+ c16,c,9,0.220491,0.651475,0.291621,0.387862,0.471548,0.359854,-0.251057,0.188708
21
+ c17,c,10,0.366785,0.394705,0.587478,0.449656,0.491091,-0.192773,-0.124306,0.176394
22
+ c6,c,11,0.287253,0.562284,0.466729,0.438755,0.514506,0.095555,-0.227253,0.028458
23
+ m12,m,10,0.259158,0.788996,0.251605,0.433253,0.5203,0.537391,-0.261142,0.145523
24
+ n7,n,10,0.417021,0.716574,0.446082,0.526559,0.581328,0.270492,-0.164307,0.076177
25
+ n6,n,11,0.396185,0.729221,0.488636,0.538014,0.608929,0.240584,-0.212743,0.178783
26
+ c15,c,10,0.363682,0.751972,0.506652,0.540769,0.629312,0.24532,-0.26563,0.207558
27
+ c19,c,10,0.316883,0.842308,0.45912,0.539437,0.650714,0.383188,-0.333831,0.176641
28
+ n2,n,10,0.170838,0.7,0.7,0.523613,0.7,0.0,-0.529162,0.387298
29
+ m9,m,11,0.384067,0.76604,0.669707,0.606605,0.717873,0.096333,-0.333806,0.152541
30
+ m6,m,11,0.519226,0.79216,0.750205,0.687197,0.771183,0.041954,-0.251957,0.21229
31
+ m10,m,11,0.391266,0.869562,0.78378,0.681536,0.826671,0.085783,-0.435405,0.102917
32
+ c14,c,11,0.361944,0.911422,0.795875,0.689747,0.853649,0.115547,-0.491705,0.246326
33
+ c2,c,11,0.918203,0.927839,0.823788,0.889943,0.875814,0.104051,0.042389,0.123414
34
+ m1,m,11,0.341365,0.940196,0.866162,0.715908,0.903179,0.074034,-0.561813,0.114442
35
+ m4,m,11,0.327944,0.925926,0.897059,0.716977,0.911493,0.028867,-0.583548,0.12707
36
+ c10,c,10,0.866489,0.978397,0.904561,0.916483,0.941479,0.073836,-0.07499,0.063073
37
+ c8,c,11,0.934343,1.0,0.88468,0.939675,0.94234,0.11532,-0.007997,0.060358
38
+ c4,c,11,0.984091,0.969091,0.916667,0.956616,0.942879,0.052424,0.041212,0.033234
39
+ c11,c,11,0.984287,0.960999,0.930776,0.958687,0.945887,0.030223,0.0384,0.042948
40
+ c7,c,11,0.958081,0.967328,0.931188,0.952199,0.949258,0.036141,0.008823,0.040867
41
+ m7,m,11,0.464702,0.987273,0.915405,0.789126,0.951339,0.071868,-0.486637,0.084361
42
+ n1,n,11,0.247939,0.954545,0.954545,0.71901,0.954545,0.0,-0.706607,0.150756
43
+ c5,c,11,0.938384,0.977273,0.937762,0.95114,0.957517,0.03951,-0.019134,0.053523
44
+ c3,c,11,1.0,1.0,,1.0,1.0,,0.0,0.0
45
+ n10,n,10,0.232207,1.0,1.0,0.744069,1.0,0.0,-0.767793,0.0
46
+ n11,n,11,0.210783,1.0,1.0,0.736928,1.0,0.0,-0.789217,0.0
47
+ n16,n,11,0.262861,1.0,1.0,0.754287,1.0,0.0,-0.737139,0.0
48
+ c12,c,8,0.302168,,,0.302168,,,,
49
+ c13,c,11,0.046661,,,0.046661,,,,
50
+ c20,c,10,0.711907,,,0.711907,,,,
evaluation/query_family/conditional/data/duplicate_asset_audit.csv ADDED
@@ -0,0 +1 @@
 
 
1
+
evaluation/query_family/conditional/data/model_subitem_heatmap.csv ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ subitem_id,subitem_label,arf,bayesnet,ctgan,forestdiffusion,realtabformer,tabbyflow,tabddpm,tabdiff,tabpfgen,tabsyn,tvae
2
+ dependency_strength_similarity,Dependency strength similarity,0.398508,0.411394,0.394348,0.319302,0.550771,0.327734,0.34007,0.341388,0.384788,0.37393,0.370008
3
+ direction_consistency,Direction consistency,0.692817,0.707886,0.668259,0.629311,0.798648,0.615482,0.608457,0.659497,0.675145,0.671617,0.646445
4
+ slice_level_consistency,Slice-level consistency,0.562109,0.578142,0.51335,0.44518,0.707718,0.490401,0.492264,0.50764,0.554063,0.534691,0.461115
5
+ family_mean,Family mean,0.534173,0.551334,0.512856,0.450679,0.671214,0.476465,0.464714,0.491389,0.519807,0.508789,0.482923
evaluation/query_family/conditional/data/model_summary.csv ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ model_id,model_label,dataset_count,dataset_prefixes,dependency_strength_similarity__mean,dependency_strength_similarity__std,dependency_strength_similarity__se,dependency_strength_similarity__ci95_low,dependency_strength_similarity__ci95_high,dependency_strength_similarity__ci95_radius,direction_consistency__mean,direction_consistency__std,direction_consistency__se,direction_consistency__ci95_low,direction_consistency__ci95_high,direction_consistency__ci95_radius,slice_level_consistency__mean,slice_level_consistency__std,slice_level_consistency__se,slice_level_consistency__ci95_low,slice_level_consistency__ci95_high,slice_level_consistency__ci95_radius,conditional_dependency_structure_score__mean,conditional_dependency_structure_score__std,conditional_dependency_structure_score__se,conditional_dependency_structure_score__ci95_low,conditional_dependency_structure_score__ci95_high,conditional_dependency_structure_score__ci95_radius,conditional_subgroup_score__mean,conditional_subgroup_score__std,conditional_subgroup_score__se,conditional_subgroup_score__ci95_low,conditional_subgroup_score__ci95_high,conditional_subgroup_score__ci95_radius,direction_minus_slice__mean,direction_minus_slice__std,direction_minus_slice__se,direction_minus_slice__ci95_low,direction_minus_slice__ci95_high,direction_minus_slice__ci95_radius,strength_minus_subgroup__mean,strength_minus_subgroup__std,strength_minus_subgroup__se,strength_minus_subgroup__ci95_low,strength_minus_subgroup__ci95_high,strength_minus_subgroup__ci95_radius
2
+ arf,ARF,49,"c,m,n",0.398508,0.332853,0.048043,0.304343,0.492673,0.094165,0.692817,0.350455,0.052243,0.590422,0.795213,0.102396,0.562109,0.4034,0.060135,0.444244,0.679974,0.117865,0.534173,0.339849,0.04855,0.439016,0.629331,0.095158,0.62475,0.369373,0.054461,0.518007,0.731494,0.106744,0.111073,0.207201,0.031237,0.049849,0.172297,0.061224,-0.234692,0.26909,0.040114,-0.313315,-0.15607,0.078623
3
+ bayesnet,BayesNet,49,"c,m,n",0.411394,0.310257,0.044782,0.323622,0.499166,0.087772,0.707886,0.338535,0.050466,0.608973,0.806799,0.098913,0.578142,0.37205,0.055462,0.469436,0.686847,0.108706,0.551334,0.3158,0.045114,0.46291,0.639758,0.088424,0.639925,0.351448,0.051818,0.538361,0.741488,0.101564,0.110007,0.17614,0.026554,0.057961,0.162053,0.052046,-0.242221,0.277417,0.041355,-0.323277,-0.161166,0.081056
4
+ ctgan,CTGAN,49,"c,m,n",0.394348,0.299669,0.043254,0.309571,0.479125,0.084777,0.668259,0.339947,0.050676,0.568934,0.767585,0.099325,0.51335,0.370652,0.055254,0.405053,0.621647,0.108297,0.512856,0.313345,0.044764,0.425119,0.600593,0.087737,0.588831,0.352034,0.051905,0.487098,0.690563,0.101733,0.135702,0.170783,0.025747,0.085239,0.186166,0.050463,-0.206708,0.253883,0.037847,-0.280888,-0.132529,0.074179
5
+ forestdiffusion,ForestDiffusion,49,"c,m,n",0.319302,0.317331,0.045803,0.229528,0.409075,0.089773,0.629311,0.347645,0.051824,0.527736,0.730886,0.101575,0.44518,0.37854,0.056429,0.334578,0.555782,0.110602,0.450679,0.323973,0.046282,0.359966,0.541391,0.090712,0.536436,0.350758,0.051716,0.435072,0.6378,0.101364,0.165589,0.237441,0.035796,0.095429,0.235748,0.070159,-0.225226,0.250042,0.037274,-0.298283,-0.152169,0.073057
6
+ realtabformer,RealTabFormer,49,"c,m,n",0.550771,0.273348,0.039454,0.47344,0.628101,0.077331,0.798648,0.253801,0.037834,0.724492,0.872803,0.074155,0.707718,0.296696,0.044229,0.621029,0.794406,0.086688,0.671214,0.259223,0.037032,0.598631,0.743796,0.072582,0.747679,0.277446,0.040907,0.667501,0.827857,0.080178,0.070269,0.149803,0.022584,0.026005,0.114533,0.044264,-0.215083,0.216565,0.032284,-0.278359,-0.151807,0.063276
7
+ tabbyflow,TabbyFlow,46,"c,m,n",0.327734,0.311124,0.045873,0.237823,0.417644,0.089911,0.615482,0.344064,0.05187,0.513817,0.717146,0.101664,0.490401,0.364915,0.055649,0.381329,0.599473,0.109072,0.476465,0.316523,0.046669,0.384994,0.567936,0.091471,0.558732,0.346883,0.052295,0.456235,0.66123,0.102497,0.116138,0.166505,0.025392,0.06637,0.165906,0.049768,-0.233238,0.250883,0.037822,-0.307369,-0.159107,0.074131
8
+ tabddpm,TabDDPM,40,"c,m,n",0.34007,0.338409,0.054189,0.23386,0.44628,0.10621,0.608457,0.36727,0.060379,0.490115,0.7268,0.118342,0.492264,0.389115,0.06397,0.366882,0.617645,0.125381,0.464714,0.346971,0.054861,0.357187,0.572241,0.107527,0.549035,0.379966,0.061639,0.428223,0.669847,0.120812,0.091644,0.113779,0.018963,0.054476,0.128811,0.037168,-0.215913,0.258679,0.042527,-0.299265,-0.132561,0.083352
9
+ tabdiff,TabDiff,44,"c,m,n",0.341388,0.311937,0.04757,0.248151,0.434625,0.093237,0.659497,0.350439,0.054074,0.553512,0.765482,0.105985,0.50764,0.369702,0.057046,0.39583,0.619451,0.111811,0.491389,0.316217,0.047671,0.397953,0.584825,0.093436,0.582578,0.348241,0.053106,0.47849,0.686667,0.104088,0.133169,0.223359,0.034883,0.064799,0.20154,0.06837,-0.244982,0.272341,0.042023,-0.327347,-0.162616,0.082365
10
+ tabpfgen,TabPFGen,46,"c,m,n",0.384788,0.315033,0.046962,0.292742,0.476835,0.092046,0.675145,0.354664,0.054726,0.567883,0.782408,0.107263,0.554063,0.384504,0.05933,0.437776,0.670351,0.116287,0.519807,0.329124,0.048527,0.424695,0.61492,0.095112,0.611939,0.362648,0.055303,0.503545,0.720334,0.108395,0.099645,0.200208,0.031267,0.038361,0.160929,0.061284,-0.235559,0.272197,0.042001,-0.317881,-0.153237,0.082322
11
+ tabsyn,TabSyn,40,"c,m,n",0.37393,0.309929,0.049628,0.276658,0.471201,0.097272,0.671617,0.334439,0.05574,0.562367,0.780867,0.10925,0.534691,0.371208,0.061868,0.41343,0.655952,0.121261,0.508789,0.309924,0.049003,0.412743,0.604835,0.096046,0.600713,0.344419,0.056622,0.489733,0.711692,0.11098,0.112999,0.217089,0.036695,0.041077,0.184921,0.071922,-0.239277,0.279113,0.046519,-0.330454,-0.1481,0.091177
12
+ tvae,TVAE,49,"c,m,n",0.370008,0.293444,0.042355,0.286992,0.453024,0.083016,0.646445,0.312643,0.046606,0.555098,0.737793,0.091348,0.461115,0.34754,0.051808,0.359571,0.562659,0.101544,0.482923,0.292488,0.041784,0.401026,0.564819,0.081897,0.552611,0.325201,0.047948,0.458633,0.64659,0.093979,0.166815,0.18845,0.02841,0.111131,0.222498,0.055683,-0.19676,0.243951,0.036366,-0.268038,-0.125483,0.071277
evaluation/query_family/conditional/data/model_summary__c.csv ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ dataset_prefix,dataset_prefix_label,model_id,model_label,dataset_count,dependency_strength_similarity__mean,dependency_strength_similarity__std,dependency_strength_similarity__se,dependency_strength_similarity__ci95_low,dependency_strength_similarity__ci95_high,dependency_strength_similarity__ci95_radius,direction_consistency__mean,direction_consistency__std,direction_consistency__se,direction_consistency__ci95_low,direction_consistency__ci95_high,direction_consistency__ci95_radius,slice_level_consistency__mean,slice_level_consistency__std,slice_level_consistency__se,slice_level_consistency__ci95_low,slice_level_consistency__ci95_high,slice_level_consistency__ci95_radius,conditional_dependency_structure_score__mean,conditional_dependency_structure_score__std,conditional_dependency_structure_score__se,conditional_dependency_structure_score__ci95_low,conditional_dependency_structure_score__ci95_high,conditional_dependency_structure_score__ci95_radius,conditional_subgroup_score__mean,conditional_subgroup_score__std,conditional_subgroup_score__se,conditional_subgroup_score__ci95_low,conditional_subgroup_score__ci95_high,conditional_subgroup_score__ci95_radius,direction_minus_slice__mean,direction_minus_slice__std,direction_minus_slice__se,direction_minus_slice__ci95_low,direction_minus_slice__ci95_high,direction_minus_slice__ci95_radius,strength_minus_subgroup__mean,strength_minus_subgroup__std,strength_minus_subgroup__se,strength_minus_subgroup__ci95_low,strength_minus_subgroup__ci95_high,strength_minus_subgroup__ci95_radius
2
+ c,Categorical,arf,ARF,19,0.647241,0.358693,0.08229,0.485953,0.808529,0.161288,0.821978,0.282878,0.07072,0.683368,0.960589,0.13861,0.751189,0.339119,0.08756,0.579572,0.922807,0.171618,0.69526,0.350719,0.08046,0.537557,0.852962,0.157702,0.794359,0.300015,0.075004,0.647352,0.941366,0.147007,0.058921,0.154213,0.039818,-0.019122,0.136963,0.078043,-0.085533,0.151551,0.037888,-0.159793,-0.011273,0.07426
3
+ c,Categorical,bayesnet,BayesNet,19,0.606439,0.363966,0.0835,0.44278,0.770099,0.163659,0.801163,0.281778,0.070445,0.663092,0.939235,0.138071,0.695539,0.34522,0.089135,0.520834,0.870245,0.174705,0.670146,0.330064,0.075722,0.521731,0.81856,0.148415,0.757866,0.300444,0.075111,0.610648,0.905083,0.147217,0.092368,0.18298,0.047245,-0.000233,0.184968,0.0926,-0.113477,0.215495,0.053874,-0.21907,-0.007884,0.105593
4
+ c,Categorical,ctgan,CTGAN,19,0.604934,0.344407,0.079012,0.450069,0.759798,0.154864,0.842486,0.236615,0.059154,0.726545,0.958427,0.115941,0.633412,0.336154,0.086795,0.463295,0.80353,0.170117,0.662516,0.309979,0.071114,0.523132,0.8019,0.139384,0.749405,0.276112,0.069028,0.61411,0.8847,0.135295,0.198573,0.185996,0.048024,0.104446,0.2927,0.094127,-0.102569,0.162836,0.040709,-0.182358,-0.022779,0.07979
5
+ c,Categorical,forestdiffusion,ForestDiffusion,19,0.508904,0.410994,0.094289,0.324099,0.69371,0.184806,0.765116,0.277404,0.069351,0.629188,0.901044,0.135928,0.529722,0.370573,0.095682,0.342186,0.717258,0.187536,0.568914,0.363163,0.083315,0.405616,0.732212,0.163298,0.662115,0.305697,0.076424,0.512324,0.811907,0.149791,0.219735,0.255798,0.066047,0.090283,0.349186,0.129452,-0.106891,0.159479,0.03987,-0.185036,-0.028747,0.078145
6
+ c,Categorical,realtabformer,RealTabFormer,19,0.730352,0.276932,0.063533,0.605828,0.854876,0.124524,0.871831,0.20995,0.052488,0.768956,0.974707,0.102876,0.832029,0.225245,0.058158,0.71804,0.946019,0.11399,0.785113,0.243394,0.055838,0.67567,0.894556,0.109443,0.857179,0.212983,0.053246,0.752818,0.961541,0.104362,0.031257,0.07233,0.018676,-0.005347,0.067861,0.036604,-0.097542,0.137816,0.034454,-0.165072,-0.030012,0.06753
7
+ c,Categorical,tabbyflow,TabbyFlow,18,0.50485,0.404515,0.095345,0.317974,0.691727,0.186876,0.720377,0.325553,0.081388,0.560857,0.879898,0.159521,0.572531,0.386454,0.099782,0.376958,0.768104,0.195573,0.587209,0.365778,0.086215,0.418229,0.75619,0.168981,0.659813,0.350052,0.087513,0.488287,0.831338,0.171525,0.129205,0.154932,0.040003,0.050799,0.207611,0.078406,-0.138981,0.215496,0.053874,-0.244574,-0.033388,0.105593
8
+ c,Categorical,tabddpm,TabDDPM,13,0.642624,0.415325,0.11519,0.416851,0.868397,0.225773,0.81479,0.297628,0.089738,0.638903,0.990677,0.175887,0.701572,0.364482,0.115259,0.475664,0.92748,0.225908,0.669457,0.387125,0.107369,0.459013,0.879901,0.210444,0.771746,0.32514,0.098033,0.579601,0.963892,0.192145,0.094697,0.098895,0.031273,0.033401,0.155993,0.061296,-0.047568,0.099991,0.030148,-0.106658,0.011523,0.059091
9
+ c,Categorical,tabdiff,TabDiff,16,0.542476,0.4035,0.100875,0.344761,0.740191,0.197715,0.792407,0.28467,0.073502,0.648344,0.93647,0.144063,0.633621,0.323327,0.086413,0.464252,0.80299,0.169369,0.634092,0.34023,0.085058,0.467379,0.800805,0.166713,0.725226,0.288175,0.074407,0.57939,0.871063,0.145837,0.143958,0.208988,0.055854,0.034484,0.253432,0.109474,-0.146585,0.238551,0.061594,-0.267309,-0.025862,0.120723
10
+ c,Categorical,tabpfgen,TabPFGen,17,0.642363,0.346973,0.084153,0.477422,0.807303,0.164941,0.815337,0.272359,0.072791,0.672667,0.958008,0.142671,0.743564,0.281975,0.078206,0.590281,0.896847,0.153283,0.682203,0.3366,0.081638,0.522194,0.842213,0.16001,0.788609,0.264322,0.070643,0.650148,0.92707,0.138461,0.057568,0.164039,0.045496,-0.031604,0.146741,0.089172,-0.072567,0.134416,0.035924,-0.142978,-0.002156,0.070411
11
+ c,Categorical,tabsyn,TabSyn,17,0.536195,0.38587,0.093587,0.352763,0.719626,0.183431,0.759827,0.277822,0.074251,0.614295,0.905359,0.145532,0.652274,0.315666,0.08755,0.480676,0.823872,0.171598,0.612264,0.328855,0.079759,0.455937,0.768592,0.156328,0.718469,0.285221,0.076228,0.569061,0.867877,0.149408,0.089078,0.179173,0.049694,-0.008321,0.186478,0.097399,-0.138556,0.239211,0.063932,-0.263862,-0.013249,0.125306
12
+ c,Categorical,tvae,TVAE,19,0.548648,0.36499,0.083734,0.384529,0.712768,0.164119,0.777613,0.252093,0.063023,0.654088,0.901138,0.123525,0.553352,0.352091,0.09091,0.375169,0.731535,0.178183,0.606235,0.319609,0.073323,0.462521,0.749949,0.143714,0.67944,0.296225,0.074056,0.53429,0.824591,0.14515,0.209435,0.178405,0.046064,0.11915,0.29972,0.090285,-0.102576,0.149097,0.037274,-0.175634,-0.029519,0.073058
evaluation/query_family/conditional/data/model_summary__m.csv ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ dataset_prefix,dataset_prefix_label,model_id,model_label,dataset_count,dependency_strength_similarity__mean,dependency_strength_similarity__std,dependency_strength_similarity__se,dependency_strength_similarity__ci95_low,dependency_strength_similarity__ci95_high,dependency_strength_similarity__ci95_radius,direction_consistency__mean,direction_consistency__std,direction_consistency__se,direction_consistency__ci95_low,direction_consistency__ci95_high,direction_consistency__ci95_radius,slice_level_consistency__mean,slice_level_consistency__std,slice_level_consistency__se,slice_level_consistency__ci95_low,slice_level_consistency__ci95_high,slice_level_consistency__ci95_radius,conditional_dependency_structure_score__mean,conditional_dependency_structure_score__std,conditional_dependency_structure_score__se,conditional_dependency_structure_score__ci95_low,conditional_dependency_structure_score__ci95_high,conditional_dependency_structure_score__ci95_radius,conditional_subgroup_score__mean,conditional_subgroup_score__std,conditional_subgroup_score__se,conditional_subgroup_score__ci95_low,conditional_subgroup_score__ci95_high,conditional_subgroup_score__ci95_radius,direction_minus_slice__mean,direction_minus_slice__std,direction_minus_slice__se,direction_minus_slice__ci95_low,direction_minus_slice__ci95_high,direction_minus_slice__ci95_radius,strength_minus_subgroup__mean,strength_minus_subgroup__std,strength_minus_subgroup__se,strength_minus_subgroup__ci95_low,strength_minus_subgroup__ci95_high,strength_minus_subgroup__ci95_radius
2
+ m,Mixed,arf,ARF,11,0.373675,0.168982,0.05095,0.273813,0.473538,0.099862,0.754495,0.26245,0.079132,0.599397,0.909593,0.155098,0.633554,0.335458,0.101145,0.43531,0.831797,0.198243,0.587241,0.225536,0.068002,0.453958,0.720525,0.133283,0.694024,0.281099,0.084754,0.527906,0.860143,0.166119,0.120942,0.216238,0.065198,-0.006847,0.24873,0.127788,-0.320349,0.225795,0.06808,-0.453785,-0.186913,0.133436
3
+ m,Mixed,bayesnet,BayesNet,11,0.387586,0.138259,0.041687,0.30588,0.469291,0.081706,0.778261,0.271596,0.081889,0.617758,0.938764,0.160503,0.668552,0.315462,0.095115,0.482126,0.854978,0.186426,0.611466,0.222321,0.067032,0.480083,0.742849,0.131383,0.723406,0.28035,0.084529,0.55773,0.889083,0.165677,0.109708,0.179375,0.054084,0.003704,0.215712,0.106004,-0.335821,0.205045,0.061823,-0.456995,-0.214647,0.121174
4
+ m,Mixed,ctgan,CTGAN,11,0.361071,0.110692,0.033375,0.295656,0.426485,0.065415,0.666412,0.275076,0.082939,0.503852,0.828972,0.16256,0.57037,0.292292,0.088129,0.397637,0.743104,0.172734,0.532618,0.211802,0.063861,0.407451,0.657784,0.125167,0.618391,0.267618,0.08069,0.460239,0.776543,0.158152,0.096042,0.189011,0.056989,-0.015657,0.20774,0.111698,-0.25732,0.177109,0.0534,-0.361985,-0.152656,0.104665
5
+ m,Mixed,forestdiffusion,ForestDiffusion,11,0.286038,0.092576,0.027913,0.231329,0.340747,0.054709,0.686067,0.244509,0.073722,0.541571,0.830562,0.144496,0.57248,0.289687,0.087344,0.401285,0.743674,0.171194,0.514861,0.187952,0.05667,0.403789,0.625934,0.111072,0.629273,0.25062,0.075565,0.481166,0.77738,0.148107,0.113587,0.190169,0.057338,0.001204,0.22597,0.112383,-0.343235,0.20572,0.062027,-0.464808,-0.221662,0.121573
6
+ m,Mixed,realtabformer,RealTabFormer,11,0.553665,0.133539,0.040263,0.474749,0.632582,0.078916,0.831844,0.201222,0.060671,0.71293,0.950759,0.118915,0.770414,0.217839,0.065681,0.641679,0.899148,0.128734,0.718641,0.169251,0.051031,0.61862,0.818662,0.100021,0.801129,0.207017,0.062418,0.67879,0.923468,0.122339,0.061431,0.066815,0.020145,0.021946,0.100916,0.039485,-0.247464,0.162514,0.049,-0.343503,-0.151424,0.09604
7
+ m,Mixed,tabbyflow,TabbyFlow,11,0.316649,0.115147,0.034718,0.248601,0.384697,0.068048,0.705259,0.247715,0.074689,0.558869,0.851649,0.14639,0.606218,0.281704,0.084937,0.439742,0.772695,0.166476,0.542709,0.191205,0.05765,0.429714,0.655703,0.112995,0.655739,0.255281,0.07697,0.504877,0.8066,0.150861,0.099041,0.144106,0.04345,0.013879,0.184202,0.085161,-0.33909,0.225558,0.068008,-0.472386,-0.205793,0.133296
8
+ m,Mixed,tabddpm,TabDDPM,10,0.283257,0.095466,0.030189,0.224087,0.342427,0.05917,0.65593,0.24775,0.078346,0.502373,0.809487,0.153557,0.568672,0.236058,0.074648,0.422362,0.714982,0.14631,0.50262,0.171712,0.0543,0.396191,0.609048,0.106428,0.612301,0.233066,0.073702,0.467845,0.756757,0.144456,0.087258,0.130112,0.041145,0.006614,0.167902,0.080644,-0.329044,0.209635,0.066292,-0.458977,-0.199111,0.129933
9
+ m,Mixed,tabdiff,TabDiff,10,0.330346,0.123057,0.038914,0.254074,0.406617,0.076272,0.727097,0.265659,0.084009,0.562439,0.891754,0.164657,0.632618,0.289166,0.091442,0.453391,0.811846,0.179227,0.563354,0.1957,0.061886,0.442057,0.68465,0.121296,0.679858,0.259989,0.082216,0.518715,0.841001,0.161143,0.094478,0.194952,0.061649,-0.026354,0.215311,0.120832,-0.349512,0.230553,0.072907,-0.49241,-0.206614,0.142898
10
+ m,Mixed,tabpfgen,TabPFGen,11,0.338356,0.09627,0.029026,0.281464,0.395247,0.056892,0.724238,0.227246,0.068517,0.589944,0.858531,0.134294,0.626699,0.272918,0.082288,0.465415,0.787983,0.161284,0.563097,0.173821,0.052409,0.460375,0.665819,0.102722,0.675468,0.23495,0.07084,0.536621,0.814315,0.138847,0.097539,0.17732,0.053464,-0.007251,0.202328,0.10479,-0.337113,0.208673,0.062917,-0.46043,-0.213795,0.123318
11
+ m,Mixed,tabsyn,TabSyn,11,0.335304,0.114159,0.03442,0.26784,0.402767,0.067463,0.711853,0.245008,0.073873,0.567062,0.856643,0.14479,0.614785,0.291491,0.087888,0.442524,0.787045,0.17226,0.55398,0.187593,0.056561,0.44312,0.664841,0.110861,0.663319,0.255208,0.076948,0.5125,0.814137,0.150818,0.097068,0.171661,0.051758,-0.004377,0.198513,0.101445,-0.328015,0.237868,0.07172,-0.468586,-0.187444,0.140571
12
+ m,Mixed,tvae,TVAE,11,0.319999,0.092464,0.027879,0.265356,0.374641,0.054643,0.589296,0.226611,0.068326,0.455378,0.723215,0.133918,0.453103,0.19246,0.058029,0.339367,0.56684,0.113737,0.454133,0.154238,0.046504,0.362984,0.545281,0.091149,0.5212,0.19156,0.057757,0.407995,0.634404,0.113205,0.136193,0.173223,0.052229,0.033825,0.238561,0.102368,-0.201201,0.125928,0.037969,-0.27562,-0.126782,0.074419
evaluation/query_family/conditional/data/model_summary__n.csv ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ dataset_prefix,dataset_prefix_label,model_id,model_label,dataset_count,dependency_strength_similarity__mean,dependency_strength_similarity__std,dependency_strength_similarity__se,dependency_strength_similarity__ci95_low,dependency_strength_similarity__ci95_high,dependency_strength_similarity__ci95_radius,direction_consistency__mean,direction_consistency__std,direction_consistency__se,direction_consistency__ci95_low,direction_consistency__ci95_high,direction_consistency__ci95_radius,slice_level_consistency__mean,slice_level_consistency__std,slice_level_consistency__se,slice_level_consistency__ci95_low,slice_level_consistency__ci95_high,slice_level_consistency__ci95_radius,conditional_dependency_structure_score__mean,conditional_dependency_structure_score__std,conditional_dependency_structure_score__se,conditional_dependency_structure_score__ci95_low,conditional_dependency_structure_score__ci95_high,conditional_dependency_structure_score__ci95_radius,conditional_subgroup_score__mean,conditional_subgroup_score__std,conditional_subgroup_score__se,conditional_subgroup_score__ci95_low,conditional_subgroup_score__ci95_high,conditional_subgroup_score__ci95_radius,direction_minus_slice__mean,direction_minus_slice__std,direction_minus_slice__se,direction_minus_slice__ci95_low,direction_minus_slice__ci95_high,direction_minus_slice__ci95_radius,strength_minus_subgroup__mean,strength_minus_subgroup__std,strength_minus_subgroup__se,strength_minus_subgroup__ci95_low,strength_minus_subgroup__ci95_high,strength_minus_subgroup__ci95_radius
2
+ n,Numerical,arf,ARF,19,0.151132,0.137617,0.032437,0.087556,0.214708,0.063576,0.540316,0.404935,0.095444,0.353245,0.727386,0.18707,0.371473,0.417793,0.095848,0.18361,0.559335,0.187863,0.342364,0.297965,0.068358,0.208382,0.476345,0.133981,0.441816,0.397943,0.091294,0.262879,0.620753,0.178937,0.148502,0.239911,0.056547,0.037669,0.259335,0.110833,-0.314933,0.3235,0.07625,-0.464382,-0.165483,0.14945
3
+ n,Numerical,bayesnet,BayesNet,19,0.220062,0.181589,0.042801,0.136172,0.303952,0.08389,0.581967,0.393696,0.092795,0.400088,0.763845,0.181878,0.433117,0.38949,0.089355,0.257981,0.608253,0.175136,0.397708,0.295841,0.067871,0.264682,0.530735,0.133027,0.492275,0.387642,0.088931,0.317969,0.66658,0.174305,0.124889,0.17739,0.041811,0.042939,0.206839,0.08195,-0.299461,0.329767,0.077727,-0.451805,-0.147116,0.152345
4
+ n,Numerical,ctgan,CTGAN,19,0.192399,0.148362,0.034969,0.123859,0.260939,0.06854,0.51452,0.389356,0.091772,0.334646,0.694393,0.179873,0.385552,0.41138,0.094377,0.200573,0.570531,0.184979,0.351755,0.299234,0.068649,0.217203,0.486307,0.134552,0.436496,0.398184,0.09135,0.257451,0.615542,0.179045,0.107548,0.137571,0.032426,0.043993,0.171102,0.063555,-0.268347,0.330293,0.077851,-0.420935,-0.115759,0.152588
5
+ n,Numerical,forestdiffusion,ForestDiffusion,19,0.139493,0.139217,0.032814,0.075178,0.203808,0.064315,0.473912,0.405867,0.095664,0.286411,0.661414,0.187501,0.304737,0.400202,0.091813,0.124784,0.484689,0.179953,0.295286,0.2926,0.067127,0.163717,0.426855,0.131569,0.376853,0.385511,0.088442,0.203506,0.5502,0.173347,0.152246,0.250839,0.059123,0.036365,0.268128,0.115882,-0.258297,0.301885,0.071155,-0.39776,-0.118833,0.139464
6
+ n,Numerical,realtabformer,RealTabFormer,19,0.359443,0.20019,0.047185,0.26696,0.451927,0.092483,0.713309,0.300906,0.070924,0.574297,0.852321,0.139012,0.573279,0.339115,0.077798,0.420795,0.725764,0.152485,0.529857,0.26053,0.05977,0.412709,0.647005,0.117148,0.624523,0.320025,0.073419,0.480622,0.768423,0.143901,0.108181,0.216594,0.051052,0.00812,0.208242,0.100061,-0.299775,0.26042,0.061382,-0.420083,-0.179467,0.120308
7
+ n,Numerical,tabbyflow,TabbyFlow,17,0.147371,0.14198,0.034435,0.079878,0.214864,0.067493,0.458665,0.371161,0.09002,0.282226,0.635104,0.176439,0.342994,0.361446,0.087663,0.171174,0.514815,0.17182,0.316343,0.269657,0.065402,0.188156,0.44453,0.128187,0.40083,0.352979,0.08561,0.233034,0.568625,0.167796,0.115671,0.196039,0.047546,0.02248,0.208862,0.093191,-0.253459,0.277131,0.067214,-0.385199,-0.121719,0.13174
8
+ n,Numerical,tabddpm,TabDDPM,17,0.129752,0.134113,0.033528,0.064036,0.195468,0.065716,0.436933,0.404649,0.101162,0.238655,0.635211,0.198278,0.324195,0.416606,0.101042,0.126153,0.522236,0.198042,0.285848,0.309051,0.074956,0.138935,0.432762,0.146914,0.367713,0.407068,0.098728,0.174205,0.561221,0.193508,0.092477,0.119001,0.02975,0.034166,0.150787,0.05831,-0.260943,0.309974,0.077493,-0.41283,-0.109056,0.151887
9
+ n,Numerical,tabdiff,TabDiff,18,0.158624,0.135157,0.03278,0.094374,0.222873,0.06425,0.502459,0.398082,0.096549,0.313223,0.691696,0.189236,0.340223,0.391782,0.092344,0.15923,0.521217,0.180994,0.324562,0.280764,0.066177,0.194856,0.454269,0.129706,0.409661,0.374509,0.088273,0.236647,0.582675,0.173014,0.147044,0.258102,0.062599,0.024351,0.269738,0.122694,-0.270313,0.306234,0.074273,-0.415888,-0.124739,0.145575
10
+ n,Numerical,tabpfgen,TabPFGen,18,0.157259,0.140587,0.034097,0.090428,0.22409,0.066831,0.527928,0.433475,0.105133,0.321867,0.733989,0.206061,0.372813,0.436996,0.103001,0.170931,0.574695,0.201882,0.339978,0.317022,0.074723,0.193521,0.486435,0.146457,0.435706,0.421683,0.099392,0.240898,0.630514,0.194808,0.133184,0.240289,0.058279,0.018958,0.24741,0.114226,-0.304077,0.335618,0.081399,-0.46362,-0.144534,0.159543
11
+ n,Numerical,tabsyn,TabSyn,12,0.161783,0.133559,0.04027,0.082855,0.240712,0.078928,0.519114,0.439142,0.132406,0.259598,0.77863,0.259516,0.333891,0.43099,0.124416,0.090035,0.577746,0.243856,0.320773,0.306762,0.088554,0.147207,0.49434,0.173567,0.405941,0.412216,0.118996,0.172708,0.639174,0.233233,0.157201,0.298448,0.089985,-0.019171,0.333572,0.176371,-0.27873,0.342223,0.103184,-0.480971,-0.076489,0.202241
12
+ n,Numerical,tvae,TVAE,19,0.212005,0.168125,0.039627,0.134335,0.289675,0.07767,0.564776,0.37595,0.088612,0.391096,0.738456,0.17368,0.392935,0.407696,0.093532,0.209613,0.576258,0.183322,0.376278,0.290178,0.066571,0.245798,0.506758,0.13048,0.463993,0.384302,0.088165,0.29119,0.636797,0.172803,0.150011,0.208465,0.049136,0.053706,0.246317,0.096306,-0.277766,0.331329,0.078095,-0.430832,-0.1247,0.153066
evaluation/query_family/conditional/data/prefix_plot_data.csv ADDED
@@ -0,0 +1,13 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ model_id,model_label,c,m,n
2
+ REAL,REAL,1.0,1.0,1.0
3
+ arf,ARF,0.794359,0.694024,0.441816
4
+ bayesnet,BayesNet,0.757866,0.723406,0.492275
5
+ ctgan,CTGAN,0.749405,0.618391,0.436496
6
+ forestdiffusion,ForestDiffusion,0.662115,0.629273,0.376853
7
+ realtabformer,RealTabFormer,0.857179,0.801129,0.624523
8
+ tabbyflow,TabbyFlow,0.659813,0.655739,0.40083
9
+ tabddpm,TabDDPM,0.771746,0.612301,0.367713
10
+ tabdiff,TabDiff,0.725226,0.679858,0.409661
11
+ tabpfgen,TabPFGen,0.788609,0.675468,0.435706
12
+ tabsyn,TabSyn,0.718469,0.663319,0.405941
13
+ tvae,TVAE,0.67944,0.5212,0.463993
evaluation/query_family/conditional/data/prefix_summary.csv ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ model_id,model_label,dataset_prefix,dataset_prefix_label,dataset_count,dependency_strength_similarity,direction_consistency,slice_level_consistency,conditional_dependency_structure_score,conditional_subgroup_score,direction_minus_slice,strength_minus_subgroup
2
+ arf,ARF,c,Categorical,19,0.647241,0.821978,0.751189,0.69526,0.794359,0.058921,-0.085533
3
+ arf,ARF,m,Mixed,11,0.373675,0.754495,0.633554,0.587241,0.694024,0.120942,-0.320349
4
+ arf,ARF,n,Numerical,19,0.151132,0.540316,0.371473,0.342364,0.441816,0.148502,-0.314933
5
+ bayesnet,BayesNet,c,Categorical,19,0.606439,0.801163,0.695539,0.670146,0.757866,0.092368,-0.113477
6
+ bayesnet,BayesNet,m,Mixed,11,0.387586,0.778261,0.668552,0.611466,0.723406,0.109708,-0.335821
7
+ bayesnet,BayesNet,n,Numerical,19,0.220062,0.581967,0.433117,0.397708,0.492275,0.124889,-0.299461
8
+ ctgan,CTGAN,c,Categorical,19,0.604934,0.842486,0.633412,0.662516,0.749405,0.198573,-0.102569
9
+ ctgan,CTGAN,m,Mixed,11,0.361071,0.666412,0.57037,0.532618,0.618391,0.096042,-0.25732
10
+ ctgan,CTGAN,n,Numerical,19,0.192399,0.51452,0.385552,0.351755,0.436496,0.107548,-0.268347
11
+ forestdiffusion,ForestDiffusion,c,Categorical,19,0.508904,0.765116,0.529722,0.568914,0.662115,0.219735,-0.106891
12
+ forestdiffusion,ForestDiffusion,m,Mixed,11,0.286038,0.686067,0.57248,0.514861,0.629273,0.113587,-0.343235
13
+ forestdiffusion,ForestDiffusion,n,Numerical,19,0.139493,0.473912,0.304737,0.295286,0.376853,0.152246,-0.258297
14
+ realtabformer,RealTabFormer,c,Categorical,19,0.730352,0.871831,0.832029,0.785113,0.857179,0.031257,-0.097542
15
+ realtabformer,RealTabFormer,m,Mixed,11,0.553665,0.831844,0.770414,0.718641,0.801129,0.061431,-0.247464
16
+ realtabformer,RealTabFormer,n,Numerical,19,0.359443,0.713309,0.573279,0.529857,0.624523,0.108181,-0.299775
17
+ tabbyflow,TabbyFlow,c,Categorical,18,0.50485,0.720377,0.572531,0.587209,0.659813,0.129205,-0.138981
18
+ tabbyflow,TabbyFlow,m,Mixed,11,0.316649,0.705259,0.606218,0.542709,0.655739,0.099041,-0.33909
19
+ tabbyflow,TabbyFlow,n,Numerical,17,0.147371,0.458665,0.342994,0.316343,0.40083,0.115671,-0.253459
20
+ tabddpm,TabDDPM,c,Categorical,13,0.642624,0.81479,0.701572,0.669457,0.771746,0.094697,-0.047568
21
+ tabddpm,TabDDPM,m,Mixed,10,0.283257,0.65593,0.568672,0.50262,0.612301,0.087258,-0.329044
22
+ tabddpm,TabDDPM,n,Numerical,17,0.129752,0.436933,0.324195,0.285848,0.367713,0.092477,-0.260943
23
+ tabdiff,TabDiff,c,Categorical,16,0.542476,0.792407,0.633621,0.634092,0.725226,0.143958,-0.146585
24
+ tabdiff,TabDiff,m,Mixed,10,0.330346,0.727097,0.632618,0.563354,0.679858,0.094478,-0.349512
25
+ tabdiff,TabDiff,n,Numerical,18,0.158624,0.502459,0.340223,0.324562,0.409661,0.147044,-0.270313
26
+ tabpfgen,TabPFGen,c,Categorical,17,0.642363,0.815337,0.743564,0.682203,0.788609,0.057568,-0.072567
27
+ tabpfgen,TabPFGen,m,Mixed,11,0.338356,0.724238,0.626699,0.563097,0.675468,0.097539,-0.337113
28
+ tabpfgen,TabPFGen,n,Numerical,18,0.157259,0.527928,0.372813,0.339978,0.435706,0.133184,-0.304077
29
+ tabsyn,TabSyn,c,Categorical,17,0.536195,0.759827,0.652274,0.612264,0.718469,0.089078,-0.138556
30
+ tabsyn,TabSyn,m,Mixed,11,0.335304,0.711853,0.614785,0.55398,0.663319,0.097068,-0.328015
31
+ tabsyn,TabSyn,n,Numerical,12,0.161783,0.519114,0.333891,0.320773,0.405941,0.157201,-0.27873
32
+ tvae,TVAE,c,Categorical,19,0.548648,0.777613,0.553352,0.606235,0.67944,0.209435,-0.102576
33
+ tvae,TVAE,m,Mixed,11,0.319999,0.589296,0.453103,0.454133,0.5212,0.136193,-0.201201
34
+ tvae,TVAE,n,Numerical,19,0.212005,0.564776,0.392935,0.376278,0.463993,0.150011,-0.277766
evaluation/query_family/conditional/figures/conditional_model_subitem_heatmap_appendix.tex ADDED
@@ -0,0 +1,21 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \documentclass{standalone}
2
+ \usepackage[table]{xcolor}
3
+ \usepackage{xcolor}
4
+ \usepackage{booktabs}
5
+
6
+ \begin{document}
7
+ \scriptsize
8
+ \textbf{Conditional model-subitem heatmap}\\[0.4em]
9
+ \emph{Mean score, 0--1; missing cells stay white.}\\[0.5em]
10
+ \setlength{\tabcolsep}{4pt}
11
+ \begin{tabular}{lccccccccccc}
12
+ \toprule
13
+ Subitem & ARF & BayesNet & CTGAN & ForestDiffusion & RealTabFormer & TabbyFlow & TabDDPM & TabDiff & TabPFGen & TabSyn & TVAE \\
14
+ \midrule
15
+ Dependency strength similarity & \cellcolor[HTML]{73C8BD} & \cellcolor[HTML]{6DC6BE} & \cellcolor[HTML]{76CABC} & \cellcolor[HTML]{A0DAB8} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{9CD8B8} & \cellcolor[HTML]{92D5B9} & \cellcolor[HTML]{92D5B9} & \cellcolor[HTML]{7ACBBC} & \cellcolor[HTML]{80CEBB} & \cellcolor[HTML]{83CEBB} \\
16
+ Direction consistency & \cellcolor[HTML]{2075B3} & \cellcolor[HTML]{206EB0} & \cellcolor[HTML]{1F7EB7} & \cellcolor[HTML]{1D8EBF} & \cellcolor[HTML]{234DA0} & \cellcolor[HTML]{2094C0} & \cellcolor[HTML]{2296C1} & \cellcolor[HTML]{1E83BA} & \cellcolor[HTML]{1F7DB6} & \cellcolor[HTML]{1F7EB7} & \cellcolor[HTML]{1E88BC} \\
17
+ Slice-level consistency & \cellcolor[HTML]{2FA4C2} & \cellcolor[HTML]{2A9EC1} & \cellcolor[HTML]{3DB2C4} & \cellcolor[HTML]{5DC0C0} & \cellcolor[HTML]{206EB0} & \cellcolor[HTML]{46B8C3} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{3FB4C4} & \cellcolor[HTML]{32A6C2} & \cellcolor[HTML]{37ACC3} & \cellcolor[HTML]{53BDC1} \\
18
+ Family mean & \cellcolor[HTML]{37ACC3} & \cellcolor[HTML]{32A6C2} & \cellcolor[HTML]{3DB2C4} & \cellcolor[HTML]{59BFC0} & \cellcolor[HTML]{1F7EB7} & \cellcolor[HTML]{4EBBC2} & \cellcolor[HTML]{53BDC1} & \cellcolor[HTML]{46B8C3} & \cellcolor[HTML]{3BB0C3} & \cellcolor[HTML]{3EB3C4} & \cellcolor[HTML]{4AB9C3} \\
19
+ \bottomrule
20
+ \end{tabular}
21
+ \end{document}
evaluation/query_family/conditional/final/v2/model_summary__m__v2.csv ADDED
@@ -0,0 +1,12 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ dataset_prefix,dataset_prefix_label,model_id,model_label,dataset_count,dependency_strength_similarity__mean,dependency_strength_similarity__std,dependency_strength_similarity__se,dependency_strength_similarity__ci95_low,dependency_strength_similarity__ci95_high,dependency_strength_similarity__ci95_radius,direction_consistency__mean,direction_consistency__std,direction_consistency__se,direction_consistency__ci95_low,direction_consistency__ci95_high,direction_consistency__ci95_radius,slice_level_consistency__mean,slice_level_consistency__std,slice_level_consistency__se,slice_level_consistency__ci95_low,slice_level_consistency__ci95_high,slice_level_consistency__ci95_radius,conditional_dependency_structure_score__mean,conditional_dependency_structure_score__std,conditional_dependency_structure_score__se,conditional_dependency_structure_score__ci95_low,conditional_dependency_structure_score__ci95_high,conditional_dependency_structure_score__ci95_radius,conditional_subgroup_score__mean,conditional_subgroup_score__std,conditional_subgroup_score__se,conditional_subgroup_score__ci95_low,conditional_subgroup_score__ci95_high,conditional_subgroup_score__ci95_radius,direction_minus_slice__mean,direction_minus_slice__std,direction_minus_slice__se,direction_minus_slice__ci95_low,direction_minus_slice__ci95_high,direction_minus_slice__ci95_radius,strength_minus_subgroup__mean,strength_minus_subgroup__std,strength_minus_subgroup__se,strength_minus_subgroup__ci95_low,strength_minus_subgroup__ci95_high,strength_minus_subgroup__ci95_radius
2
+ m,Mixed,arf,ARF,11,0.373675,0.168982,0.05095,0.273813,0.473538,0.099862,0.754495,0.26245,0.079132,0.599397,0.909593,0.155098,0.633554,0.335458,0.101145,0.43531,0.831797,0.198243,0.587241,0.225536,0.068002,0.453958,0.720525,0.133283,0.694024,0.281099,0.084754,0.527906,0.860143,0.166119,0.120942,0.216238,0.065198,-0.006847,0.24873,0.127788,-0.320349,0.225795,0.06808,-0.453785,-0.186913,0.133436
3
+ m,Mixed,bayesnet,BayesNet,11,0.387586,0.138259,0.041687,0.30588,0.469291,0.081706,0.778261,0.271596,0.081889,0.617758,0.938764,0.160503,0.668552,0.315462,0.095115,0.482126,0.854978,0.186426,0.611466,0.222321,0.067032,0.480083,0.742849,0.131383,0.723406,0.28035,0.084529,0.55773,0.889083,0.165677,0.109708,0.179375,0.054084,0.003704,0.215712,0.106004,-0.335821,0.205045,0.061823,-0.456995,-0.214647,0.121174
4
+ m,Mixed,ctgan,CTGAN,11,0.361071,0.110692,0.033375,0.295656,0.426485,0.065415,0.666412,0.275076,0.082939,0.503852,0.828972,0.16256,0.57037,0.292292,0.088129,0.397637,0.743104,0.172734,0.532618,0.211802,0.063861,0.407451,0.657784,0.125167,0.618391,0.267618,0.08069,0.460239,0.776543,0.158152,0.096042,0.189011,0.056989,-0.015657,0.20774,0.111698,-0.25732,0.177109,0.0534,-0.361985,-0.152656,0.104665
5
+ m,Mixed,forestdiffusion,ForestDiffusion,11,0.286038,0.092576,0.027913,0.231329,0.340747,0.054709,0.686067,0.244509,0.073722,0.541571,0.830562,0.144496,0.57248,0.289687,0.087344,0.401285,0.743674,0.171194,0.514861,0.187952,0.05667,0.403789,0.625934,0.111072,0.629273,0.25062,0.075565,0.481166,0.77738,0.148107,0.113587,0.190169,0.057338,0.001204,0.22597,0.112383,-0.343235,0.20572,0.062027,-0.464808,-0.221662,0.121573
6
+ m,Mixed,realtabformer,RealTabFormer,11,0.553665,0.133539,0.040263,0.474749,0.632582,0.078916,0.831844,0.201222,0.060671,0.71293,0.950759,0.118915,0.770414,0.217839,0.065681,0.641679,0.899148,0.128734,0.718641,0.169251,0.051031,0.61862,0.818662,0.100021,0.801129,0.207017,0.062418,0.67879,0.923468,0.122339,0.061431,0.066815,0.020145,0.021946,0.100916,0.039485,-0.247464,0.162514,0.049,-0.343503,-0.151424,0.09604
7
+ m,Mixed,tabbyflow,TabbyFlow,11,0.316649,0.115147,0.034718,0.248601,0.384697,0.068048,0.705259,0.247715,0.074689,0.558869,0.851649,0.14639,0.606218,0.281704,0.084937,0.439742,0.772695,0.166476,0.542709,0.191205,0.05765,0.429714,0.655703,0.112995,0.655739,0.255281,0.07697,0.504877,0.8066,0.150861,0.099041,0.144106,0.04345,0.013879,0.184202,0.085161,-0.33909,0.225558,0.068008,-0.472386,-0.205793,0.133296
8
+ m,Mixed,tabddpm,TabDDPM,10,0.283257,0.095466,0.030189,0.224087,0.342427,0.05917,0.65593,0.24775,0.078346,0.502373,0.809487,0.153557,0.568672,0.236058,0.074648,0.422362,0.714982,0.14631,0.50262,0.171712,0.0543,0.396191,0.609048,0.106428,0.612301,0.233066,0.073702,0.467845,0.756757,0.144456,0.087258,0.130112,0.041145,0.006614,0.167902,0.080644,-0.329044,0.209635,0.066292,-0.458977,-0.199111,0.129933
9
+ m,Mixed,tabdiff,TabDiff,10,0.330346,0.123057,0.038914,0.254074,0.406617,0.076272,0.727097,0.265659,0.084009,0.562439,0.891754,0.164657,0.632618,0.289166,0.091442,0.453391,0.811846,0.179227,0.563354,0.1957,0.061886,0.442057,0.68465,0.121296,0.679858,0.259989,0.082216,0.518715,0.841001,0.161143,0.094478,0.194952,0.061649,-0.026354,0.215311,0.120832,-0.349512,0.230553,0.072907,-0.49241,-0.206614,0.142898
10
+ m,Mixed,tabpfgen,TabPFGen,11,0.338356,0.09627,0.029026,0.281464,0.395247,0.056892,0.724238,0.227246,0.068517,0.589944,0.858531,0.134294,0.626699,0.272918,0.082288,0.465415,0.787983,0.161284,0.563097,0.173821,0.052409,0.460375,0.665819,0.102722,0.675468,0.23495,0.07084,0.536621,0.814315,0.138847,0.097539,0.17732,0.053464,-0.007251,0.202328,0.10479,-0.337113,0.208673,0.062917,-0.46043,-0.213795,0.123318
11
+ m,Mixed,tabsyn,TabSyn,11,0.335304,0.114159,0.03442,0.26784,0.402767,0.067463,0.711853,0.245008,0.073873,0.567062,0.856643,0.14479,0.614785,0.291491,0.087888,0.442524,0.787045,0.17226,0.55398,0.187593,0.056561,0.44312,0.664841,0.110861,0.663319,0.255208,0.076948,0.5125,0.814137,0.150818,0.097068,0.171661,0.051758,-0.004377,0.198513,0.101445,-0.328015,0.237868,0.07172,-0.468586,-0.187444,0.140571
12
+ m,Mixed,tvae,TVAE,11,0.319999,0.092464,0.027879,0.265356,0.374641,0.054643,0.589296,0.226611,0.068326,0.455378,0.723215,0.133918,0.453103,0.19246,0.058029,0.339367,0.56684,0.113737,0.454133,0.154238,0.046504,0.362984,0.545281,0.091149,0.5212,0.19156,0.057757,0.407995,0.634404,0.113205,0.136193,0.173223,0.052229,0.033825,0.238561,0.102368,-0.201201,0.125928,0.037969,-0.27562,-0.126782,0.074419
evaluation/query_family/conditional/locality_support_diagnostics/LATEST_RUN.json ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+ {
2
+ "run_tag": "20260524_090854_conditional_locality_support",
3
+ "run_dir": "/data/jialinzhang/TabQueryBench/code_snapshot/Evaluation/query_fivepart_breakdown/conditional_breakdown/locality_support_diagnostics/runs/20260524_090854_conditional_locality_support",
4
+ "generated_at_utc": "2026-05-24T09:10:34.258498+00:00"
5
+ }
evaluation/query_family/conditional/locality_support_diagnostics/README.md CHANGED
@@ -1,32 +1,19 @@
1
- # Conditional Locality/Support Diagnostics
2
 
3
- Paper-facing assets mirrored from the latest standalone conditional locality/support diagnostic run.
4
 
5
- Primary paper-facing files:
6
 
7
- - `fig_conditional_locality_main.pdf`
8
- - `fig_conditional_support_main.pdf`
9
- - `fig_conditional_locality_support_combined.pdf`
10
- - `paper_caption.txt`
11
- - `paper_paragraphs.md`
12
- - `conditional_locality_support_report.md`
13
 
14
- Must-do bundle (`must_do/`):
15
 
16
- - `must_do/fig_conditional_locality_main.pdf`
17
- - `must_do/fig_conditional_support_main.pdf`
18
- - `must_do/fig_conditional_locality_support_combined.pdf`
19
- - `must_do/fig_conditional_locality_main.png`
20
- - `must_do/fig_conditional_support_main.png`
21
- - `must_do/fig_conditional_locality_support_combined.png`
22
 
23
- Support files:
24
 
25
- - `conditional_template_mapping.csv`
26
- - `conditional_locality_summary.csv`
27
- - `conditional_support_bucket_summary.csv`
28
- - `conditional_support_method_audit.csv`
29
-
30
-
31
- Latest run: `20260519_192327_conditional_locality_support`
32
- Primary support variant: `all_filtered_local`
 
1
+ # Conditional locality/support diagnostics
2
 
3
+ This directory contains a standalone paper-facing diagnostic built on top of the frozen conditional breakdown outputs and the existing upstream analysis artifacts.
4
 
5
+ ## Latest run
6
 
7
+ - `20260524_090854_conditional_locality_support`
 
 
 
 
 
8
 
9
+ ## Re-run
10
 
11
+ ```bash
12
+ python src/eval/query_fivepart_breakdown/conditional_breakdown/conditional_locality_support_diagnostic.py
13
+ ```
 
 
 
14
 
15
+ ## Output structure
16
 
17
+ - `runs/<timestamp>_conditional_locality_support/` holds the full reproducible bundle for one run.
18
+ - `final/` mirrors the paper-facing assets from the latest run.
19
+ - `final/must_do/` keeps the minimum figure bundle for paper drafting.
 
 
 
 
 
evaluation/query_family/conditional/locality_support_diagnostics/manifest.json ADDED
@@ -0,0 +1,240 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "task": "conditional_locality_support_diagnostic",
3
+ "generated_at_utc": "2026-05-24T09:10:34.236847+00:00",
4
+ "source_analysis_run": "20260524_encodingrepair_v2_analysis_merged49",
5
+ "source_conditional_root": "/data/jialinzhang/TabQueryBench/code_snapshot/Evaluation/query_fivepart_breakdown/conditional_breakdown",
6
+ "run_tag": "20260524_090854_conditional_locality_support",
7
+ "run_dir": "/data/jialinzhang/TabQueryBench/code_snapshot/Evaluation/query_fivepart_breakdown/conditional_breakdown/locality_support_diagnostics/runs/20260524_090854_conditional_locality_support",
8
+ "primary_support_variant": "all_filtered_local",
9
+ "primary_support_reason": "primary_scalar_variant_missing",
10
+ "coverage": {
11
+ "conditional_query_rows": 17606,
12
+ "locality_dataset_model_panels": 404,
13
+ "filtered_local_query_rows": 2317,
14
+ "support_unique_cases": 223,
15
+ "support_primary_panel_rows": 648
16
+ },
17
+ "support_method_summary": {
18
+ "case_count": 223,
19
+ "template_count": 1,
20
+ "mode_counts": {
21
+ "exact": 187,
22
+ "unavailable": 36
23
+ },
24
+ "sql_artifact_found_count": 196,
25
+ "sql_artifact_missing_count": 27,
26
+ "main_eligible_case_count": 0
27
+ },
28
+ "support_variant_summary": {
29
+ "scalar_filtered_local": {
30
+ "eligible_case_count": 0,
31
+ "supported_dataset_count": 0,
32
+ "unsupported_dataset_count": 0,
33
+ "dataset_notes": []
34
+ },
35
+ "all_filtered_local": {
36
+ "eligible_case_count": 187,
37
+ "supported_dataset_count": 21,
38
+ "unsupported_dataset_count": 2,
39
+ "dataset_notes": [
40
+ {
41
+ "analysis_variant": "all_filtered_local",
42
+ "dataset_id": "c4",
43
+ "case_count": 9,
44
+ "unique_support_values": 9,
45
+ "bucketing_status": "ok"
46
+ },
47
+ {
48
+ "analysis_variant": "all_filtered_local",
49
+ "dataset_id": "c5",
50
+ "case_count": 2,
51
+ "unique_support_values": 2,
52
+ "bucketing_status": "unsupported_degenerate_within_dataset"
53
+ },
54
+ {
55
+ "analysis_variant": "all_filtered_local",
56
+ "dataset_id": "m4",
57
+ "case_count": 8,
58
+ "unique_support_values": 8,
59
+ "bucketing_status": "ok"
60
+ },
61
+ {
62
+ "analysis_variant": "all_filtered_local",
63
+ "dataset_id": "m10",
64
+ "case_count": 9,
65
+ "unique_support_values": 9,
66
+ "bucketing_status": "ok"
67
+ },
68
+ {
69
+ "analysis_variant": "all_filtered_local",
70
+ "dataset_id": "n8",
71
+ "case_count": 4,
72
+ "unique_support_values": 4,
73
+ "bucketing_status": "ok"
74
+ },
75
+ {
76
+ "analysis_variant": "all_filtered_local",
77
+ "dataset_id": "c7",
78
+ "case_count": 9,
79
+ "unique_support_values": 9,
80
+ "bucketing_status": "ok"
81
+ },
82
+ {
83
+ "analysis_variant": "all_filtered_local",
84
+ "dataset_id": "c8",
85
+ "case_count": 9,
86
+ "unique_support_values": 9,
87
+ "bucketing_status": "ok"
88
+ },
89
+ {
90
+ "analysis_variant": "all_filtered_local",
91
+ "dataset_id": "n15",
92
+ "case_count": 9,
93
+ "unique_support_values": 7,
94
+ "bucketing_status": "ok"
95
+ },
96
+ {
97
+ "analysis_variant": "all_filtered_local",
98
+ "dataset_id": "m7",
99
+ "case_count": 9,
100
+ "unique_support_values": 9,
101
+ "bucketing_status": "ok"
102
+ },
103
+ {
104
+ "analysis_variant": "all_filtered_local",
105
+ "dataset_id": "c16",
106
+ "case_count": 9,
107
+ "unique_support_values": 7,
108
+ "bucketing_status": "ok"
109
+ },
110
+ {
111
+ "analysis_variant": "all_filtered_local",
112
+ "dataset_id": "c17",
113
+ "case_count": 8,
114
+ "unique_support_values": 5,
115
+ "bucketing_status": "ok"
116
+ },
117
+ {
118
+ "analysis_variant": "all_filtered_local",
119
+ "dataset_id": "m6",
120
+ "case_count": 9,
121
+ "unique_support_values": 9,
122
+ "bucketing_status": "ok"
123
+ },
124
+ {
125
+ "analysis_variant": "all_filtered_local",
126
+ "dataset_id": "n17",
127
+ "case_count": 9,
128
+ "unique_support_values": 7,
129
+ "bucketing_status": "ok"
130
+ },
131
+ {
132
+ "analysis_variant": "all_filtered_local",
133
+ "dataset_id": "c11",
134
+ "case_count": 9,
135
+ "unique_support_values": 9,
136
+ "bucketing_status": "ok"
137
+ },
138
+ {
139
+ "analysis_variant": "all_filtered_local",
140
+ "dataset_id": "n5",
141
+ "case_count": 9,
142
+ "unique_support_values": 7,
143
+ "bucketing_status": "ok"
144
+ },
145
+ {
146
+ "analysis_variant": "all_filtered_local",
147
+ "dataset_id": "c9",
148
+ "case_count": 9,
149
+ "unique_support_values": 6,
150
+ "bucketing_status": "ok"
151
+ },
152
+ {
153
+ "analysis_variant": "all_filtered_local",
154
+ "dataset_id": "c19",
155
+ "case_count": 8,
156
+ "unique_support_values": 7,
157
+ "bucketing_status": "ok"
158
+ },
159
+ {
160
+ "analysis_variant": "all_filtered_local",
161
+ "dataset_id": "c18",
162
+ "case_count": 8,
163
+ "unique_support_values": 8,
164
+ "bucketing_status": "ok"
165
+ },
166
+ {
167
+ "analysis_variant": "all_filtered_local",
168
+ "dataset_id": "n19",
169
+ "case_count": 6,
170
+ "unique_support_values": 2,
171
+ "bucketing_status": "unsupported_degenerate_within_dataset"
172
+ },
173
+ {
174
+ "analysis_variant": "all_filtered_local",
175
+ "dataset_id": "c14",
176
+ "case_count": 9,
177
+ "unique_support_values": 9,
178
+ "bucketing_status": "ok"
179
+ },
180
+ {
181
+ "analysis_variant": "all_filtered_local",
182
+ "dataset_id": "n12",
183
+ "case_count": 8,
184
+ "unique_support_values": 4,
185
+ "bucketing_status": "ok"
186
+ },
187
+ {
188
+ "analysis_variant": "all_filtered_local",
189
+ "dataset_id": "c15",
190
+ "case_count": 9,
191
+ "unique_support_values": 9,
192
+ "bucketing_status": "ok"
193
+ },
194
+ {
195
+ "analysis_variant": "all_filtered_local",
196
+ "dataset_id": "c10",
197
+ "case_count": 9,
198
+ "unique_support_values": 9,
199
+ "bucketing_status": "ok"
200
+ }
201
+ ]
202
+ }
203
+ },
204
+ "compile_notes": {
205
+ "fig_conditional_locality_main": {
206
+ "success": false,
207
+ "note": "latexmk not available"
208
+ },
209
+ "fig_conditional_locality_by_model": {
210
+ "success": false,
211
+ "note": "latexmk not available"
212
+ },
213
+ "fig_conditional_support_main": {
214
+ "success": false,
215
+ "note": "latexmk not available"
216
+ },
217
+ "fig_conditional_support_by_model": {
218
+ "success": false,
219
+ "note": "latexmk not available"
220
+ },
221
+ "fig_conditional_locality_support_combined": {
222
+ "success": false,
223
+ "note": "latexmk not available"
224
+ },
225
+ "table_conditional_locality_summary": {
226
+ "success": false,
227
+ "note": "latexmk not available"
228
+ },
229
+ "table_conditional_support_summary": {
230
+ "success": false,
231
+ "note": "latexmk not available"
232
+ }
233
+ },
234
+ "key_findings": {
235
+ "locality_global": "Across panel means, conditional fidelity declines from grouped/global summaries (0.497) to 2D surfaces (0.949) and then to filtered/local slices (0.524).",
236
+ "locality_model": "The strongest grouped/global to filtered/local drop appears for TVAE, falling from 0.486 to 0.405.",
237
+ "support_global": "Within the exact-support filtered-local subset, dense slices score 0.591, medium slices 0.547, and sparse slices 0.484, consistent with a sparse-support penalty.",
238
+ "support_model": "Model behavior is mixed: 11 models have positive dense-minus-sparse gaps and 0 show the reverse; the largest positive gap is TVAE at 0.194."
239
+ }
240
+ }
evaluation/query_family/conditional/manifest.json ADDED
@@ -0,0 +1,69 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "task": "conditional_breakdown",
3
+ "sql_source_version": "v2",
4
+ "sql_source_label": "v2_current",
5
+ "source_analysis_run": "20260526_v2_official20_plus_c2patch_plus_subgroupconditionalrepair_merged49",
6
+ "excluded_models": [
7
+ "cdtd",
8
+ "codi",
9
+ "goggle"
10
+ ],
11
+ "included_models": [
12
+ "arf",
13
+ "bayesnet",
14
+ "ctgan",
15
+ "forestdiffusion",
16
+ "realtabformer",
17
+ "tabbyflow",
18
+ "tabddpm",
19
+ "tabdiff",
20
+ "tabpfgen",
21
+ "tabsyn",
22
+ "tvae"
23
+ ],
24
+ "dataset_panel_count": 510,
25
+ "query_row_count": 25108,
26
+ "compile_notes": {
27
+ "subgroup_tradeoff": {
28
+ "success": false,
29
+ "note": "latexmk not available"
30
+ },
31
+ "strength_bridge": {
32
+ "success": false,
33
+ "note": "latexmk not available"
34
+ },
35
+ "dumbbell": {
36
+ "success": false,
37
+ "note": "latexmk not available"
38
+ },
39
+ "heatmap": {
40
+ "success": false,
41
+ "note": "latexmk not available"
42
+ },
43
+ "prefix_bars": {
44
+ "success": false,
45
+ "note": "latexmk not available"
46
+ },
47
+ "model_subitem_heatmap": {
48
+ "success": false,
49
+ "note": "latexmk not available"
50
+ },
51
+ "family_subitem_bars": {
52
+ "success": false,
53
+ "note": "latexmk not available"
54
+ },
55
+ "prefix_bar_c": {
56
+ "success": false,
57
+ "note": "latexmk not available"
58
+ },
59
+ "prefix_tradeoff_m": {
60
+ "success": false,
61
+ "note": "latexmk not available"
62
+ },
63
+ "prefix_tradeoff_n": {
64
+ "success": false,
65
+ "note": "latexmk not available"
66
+ }
67
+ },
68
+ "publish_final": true
69
+ }
evaluation/query_family/subgroup/README.md ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Subgroup Breakdown
2
+
3
+ This directory contains a subgroup-focused decomposition analysis built from the repository's unified `analysis` outputs.
4
+
5
+ ## Inputs
6
+
7
+ - Source run: `20260526_v2_official20_plus_c2patch_plus_subgroupconditionalrepair_merged49`
8
+ - Query-level source: `Evaluation/analysis/runs/20260526_v2_official20_plus_c2patch_plus_subgroupconditionalrepair_merged49/summaries/analysis_query_scores__all_datasets.jsonl`
9
+ - Asset-level source: `Evaluation/analysis/runs/20260526_v2_official20_plus_c2patch_plus_subgroupconditionalrepair_merged49/summaries/analysis_asset_scores__all_datasets.csv`
10
+ - Canonical contract: `doc/analytics_family_subitem_contract_v1.md`
11
+
12
+ ## What this analysis exports
13
+
14
+ - deduplicated dataset-model subgroup scores
15
+ - model-level subgroup summaries
16
+ - canonical subgroup decomposition figures
17
+ - paper-ready LaTeX table snippets
18
+ - final copies under `Evaluation/query_fivepart_breakdown/subgroup_breakdown/final/`
19
+
20
+ ## Re-run
21
+
22
+ ```bash
23
+ python src/eval/query_fivepart_breakdown/subgroup_breakdown/runner.py
24
+ ```
25
+
26
+ ## TeX compilation
27
+
28
+ The runner writes standalone `.tex` files and tries `latexmk -pdf` when available.
29
+ If no local TeX compiler exists, it still exports matching preview `.pdf/.png` files for immediate inspection.
evaluation/query_family/subgroup/data/dataset_model_heatmap.csv CHANGED
@@ -1,49 +1,50 @@
1
- dataset_id,arf,bayesnet,ctgan,forestdiffusion,real,realtabformer,tabbyflow,tabddpm,tabdiff,tabpfgen,tabsyn,tvae
2
- c2,0.9950806818181819,0.9978355,0.9906795151515151,0.0,1.0,0.9978355,0.04541412303030304,0.0,0.04541412303030304,0.8700155303030304,0.04541412303030304,0.9925554242424242
3
- c3,1.0,1.0,1.0,,1.0,1.0,1.0,1.0,1.0,1.0,0.0,1.0
4
- c4,0.9862121212121212,0.9810606060606061,0.9848484848484849,0.9422222272727272,1.0,0.9962121212121212,0.9848484848484849,0.9849494999999999,0.9786363636363636,0.9849494999999999,0.9497979848484848,0.9773737424242424
5
- c5,0.9650723418181818,0.8959116533333333,0.9264980084848485,,1.0,0.9818562206060606,0.9864292272727273,0.9589960303030303,0.9270367357575757,0.9701548175757576,0.9373272509090909,0.8941904090909091
6
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- c12,0.9772267206477733,0.9903846153846154,0.9741902834008097,,1.0,0.993421052631579,,,,0.9736842105263157,,0.5035425101214575
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- c15,0.6858525157342656,0.5599161888111888,,,1.0,0.9519230769230769,,,,,0.041619375874125876,0.3239446678321678
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- c16,0.7887086923076922,0.5558508173076924,0.6290680865384616,,1.0,0.712309826923077,,,,,0.0,0.33543666346153844
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- c17,0.6816935498084291,0.6890658505747127,0.8288834597701149,,1.0,0.6943188285440614,,,,0.6638515,0.0,0.7559332624521072
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- c18,0.4643983375,0.4003761070652174,,,1.0,0.6505843809782609,,,,,0.04413182282608696,
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- c19,0.9996582337662338,0.656926409090909,0.67303937012987,,1.0,0.5195311753246753,,,,0.0,0.0,0.6745784155844157
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22
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- m8,0.9530078628205128,0.8983761974358975,0.6999387307692309,0.8533997102564103,1.0,0.9639641230769231,,0.9118780064102564,0.9548566461538461,0.9763964,0.9633981192307692,0.580714576923077
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- m12,0.8633765029761905,0.8649314791666667,0.4460177529761905,,1.0,0.8526505416666667,0.8467978244047619,,,,0.8367397053571428,0.3761376964285714
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- n1,1.0,1.0,1.0,0.0,1.0,1.0,1.0,0.0,,1.0,1.0,1.0
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- n2,0.5302675789473684,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.6250044210526317,0.0
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34
- n4,0.23488504057017545,0.19517543859649122,0.08530701754385965,,1.0,0.5735412752192983,0.24914228070175437,0.024066587719298246,,0.19517543859649122,0.23949662828947366,0.08754870065789473
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- n5,0.47325183114035085,0.38281372149122805,0.3386876918859649,0.0037954385964912283,1.0,0.4391621447368421,0.4045526524122807,0.007718578947368421,,0.4118241436403509,0.0472466524122807,0.3303209451754386
36
- n6,1.0,1.0,1.0,0.0,1.0,1.0,1.0,0.0,1.0,1.0,0.0,1.0
37
- n7,0.9358178152173913,0.9789165,0.932608695652174,0.0,1.0,0.9764190869565217,0.9660455652173913,0.8363915,,0.9897644891304349,0.9611111304347826,0.9577596847826086
38
- n8,0.06470857142857143,0.1876351749084249,0.28077292765567763,,1.0,0.2737260192307692,0.27730195787545786,,,,0.32060799267399265,0.18297101923076922
39
- n9,0.7390323626373627,0.7327906886446887,0.5908137197802198,0.0008026309523809525,1.0,0.8410697051282051,0.7050357216117216,0.7495911565934066,,0.8139476611721612,0.013285511904761904,0.6320920558608059
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- n10,0.8907868586956522,0.9323339531772575,0.8916150108695653,0.0,1.0,0.9051203315217391,0.9475333574414716,0.8866460760869566,,0.9509754770066889,0.0,0.9575170811036788
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- n11,1.0,1.0,1.0,0.0,1.0,1.0,1.0,1.0,,1.0,0.0,1.0
42
- n12,0.7476066485507247,0.4637522427536232,0.45212289130434785,0.004901958333333334,1.0,,0.010222577898550725,0.4860768405797101,,0.32335249637681157,0.00641025,0.5161750597826087
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- n14,0.24468534615384613,0.14638171153846152,0.08974355384615385,,1.0,0.2001118653846154,,0.0717949076923077,,0.08974355384615385,0.16226701923076925,0.08653843846153847
44
- n15,0.9388694842657344,0.9057275926573427,0.06390416258741258,,1.0,0.9055819300699302,,0.0,,0.9668609160839161,0.0,0.7385876468531469
45
- n16,0.0,1.0,1.0,,1.0,,,0.0,,,0.0,0.75
46
- n17,0.711438380952381,0.5866132857142857,0.6049935,,1.0,0.5954431428571428,,0.7035091666666666,,0.8013314761904761,0.024943309523809527,0.5536538095238095
47
- n18,0.5016445504385965,0.36041527192982453,0.1487374912280702,,1.0,,,,,,,0.12071836951754386
48
- n19,0.44070935054945054,0.46628966703296704,0.33072441648351647,,1.0,,,0.0264361532967033,,0.6205209917582417,,0.26012073406593406
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- n20,0.009414631578947369,0.0,0.0,,1.0,0.11557476315789472,,0.0,,0.0,0.0009473684210526316,0.0
 
 
1
+ dataset_id,arf,bayesnet,ctgan,forestdiffusion,real,realtabformer,tabbyflow,tabddpm,tabdiff,tabpfgen,tabsyn,tvae
2
+ c2,0.9895528787878788,0.9935065000000001,0.9792929393939394,0.9885198181818182,1.0,0.9935065000000001,0.8360101496969697,0.9813590606060606,0.8363348315151515,0.846717696969697,0.878772392121212,0.9895528787878788
3
+ c3,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0
4
+ c4,0.99375,0.99375,0.99375,0.9875,1.0,1.0,1.0,1.0,0.99375,1.0,0.98125,1.0
5
+ c5,0.8511111666666666,0.8427778166666666,0.8511111666666666,0.8286111666666667,1.0,0.8511111666666666,0.8461111666666666,0.8302778166666667,0.8511111666666666,0.9055556166666667,0.8386111666666667,0.8302778166666667
6
+ c6,0.55,0.552445625,0.55,0.5468039772727273,1.0,0.55,0.55119675,0.5468039772727273,0.55,0.55,0.55,0.55119675
7
+ c7,0.9780849375,0.9464342968749999,0.97356340625,0.982235875,1.0,0.950177421875,0.915886125,0.9768944687500001,0.9469644375,0.9505952343749999,0.91407753125,0.945863390625
8
+ c8,1.0,1.0,1.0,0.9722222222222222,1.0,1.0,0.9537037222222222,0.9537037222222222,0.9722222222222222,1.0,1.0,0.9606481875
9
+ c9,0.2361111111111111,0.2613191388888889,0.25922256944444444,0.2361111111111111,1.0,0.9746316527777779,0.2361111111111111,0.2361111111111111,0.2361111111111111,0.2361111111111111,0.2361111111111111,0.2607975347222222
10
+ c10,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,,0.9636752500000001
11
+ c11,0.9611444407796101,0.9578543965517241,0.943903044227886,0.9553973028485757,1.0,1.0,0.9760536379310345,0.9727011379310344,0.978385820089955,0.9863505689655172,0.9750957758620689,0.9789272068965518
12
+ c12,1.0,1.0,1.0,0.7916666666666667,1.0,1.0,,,,1.0,1.0,0.5833333333333333
13
+ c13,1.0,1.0,0.44084587499999994,1.0,1.0,1.0,1.0,0.6150252916666666,0.9631944583333334,0.049999999999999996,1.0,0.44084587499999994
14
+ c14,1.0,1.0,0.8891368749999999,0.7803075486111111,1.0,1.0,0.9934294375,0.3744110972222222,1.0,1.0,1.0,0.7529545694444444
15
+ c15,0.8685516874999999,0.7786666736111111,0.6853631458333334,0.7052959652777777,1.0,1.0,0.7306659305555556,,0.7432709930555556,0.7786666736111111,0.7432709930555556,0.5536016388888889
16
+ c16,0.875,0.64409721875,0.875,0.6398285,1.0,0.850786125,0.30767540625,,0.567617,,0.5558298125000001,0.44113071875
17
+ c17,0.6883422857142857,0.6890161428571429,0.9483648571428571,0.5178571428571429,1.0,0.551304,0.30357142857142855,,0.5378151428571429,0.6809298571428571,0.5210082857142857,0.8465467142857143
18
+ c18,0.5541593571428571,0.49750124999999995,0.59071125,0.48437389285714283,1.0,0.834777,0.32438814285714285,,,,,0.5948795
19
+ c19,1.0,1.0,0.765625,0.7991071428571428,1.0,0.5334821428571428,0.6674107142857143,,0.7991071428571428,1.0,0.8850446428571428,0.7823660714285714
20
+ c20,1.0,1.0,1.0,1.0,1.0,1.0,1.0,0.7681818181818181,,1.0,1.0,1.0
21
+ m1,0.9994876875,1.0,1.0,0.8879629444444443,1.0,0.8939358958333333,0.9282407222222222,0.8375,0.9375,0.9573087499999999,0.9375,0.676872673611111
22
+ m2,0.4750088333333333,0.4750078333333334,0.4750943333333334,0.47501250000000006,1.0,0.5159090000000001,0.4583665,0.4776515,,0.4750081666666667,0.4760658333333334,0.47511950000000003
23
+ m4,1.0,1.0,0.7619048571428572,1.0,1.0,1.0,1.0,0.9523808571428571,1.0,1.0,1.0,0.7619048571428572
24
+ m5,0.5525,0.5525,0.4070771666666667,0.4612570833333334,1.0,0.54027325,0.5338541666666667,0.3982809166666667,0.4915625,0.7799512500000001,0.5338541666666667,0.27898283333333335
25
+ m6,0.9850159444444444,0.9840535069444445,0.3120000347222222,0.8286696041666667,1.0,0.9529647708333333,0.9027777986111112,0.8088779444444445,0.9444444444444444,0.9086270972222222,0.9374999444444445,0.2626410347222222
26
+ m7,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,0.9409722222222222,1.0,0.9527777777777777
27
+ m8,0.493788125,0.49376968750000005,0.5011513125,0.493783,1.0,0.546287875,0.49400750000000004,0.49407675000000006,0.49425937500000006,0.49377043750000005,0.494391375,0.41595393750000004
28
+ m9,0.875323375,0.875,0.875,0.672619125,1.0,0.954241125,0.5688865,0.672619125,0.669871375,0.754485875,0.67006475,0.655365875
29
+ m10,0.8264622013888889,0.8821059444444443,0.8680555555555556,0.8206382847222222,1.0,0.9940972222222222,0.8293441736111111,0.7850693819444444,0.8296580833333334,0.8263888888888888,0.8303240347222223,0.8584876666666668
30
+ m11,0.40940806250000006,0.40938725000000004,0.43535662500000005,0.4093879375,1.0,0.5476346875,0.40984675000000004,0.4098136875,0.409857625,0.409393625,0.40990312500000003,0.42227281250000004
31
+ m12,0.6913834166666666,0.7327845,0.6656881875,0.5833469444444445,1.0,0.9637765486111112,0.7107639305555555,,0.7356208680555556,0.716615611111111,0.6915849236111111,0.6306438333333333
32
+ n1,1.0,1.0,1.0,1.0,1.0,1.0,0.5,1.0,1.0,1.0,1.0,1.0
33
+ n2,1.0,1.0,1.0,0.25,1.0,1.0,0.25,0.25,0.25,1.0,,1.0
34
+ n3,0.22251591071428573,0.22187046428571428,0.11855421428571428,0.17021373214285715,1.0,0.5030652142857144,0.17747716964285715,0.173135875,0.17733688392857144,0.15301963392857143,0.22965366071428572,0.11855421428571428
35
+ n4,0.393511725,0.39342648750000003,0.2056921125,0.3938777375,1.0,0.493808075,0.398868225,0.22271503750000002,0.39853447500000005,0.4020431125,,0.25004906250000003
36
+ n5,0.3580470416666667,0.49039865972222224,0.43616718749999994,0.3541958055555555,1.0,0.5275831805555555,0.33237845833333335,0.13425336111111114,0.3571736180555556,0.35417166666666666,,0.42243172222222225
37
+ n6,0.55,0.55,0.2125,0.55,1.0,0.55,0.55,0.55,0.55,0.55,0.55,0.2125
38
+ n7,0.55,0.55,0.55,0.55,1.0,0.55,0.55,0.534732142857143,0.55,0.55,,0.55
39
+ n8,0.6061507777777778,0.5982143333333334,0.36210322222222224,0.5426587777777778,1.0,0.6814135208333334,0.6081039027777778,,0.5579791944444444,,0.5579380694444445,0.5426587777777778
40
+ n9,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,,0.0
41
+ n10,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,,1.0
42
+ n11,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0
43
+ n12,0.14285714285714285,0.14285714285714285,0.9114194285714285,0.07142857142857142,1.0,0.9667622857142857,0.07142857142857142,0.07142857142857142,0.07142857142857142,0.07142857142857142,,0.9280722857142857
44
+ n14,0.007686,0.000618,0.0,0.0,1.0,0.097561,,0.0,0.022005,0.0,0.023041,0.0
45
+ n15,0.9444444444444444,0.9869166111111112,0.12422846527777778,0.9228395,1.0,0.9465277777777779,0.7195987777777778,0.3212962569444444,0.9444444444444444,0.9141975555555555,0.9444444444444444,0.8181671875000001
46
+ n16,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0
47
+ n17,0.08370688888888889,0.6254444027777778,0.5939584791666667,0.048475187499999996,1.0,0.6935995763888889,,0.07783188194444444,0.0768019375,0.07856441666666666,0.05058007638888889,0.5670293055555555
48
+ n18,0.13619258333333334,0.1608587013888889,0.16548364583333336,0.14601217361111113,1.0,0.26730430555555557,0.16624278472222223,,0.157228125,0.14442153472222222,0.1569427986111111,0.1555749097222222
49
+ n19,0.171568625,0.227941125,0.816144125,0.04289225,1.0,0.71287425,0.028186375,0.028186375,0.127193,0.23529412500000002,0.171568625,0.680077
50
+ n20,0.003437125,0.00013990625,0.0,0.0,1.0,0.72794584375,0.00026190625,0.0,,0.0,0.000121,0.0
evaluation/query_family/subgroup/data/dataset_model_scores.csv CHANGED
@@ -1,476 +1,560 @@
1
- dataset_id,dataset_prefix,model_id,model_label,internal_profile_stability,subgroup_size_stability,internal_profile_stability__query_count,subgroup_size_stability__query_count,subgroup_structure_score,profile_minus_size,active_subitem_count
2
- c2,c,real,REAL,1.0,1.0,25.0,33.0,1.0,0.0,2
3
- c2,c,arf,ARF,1.0,0.9901613636363636,25.0,33.0,0.9950806818181819,0.009838636363636355,2
4
- c2,c,bayesnet,BayesNet,1.0,0.995671,25.0,33.0,0.9978355,0.004329000000000027,2
5
- c2,c,ctgan,CTGAN,1.0,0.9813590303030303,25.0,33.0,0.9906795151515151,0.01864096969696971,2
6
- c2,c,forestdiffusion,ForestDiffusion,0.0,0.0,25.0,33.0,0.0,0.0,2
7
- c2,c,realtabformer,RealTabFormer,1.0,0.995671,25.0,33.0,0.9978355,0.004329000000000027,2
8
- c2,c,tabbyflow,TabbyFlow,0.07466664,0.016161606060606064,25.0,33.0,0.04541412303030304,0.05850503393939394,2
9
- c2,c,tabddpm,TabDDPM,0.0,0.0,25.0,33.0,0.0,0.0,2
10
- c2,c,tabdiff,TabDiff,0.07466664,0.016161606060606064,25.0,33.0,0.04541412303030304,0.05850503393939394,2
11
- c2,c,tabpfgen,TabPFGen,0.91,0.8300310606060606,25.0,33.0,0.8700155303030304,0.07996893939393945,2
12
- c2,c,tabsyn,TabSyn,0.07466664,0.016161606060606064,25.0,33.0,0.04541412303030304,0.05850503393939394,2
13
- c2,c,tvae,TVAE,1.0,0.9851108484848484,25.0,33.0,0.9925554242424242,0.014889151515151577,2
14
- c3,c,real,REAL,1.0,1.0,21.0,23.0,1.0,0.0,2
15
- c3,c,arf,ARF,1.0,1.0,21.0,23.0,1.0,0.0,2
16
- c3,c,bayesnet,BayesNet,1.0,1.0,21.0,23.0,1.0,0.0,2
17
- c3,c,ctgan,CTGAN,1.0,1.0,21.0,23.0,1.0,0.0,2
18
- c3,c,realtabformer,RealTabFormer,1.0,1.0,21.0,23.0,1.0,0.0,2
19
- c3,c,tabbyflow,TabbyFlow,1.0,1.0,21.0,23.0,1.0,0.0,2
20
- c3,c,tabddpm,TabDDPM,1.0,1.0,21.0,23.0,1.0,0.0,2
21
- c3,c,tabdiff,TabDiff,1.0,1.0,21.0,23.0,1.0,0.0,2
22
- c3,c,tabpfgen,TabPFGen,1.0,1.0,21.0,23.0,1.0,0.0,2
23
- c3,c,tabsyn,TabSyn,0.0,0.0,21.0,23.0,0.0,0.0,2
24
- c3,c,tvae,TVAE,1.0,1.0,21.0,23.0,1.0,0.0,2
25
- c4,c,real,REAL,1.0,1.0,25.0,33.0,1.0,0.0,2
26
- c4,c,arf,ARF,0.98,0.9924242424242424,25.0,33.0,0.9862121212121212,-0.012424242424242449,2
27
- c4,c,bayesnet,BayesNet,1.0,0.9621212121212122,25.0,33.0,0.9810606060606061,0.037878787878787845,2
28
- c4,c,ctgan,CTGAN,1.0,0.9696969696969697,25.0,33.0,0.9848484848484849,0.030303030303030276,2
29
- c4,c,forestdiffusion,ForestDiffusion,0.94,0.9444444545454546,25.0,33.0,0.9422222272727272,-0.0044444545454546125,2
30
- c4,c,realtabformer,RealTabFormer,1.0,0.9924242424242424,25.0,33.0,0.9962121212121212,0.007575757575757569,2
31
- c4,c,tabbyflow,TabbyFlow,1.0,0.9696969696969697,25.0,33.0,0.9848484848484849,0.030303030303030276,2
32
- c4,c,tabddpm,TabDDPM,0.98,0.9898989999999999,25.0,33.0,0.9849494999999999,-0.00989899999999988,2
33
- c4,c,tabdiff,TabDiff,0.98,0.9772727272727273,25.0,33.0,0.9786363636363636,0.0027272727272726893,2
34
- c4,c,tabpfgen,TabPFGen,0.98,0.9898989999999999,25.0,33.0,0.9849494999999999,-0.00989899999999988,2
35
- c4,c,tabsyn,TabSyn,0.94,0.9595959696969697,25.0,33.0,0.9497979848484848,-0.01959596969696975,2
36
- c4,c,tvae,TVAE,0.98,0.9747474848484847,25.0,33.0,0.9773737424242424,0.005252515151515258,2
37
- c5,c,real,REAL,1.0,1.0,25.0,33.0,1.0,0.0,2
38
- c5,c,arf,ARF,0.98333332,0.9468113636363636,25.0,33.0,0.9650723418181818,0.03652195636363631,2
39
- c5,c,bayesnet,BayesNet,0.9426666400000001,0.8491566666666667,25.0,33.0,0.8959116533333333,0.09350997333333344,2
40
- c5,c,ctgan,CTGAN,0.94733332,0.905662696969697,25.0,33.0,0.9264980084848485,0.041670623030303,2
41
- c5,c,realtabformer,RealTabFormer,0.99333332,0.9703791212121212,25.0,33.0,0.9818562206060606,0.022954198787878743,2
42
- c5,c,tabbyflow,TabbyFlow,1.0,0.9728584545454545,25.0,33.0,0.9864292272727273,0.0271415454545455,2
43
- c5,c,tabddpm,TabDDPM,0.99,0.9279920606060605,25.0,33.0,0.9589960303030303,0.06200793939393945,2
44
- c5,c,tabdiff,TabDiff,0.95733332,0.8967401515151515,25.0,33.0,0.9270367357575757,0.060593168484848525,2
45
- c5,c,tabpfgen,TabPFGen,0.97511112,0.9651985151515152,25.0,33.0,0.9701548175757576,0.009912604848484774,2
46
- c5,c,tabsyn,TabSyn,0.98333332,0.8913211818181819,25.0,33.0,0.9373272509090909,0.09201213818181808,2
47
- c5,c,tvae,TVAE,0.92,0.8683808181818181,25.0,33.0,0.8941904090909091,0.051619181818181925,2
48
- c6,c,real,REAL,1.0,1.0,21.0,29.0,1.0,0.0,2
49
- c6,c,arf,ARF,0.9551587619047618,0.8950960344827587,21.0,29.0,0.9251273981937602,0.06006272742200314,2
50
- c6,c,bayesnet,BayesNet,0.9551587619047618,0.9421704827586207,21.0,29.0,0.9486646223316912,0.01298827914614109,2
51
- c6,c,ctgan,CTGAN,0.7636165714285715,0.6843782068965517,21.0,29.0,0.7239973891625616,0.07923836453201982,2
52
- c6,c,realtabformer,RealTabFormer,1.0,0.9748263103448276,21.0,29.0,0.9874131551724138,0.025173689655172415,2
53
- c6,c,tabbyflow,TabbyFlow,0.9299620000000001,0.8770257586206897,21.0,29.0,0.9034938793103449,0.05293624137931041,2
54
- c6,c,tabdiff,TabDiff,0.934864,0.8645758965517241,21.0,29.0,0.899719948275862,0.07028810344827596,2
55
- c6,c,tabpfgen,TabPFGen,0.987301619047619,0.9491222068965517,21.0,29.0,0.9682119129720854,0.03817941215106735,2
56
- c6,c,tabsyn,TabSyn,0.9484127142857143,0.9264178620689655,21.0,29.0,0.9374152881773399,0.021994852216748795,2
57
- c6,c,tvae,TVAE,0.8090436666666666,0.7198470689655173,21.0,29.0,0.764445367816092,0.0891965977011493,2
58
- c7,c,real,REAL,1.0,1.0,25.0,33.0,1.0,0.0,2
59
- c7,c,arf,ARF,0.9520000000000001,0.9921593636363636,25.0,33.0,0.9720796818181818,-0.04015936363636352,2
60
- c7,c,bayesnet,BayesNet,1.0,0.9944903636363637,25.0,33.0,0.9972451818181818,0.005509636363636328,2
61
- c7,c,ctgan,CTGAN,0.992,0.9816738787878787,25.0,33.0,0.9868369393939393,0.010326121212121286,2
62
- c7,c,forestdiffusion,ForestDiffusion,0.92842104,0.9746625757575758,25.0,33.0,0.9515418078787878,-0.046241535757575725,2
63
- c7,c,realtabformer,RealTabFormer,1.0,0.9944903636363637,25.0,33.0,0.9972451818181818,0.005509636363636328,2
64
- c7,c,tabbyflow,TabbyFlow,0.932,0.8754578484848484,25.0,33.0,0.9037289242424242,0.05654215151515163,2
65
- c7,c,tabddpm,TabDDPM,1.0,0.9901613636363636,25.0,33.0,0.9950806818181819,0.009838636363636355,2
66
- c7,c,tabdiff,TabDiff,0.94,0.8754578484848484,25.0,33.0,0.9077289242424242,0.06454215151515152,2
67
- c7,c,tabpfgen,TabPFGen,0.946,0.8764038787878787,25.0,33.0,0.9112019393939393,0.06959612121212122,2
68
- c7,c,tabsyn,TabSyn,0.812,0.9032633939393939,25.0,33.0,0.857631696969697,-0.09126339393939387,2
69
- c7,c,tvae,TVAE,0.934,0.9831002424242423,25.0,33.0,0.9585501212121212,-0.04910024242424227,2
70
- c8,c,real,REAL,1.0,1.0,20.0,26.0,1.0,0.0,2
71
- c8,c,arf,ARF,1.0,1.0,20.0,26.0,1.0,0.0,2
72
- c8,c,bayesnet,BayesNet,1.0,1.0,20.0,26.0,1.0,0.0,2
73
- c8,c,ctgan,CTGAN,1.0,1.0,20.0,26.0,1.0,0.0,2
74
- c8,c,forestdiffusion,ForestDiffusion,0.9,0.8846153846153846,20.0,26.0,0.8923076923076922,0.015384615384615441,2
75
- c8,c,realtabformer,RealTabFormer,1.0,1.0,20.0,26.0,1.0,0.0,2
76
- c8,c,tabbyflow,TabbyFlow,0.1,0.08974357692307693,20.0,26.0,0.09487178846153846,0.01025642307692308,2
77
- c8,c,tabddpm,TabDDPM,0.0,0.038461538461538464,20.0,26.0,0.019230769230769232,-0.038461538461538464,2
78
- c8,c,tabdiff,TabDiff,0.1,0.08974357692307693,20.0,26.0,0.09487178846153846,0.01025642307692308,2
79
- c8,c,tabpfgen,TabPFGen,1.0,1.0,20.0,26.0,1.0,0.0,2
80
- c8,c,tabsyn,TabSyn,0.3,0.3076923076923077,20.0,26.0,0.3038461538461539,-0.0076923076923077205,2
81
- c8,c,tvae,TVAE,0.9666667,0.9615385000000001,20.0,26.0,0.9641026,0.005128199999999916,2
82
- c9,c,real,REAL,1.0,1.0,25.0,33.0,1.0,0.0,2
83
- c9,c,arf,ARF,0.50174296,0.6043858787878787,25.0,33.0,0.5530644193939394,-0.10264291878787879,2
84
- c9,c,bayesnet,BayesNet,0.33805436,0.20682351515151515,25.0,33.0,0.27243893757575754,0.13123084484848485,2
85
- c9,c,ctgan,CTGAN,0.32370372000000003,0.1915919696969697,25.0,33.0,0.25764784484848485,0.13211175030303032,2
86
- c9,c,forestdiffusion,ForestDiffusion,0.04847552,0.22305360606060606,25.0,33.0,0.13576456303030304,-0.17457808606060607,2
87
- c9,c,realtabformer,RealTabFormer,0.89128228,0.8984037272727273,25.0,33.0,0.8948430036363637,-0.007121447272727344,2
88
- c9,c,tabbyflow,TabbyFlow,0.61277812,0.7972120909090908,25.0,33.0,0.7049951054545454,-0.18443397090909086,2
89
- c9,c,tabddpm,TabDDPM,0.16464991999999998,0.23359275757575756,25.0,33.0,0.19912133878787877,-0.06894283757575759,2
90
- c9,c,tabdiff,TabDiff,0.62688156,0.8036001515151515,25.0,33.0,0.7152408557575758,-0.17671859151515157,2
91
- c9,c,tabpfgen,TabPFGen,0.47374760000000005,0.5368468484848484,25.0,33.0,0.5052972242424243,-0.06309924848484838,2
92
- c9,c,tabsyn,TabSyn,0.6161316800000001,0.7905405757575757,25.0,33.0,0.703336127878788,-0.17440889575757568,2
93
- c9,c,tvae,TVAE,0.2882162,0.17860581818181817,25.0,33.0,0.23341100909090906,0.1096103818181818,2
94
- c10,c,real,REAL,1.0,1.0,20.0,26.0,1.0,0.0,2
95
- c10,c,arf,ARF,0.0,0.0,20.0,26.0,0.0,0.0,2
96
- c10,c,bayesnet,BayesNet,0.0,0.0,20.0,26.0,0.0,0.0,2
97
- c10,c,ctgan,CTGAN,0.9328571,0.9757325384615385,20.0,26.0,0.9542948192307692,-0.04287543846153852,2
98
- c10,c,forestdiffusion,ForestDiffusion,0.0,0.0,20.0,26.0,0.0,0.0,2
99
- c10,c,realtabformer,RealTabFormer,0.8865584,0.7803147692307693,20.0,26.0,0.8334365846153846,0.10624363076923071,2
100
- c10,c,tabbyflow,TabbyFlow,0.08,0.0,20.0,26.0,0.04,0.08,2
101
- c10,c,tabddpm,TabDDPM,0.0,0.0,20.0,26.0,0.0,0.0,2
102
- c10,c,tabpfgen,TabPFGen,0.0,0.0,20.0,26.0,0.0,0.0,2
103
- c10,c,tabsyn,TabSyn,0.0,0.0,20.0,26.0,0.0,0.0,2
104
- c10,c,tvae,TVAE,0.8954945000000001,0.9002888461538461,20.0,26.0,0.8978916730769231,-0.004794346153845996,2
105
- c11,c,real,REAL,1.0,1.0,25.0,33.0,1.0,0.0,2
106
- c11,c,arf,ARF,0.98666668,0.959596,25.0,33.0,0.97313134,0.027070680000000014,2
107
- c11,c,bayesnet,BayesNet,1.0,0.9898989999999999,25.0,33.0,0.9949494999999999,0.010101000000000138,2
108
- c11,c,ctgan,CTGAN,0.98666668,0.959596,25.0,33.0,0.97313134,0.027070680000000014,2
109
- c11,c,forestdiffusion,ForestDiffusion,0.0,0.0,25.0,33.0,0.0,0.0,2
110
- c11,c,realtabformer,RealTabFormer,1.0,0.996633,25.0,33.0,0.9983165,0.003367000000000009,2
111
- c11,c,tabbyflow,TabbyFlow,0.0,0.0,25.0,33.0,0.0,0.0,2
112
- c11,c,tabddpm,TabDDPM,0.0,0.0,25.0,33.0,0.0,0.0,2
113
- c11,c,tabsyn,TabSyn,0.0,0.0,25.0,33.0,0.0,0.0,2
114
- c11,c,tvae,TVAE,1.0,0.9680134848484849,25.0,33.0,0.9840067424242425,0.03198651515151507,2
115
- c12,c,real,REAL,1.0,1.0,38.0,26.0,1.0,0.0,2
116
- c12,c,arf,ARF,0.9736842105263158,0.9807692307692307,38.0,26.0,0.9772267206477733,-0.007085020242914908,2
117
- c12,c,bayesnet,BayesNet,1.0,0.9807692307692307,38.0,26.0,0.9903846153846154,0.019230769230769273,2
118
- c12,c,ctgan,CTGAN,0.9868421052631579,0.9615384615384616,38.0,26.0,0.9741902834008097,0.02530364372469629,2
119
- c12,c,realtabformer,RealTabFormer,0.9868421052631579,1.0,38.0,26.0,0.993421052631579,-0.013157894736842146,2
120
- c12,c,tabpfgen,TabPFGen,0.9473684210526315,1.0,38.0,26.0,0.9736842105263157,-0.052631578947368474,2
121
- c12,c,tvae,TVAE,0.5263157894736842,0.4807692307692308,38.0,26.0,0.5035425101214575,0.0455465587044534,2
122
- c14,c,real,REAL,1.0,1.0,34.0,26.0,1.0,0.0,2
123
- c14,c,arf,ARF,0.6764705882352942,0.38159342307692307,34.0,26.0,0.5290320056561086,0.2948771651583711,2
124
- c14,c,bayesnet,BayesNet,0.8196078529411764,0.8096153846153846,34.0,26.0,0.8146116187782806,0.009992468325791815,2
125
- c14,c,ctgan,CTGAN,0.8245797941176471,0.7751028461538462,34.0,26.0,0.7998413201357466,0.04947694796380098,2
126
- c14,c,realtabformer,RealTabFormer,0.9960784411764706,0.9477689230769231,34.0,26.0,0.9719236821266968,0.04830951809954753,2
127
- c14,c,tabsyn,TabSyn,0.0,0.15384615384615385,34.0,26.0,0.07692307692307693,-0.15384615384615385,2
128
- c14,c,tvae,TVAE,0.40467038235294117,0.5015901153846154,34.0,26.0,0.4531302488687783,-0.09691973303167423,2
129
- c15,c,real,REAL,1.0,1.0,11.0,26.0,1.0,0.0,2
130
- c15,c,arf,ARF,0.8520164545454545,0.5196885769230769,11.0,26.0,0.6858525157342656,0.3323278776223776,2
131
- c15,c,bayesnet,BayesNet,0.6939394545454545,0.4258929230769231,11.0,26.0,0.5599161888111888,0.26804653146853136,2
132
- c15,c,realtabformer,RealTabFormer,1.0,0.9038461538461539,11.0,26.0,0.9519230769230769,0.09615384615384615,2
133
- c15,c,tabsyn,TabSyn,0.033834636363636365,0.04940411538461539,11.0,26.0,0.041619375874125876,-0.015569479020979021,2
134
- c15,c,tvae,TVAE,0.4602271818181818,0.18766215384615384,11.0,26.0,0.3239446678321678,0.272565027972028,2
135
- c16,c,real,REAL,1.0,1.0,52.0,26.0,1.0,0.0,2
136
- c16,c,arf,ARF,0.7769366153846153,0.8004807692307693,52.0,26.0,0.7887086923076922,-0.023544153846153937,2
137
- c16,c,bayesnet,BayesNet,0.5665299038461539,0.5451717307692308,52.0,26.0,0.5558508173076924,0.021358173076923115,2
138
- c16,c,ctgan,CTGAN,0.6600592115384616,0.5980769615384616,52.0,26.0,0.6290680865384616,0.061982250000000016,2
139
- c16,c,realtabformer,RealTabFormer,0.7154773846153847,0.7091422692307692,52.0,26.0,0.712309826923077,0.006335115384615508,2
140
- c16,c,tabsyn,TabSyn,0.0,0.0,52.0,26.0,0.0,0.0,2
141
- c16,c,tvae,TVAE,0.33442990384615384,0.3364434230769231,52.0,26.0,0.33543666346153844,-0.002013519230769256,2
142
- c17,c,real,REAL,1.0,1.0,18.0,29.0,1.0,0.0,2
143
- c17,c,arf,ARF,0.7121994444444444,0.6511876551724138,18.0,29.0,0.6816935498084291,0.06101178927203055,2
144
- c17,c,bayesnet,BayesNet,0.7242446666666668,0.6538870344827586,18.0,29.0,0.6890658505747127,0.07035763218390811,2
145
- c17,c,ctgan,CTGAN,0.8154513333333333,0.8423155862068965,18.0,29.0,0.8288834597701149,-0.0268642528735632,2
146
- c17,c,realtabformer,RealTabFormer,0.7013092777777777,0.6873283793103449,18.0,29.0,0.6943188285440614,0.01398089846743289,2
147
- c17,c,tabpfgen,TabPFGen,0.68293,0.6447729999999999,18.0,29.0,0.6638515,0.03815700000000011,2
148
- c17,c,tabsyn,TabSyn,0.0,0.0,18.0,29.0,0.0,0.0,2
149
- c17,c,tvae,TVAE,0.7535401111111111,0.7583264137931034,18.0,29.0,0.7559332624521072,-0.004786302681992316,2
150
- c18,c,real,REAL,1.0,1.0,40.0,23.0,1.0,0.0,2
151
- c18,c,arf,ARF,0.366703675,0.562093,40.0,23.0,0.4643983375,-0.19538932499999995,2
152
- c18,c,bayesnet,BayesNet,0.310141475,0.49061073913043485,40.0,23.0,0.4003761070652174,-0.18046926413043485,2
153
- c18,c,realtabformer,RealTabFormer,0.566635675,0.7345330869565218,40.0,23.0,0.6505843809782609,-0.16789741195652175,2
154
- c18,c,tabsyn,TabSyn,0.03840495,0.049858695652173914,40.0,23.0,0.04413182282608696,-0.011453745652173913,2
155
- c19,c,real,REAL,1.0,1.0,77.0,7.0,1.0,0.0,2
156
- c19,c,arf,ARF,0.9993164675324675,1.0,77.0,7.0,0.9996582337662338,-0.0006835324675324994,2
157
- c19,c,bayesnet,BayesNet,0.5995671038961039,0.7142857142857143,77.0,7.0,0.656926409090909,-0.1147186103896104,2
158
- c19,c,ctgan,CTGAN,0.5981795974025974,0.7478991428571428,77.0,7.0,0.67303937012987,-0.14971954545454536,2
159
- c19,c,realtabformer,RealTabFormer,0.5033480649350649,0.5357142857142857,77.0,7.0,0.5195311753246753,-0.0323662207792208,2
160
- c19,c,tabpfgen,TabPFGen,0.0,0.0,77.0,7.0,0.0,0.0,2
161
- c19,c,tabsyn,TabSyn,0.0,0.0,77.0,7.0,0.0,0.0,2
162
- c19,c,tvae,TVAE,0.6031251168831169,0.7460317142857144,77.0,7.0,0.6745784155844157,-0.14290659740259748,2
163
- c20,c,real,REAL,1.0,1.0,33.0,33.0,1.0,0.0,2
164
- c20,c,arf,ARF,0.06060606060606061,0.15151515151515152,33.0,33.0,0.10606060606060606,-0.09090909090909091,2
165
- c20,c,bayesnet,BayesNet,0.7283950606060606,0.9329362424242423,33.0,33.0,0.8306656515151515,-0.2045411818181817,2
166
- c20,c,ctgan,CTGAN,0.7462071818181818,0.8698105151515152,33.0,33.0,0.8080088484848484,-0.1236033333333334,2
167
- c20,c,forestdiffusion,ForestDiffusion,0.0,0.0,33.0,33.0,0.0,0.0,2
168
- c20,c,realtabformer,RealTabFormer,0.7535353636363636,0.9308999090909091,33.0,33.0,0.8422176363636364,-0.1773645454545455,2
169
- c20,c,tabbyflow,TabbyFlow,0.0,0.0,33.0,33.0,0.0,0.0,2
170
- c20,c,tabddpm,TabDDPM,0.0,0.0,33.0,33.0,0.0,0.0,2
171
- c20,c,tabpfgen,TabPFGen,0.06060606060606061,0.15151515151515152,33.0,33.0,0.10606060606060606,-0.09090909090909091,2
172
- c20,c,tabsyn,TabSyn,0.0,0.0,33.0,33.0,0.0,0.0,2
173
- c20,c,tvae,TVAE,0.7233806060606061,0.8810461515151515,33.0,33.0,0.8022133787878788,-0.15766554545454547,2
174
- m1,m,real,REAL,1.0,1.0,34.0,8.0,1.0,0.0,2
175
- m1,m,arf,ARF,0.9813719117647058,1.0,34.0,8.0,0.9906859558823529,-0.01862808823529416,2
176
- m1,m,bayesnet,BayesNet,0.9800419705882353,1.0,34.0,8.0,0.9900209852941176,-0.01995802941176472,2
177
- m1,m,ctgan,CTGAN,0.965393794117647,1.0,34.0,8.0,0.9826968970588235,-0.03460620588235297,2
178
- m1,m,realtabformer,RealTabFormer,0.7703004705882353,0.95833325,34.0,8.0,0.8643168602941176,-0.18803277941176477,2
179
- m1,m,tabbyflow,TabbyFlow,0.9455695000000001,0.979166625,34.0,8.0,0.9623680625,-0.033597124999999894,2
180
- m1,m,tabddpm,TabDDPM,0.7261974705882352,1.0,34.0,8.0,0.8630987352941176,-0.27380252941176475,2
181
- m1,m,tabdiff,TabDiff,0.9882839411764704,1.0,34.0,8.0,0.9941419705882353,-0.011716058823529552,2
182
- m1,m,tabpfgen,TabPFGen,0.8950504411764706,1.0,34.0,8.0,0.9475252205882353,-0.10494955882352941,2
183
- m1,m,tabsyn,TabSyn,0.8673568235294118,1.0,34.0,8.0,0.9336784117647059,-0.1326431764705882,2
184
- m1,m,tvae,TVAE,0.5142900882352941,0.71875,34.0,8.0,0.616520044117647,-0.2044599117647059,2
185
- m2,m,real,REAL,1.0,1.0,20.0,26.0,1.0,0.0,2
186
- m2,m,arf,ARF,0.9571429,0.8034663846153846,20.0,26.0,0.8803046423076923,0.15367651538461546,2
187
- m2,m,bayesnet,BayesNet,0.9,0.8803418846153845,20.0,26.0,0.8901709423076922,0.019658115384615482,2
188
- m2,m,ctgan,CTGAN,0.9,0.8226495769230768,20.0,26.0,0.8613247884615385,0.07735042307692319,2
189
- m2,m,realtabformer,RealTabFormer,0.9709091000000001,0.9146253461538462,20.0,26.0,0.9427672230769231,0.05628375384615392,2
190
- m2,m,tabddpm,TabDDPM,0.22111109999999998,0.6136363461538461,20.0,26.0,0.41737372307692305,-0.3925252461538461,2
191
- m2,m,tabpfgen,TabPFGen,0.9000456,0.9188051153846154,20.0,26.0,0.9094253576923077,-0.0187595153846154,2
192
- m2,m,tabsyn,TabSyn,0.7588889,0.8040627307692307,20.0,26.0,0.7814758153846153,-0.04517383076923076,2
193
- m2,m,tvae,TVAE,0.9,0.8034188076923077,20.0,26.0,0.8517094038461539,0.09658119230769235,2
194
- m4,m,real,REAL,1.0,1.0,45.0,7.0,1.0,0.0,2
195
- m4,m,arf,ARF,0.6833333333333333,0.7142857142857143,45.0,7.0,0.6988095238095238,-0.030952380952380953,2
196
- m4,m,bayesnet,BayesNet,0.6851851777777778,0.7142857142857143,45.0,7.0,0.699735446031746,-0.029100536507936536,2
197
- m4,m,ctgan,CTGAN,0.6740741777777778,0.7619048571428572,45.0,7.0,0.7179895174603175,-0.08783067936507938,2
198
- m4,m,forestdiffusion,ForestDiffusion,0.9259259111111111,1.0,45.0,7.0,0.9629629555555556,-0.07407408888888889,2
199
- m4,m,realtabformer,RealTabFormer,0.9907407333333335,1.0,45.0,7.0,0.9953703666666667,-0.009259266666666544,2
200
- m4,m,tabbyflow,TabbyFlow,0.9814814666666667,1.0,45.0,7.0,0.9907407333333333,-0.01851853333333331,2
201
- m4,m,tabddpm,TabDDPM,0.0,0.0,45.0,7.0,0.0,0.0,2
202
- m4,m,tabdiff,TabDiff,1.0,1.0,45.0,7.0,1.0,0.0,2
203
- m4,m,tabpfgen,TabPFGen,0.6787878888888889,0.7142857142857143,45.0,7.0,0.6965368015873016,-0.035497825396825444,2
204
- m4,m,tabsyn,TabSyn,1.0,1.0,45.0,7.0,1.0,0.0,2
205
- m4,m,tvae,TVAE,0.6259260222222223,0.7619048571428572,45.0,7.0,0.6939154396825398,-0.1359788349206349,2
206
- m5,m,real,REAL,1.0,1.0,20.0,26.0,1.0,0.0,2
207
- m5,m,arf,ARF,0.8126632,0.9333441538461538,20.0,26.0,0.8730036769230769,-0.12068095384615374,2
208
- m5,m,bayesnet,BayesNet,0.5585621,0.8964237692307692,20.0,26.0,0.7274929346153846,-0.3378616692307692,2
209
- m5,m,ctgan,CTGAN,0.2583053,0.5632303461538462,20.0,26.0,0.41076782307692306,-0.30492504615384614,2
210
- m5,m,forestdiffusion,ForestDiffusion,0.6322618999999999,0.38553203846153844,20.0,26.0,0.5088969692307692,0.2467298615384615,2
211
- m5,m,realtabformer,RealTabFormer,0.9785714000000001,0.9461023846153847,20.0,26.0,0.9623368923076924,0.03246901538461544,2
212
- m5,m,tabbyflow,TabbyFlow,0.8725596,0.8892153076923077,20.0,26.0,0.8808874538461539,-0.01665570769230773,2
213
- m5,m,tabddpm,TabDDPM,0.1115132,0.009971500000000001,20.0,26.0,0.06074235,0.10154170000000001,2
214
- m5,m,tabdiff,TabDiff,0.7888889,0.8800306153846154,20.0,26.0,0.8344597576923076,-0.09114171538461535,2
215
- m5,m,tabpfgen,TabPFGen,0.6799999999999999,0.9467158076923077,20.0,26.0,0.8133579038461538,-0.26671580769230774,2
216
- m5,m,tabsyn,TabSyn,0.9097339,0.9153369615384614,20.0,26.0,0.9125354307692307,-0.005603061538461462,2
217
- m5,m,tvae,TVAE,0.222227,0.4707727692307693,20.0,26.0,0.3464998846153846,-0.24854576923076926,2
218
- m6,m,real,REAL,1.0,1.0,35.0,26.0,1.0,0.0,2
219
- m6,m,arf,ARF,0.7211579142857143,0.5405882307692308,35.0,26.0,0.6308730725274725,0.1805696835164835,2
220
- m6,m,bayesnet,BayesNet,0.6594251999999999,0.5486425384615384,35.0,26.0,0.6040338692307692,0.1107826615384615,2
221
- m6,m,ctgan,CTGAN,0.5752261428571429,0.4371206538461539,35.0,26.0,0.5061733983516484,0.138105489010989,2
222
- m6,m,forestdiffusion,ForestDiffusion,0.5781548857142856,0.4189211538461538,35.0,26.0,0.4985380197802197,0.15923373186813183,2
223
- m6,m,realtabformer,RealTabFormer,0.6691195714285714,0.5419808461538461,35.0,26.0,0.6055502087912088,0.12713872527472525,2
224
- m6,m,tabbyflow,TabbyFlow,0.5805850285714286,0.4944518846153846,35.0,26.0,0.5375184565934066,0.08613314395604399,2
225
- m6,m,tabddpm,TabDDPM,0.12040817142857141,0.14102565384615384,35.0,26.0,0.13071691263736263,-0.020617482417582433,2
226
- m6,m,tabdiff,TabDiff,0.5975843428571428,0.5136163461538461,35.0,26.0,0.5556003445054944,0.08396799670329669,2
227
- m6,m,tabpfgen,TabPFGen,0.6144663714285714,0.46563611538461536,35.0,26.0,0.5400512434065934,0.14883025604395606,2
228
- m6,m,tabsyn,TabSyn,0.6100875714285715,0.5054752307692307,35.0,26.0,0.5577814010989011,0.10461234065934077,2
229
- m6,m,tvae,TVAE,0.3547256285714286,0.33118734615384615,35.0,26.0,0.3429564873626374,0.023538282417582435,2
230
- m7,m,real,REAL,1.0,1.0,15.0,26.0,1.0,0.0,2
231
- m7,m,arf,ARF,0.4222222,1.0,15.0,26.0,0.7111111,-0.5777778,2
232
- m7,m,bayesnet,BayesNet,0.4095238,1.0,15.0,26.0,0.7047619,-0.5904762,2
233
- m7,m,ctgan,CTGAN,0.40555553333333333,0.8769230769230769,15.0,26.0,0.6412393051282052,-0.4713675435897436,2
234
- m7,m,forestdiffusion,ForestDiffusion,0.10666666666666667,0.4140321153846154,15.0,26.0,0.26034939102564103,-0.3073654487179487,2
235
- m7,m,realtabformer,RealTabFormer,0.4666666666666667,1.0,15.0,26.0,0.7333333333333334,-0.5333333333333333,2
236
- m7,m,tabbyflow,TabbyFlow,0.4095238,1.0,15.0,26.0,0.7047619,-0.5904762,2
237
- m7,m,tabddpm,TabDDPM,0.07619046666666666,0.5384615384615384,15.0,26.0,0.30732600256410253,-0.46227107179487176,2
238
- m7,m,tabdiff,TabDiff,0.4222222,1.0,15.0,26.0,0.7111111,-0.5777778,2
239
- m7,m,tabpfgen,TabPFGen,0.4066666666666666,0.8653846153846154,15.0,26.0,0.6360256410256411,-0.4587179487179488,2
240
- m7,m,tabsyn,TabSyn,0.4095238,1.0,15.0,26.0,0.7047619,-0.5904762,2
241
- m7,m,tvae,TVAE,0.3305555333333333,0.7519230769230769,15.0,26.0,0.5412393051282052,-0.4213675435897436,2
242
- m8,m,real,REAL,1.0,1.0,15.0,26.0,1.0,0.0,2
243
- m8,m,arf,ARF,0.9387655333333333,0.9672501923076923,15.0,26.0,0.9530078628205128,-0.028484658974358923,2
244
- m8,m,bayesnet,BayesNet,0.8914269333333333,0.9053254615384615,15.0,26.0,0.8983761974358975,-0.013898528205128158,2
245
- m8,m,ctgan,CTGAN,0.6199100000000001,0.7799674615384615,15.0,26.0,0.6999387307692309,-0.16005746153846145,2
246
- m8,m,forestdiffusion,ForestDiffusion,0.8126332666666667,0.8941661538461538,15.0,26.0,0.8533997102564103,-0.08153288717948715,2
247
- m8,m,realtabformer,RealTabFormer,0.9531194,0.9748088461538462,15.0,26.0,0.9639641230769231,-0.02168944615384627,2
248
- m8,m,tabddpm,TabDDPM,0.8556626666666667,0.9680933461538461,15.0,26.0,0.9118780064102564,-0.11243067948717944,2
249
- m8,m,tabdiff,TabDiff,0.9337366,0.9759766923076924,15.0,26.0,0.9548566461538461,-0.04224009230769232,2
250
- m8,m,tabpfgen,TabPFGen,0.9737028,0.97909,15.0,26.0,0.9763964,-0.005387200000000036,2
251
- m8,m,tabsyn,TabSyn,0.9460042000000001,0.9807920384615384,15.0,26.0,0.9633981192307692,-0.03478783846153832,2
252
- m8,m,tvae,TVAE,0.423231,0.738198153846154,15.0,26.0,0.580714576923077,-0.3149671538461539,2
253
- m9,m,real,REAL,1.0,1.0,32.0,26.0,1.0,0.0,2
254
- m9,m,arf,ARF,0.6874353125,0.8588241153846153,32.0,26.0,0.7731297139423077,-0.17138880288461533,2
255
- m9,m,bayesnet,BayesNet,0.67620578125,0.864743576923077,32.0,26.0,0.7704746790865384,-0.18853779567307705,2
256
- m9,m,ctgan,CTGAN,0.670513875,0.8358974230769232,32.0,26.0,0.7532056490384615,-0.16538354807692313,2
257
- m9,m,forestdiffusion,ForestDiffusion,0.0,0.0,32.0,26.0,0.0,0.0,2
258
- m9,m,realtabformer,RealTabFormer,0.83374540625,0.9453455384615383,32.0,26.0,0.8895454723557692,-0.1116001322115383,2
259
- m9,m,tabddpm,TabDDPM,0.665195625,0.8791208846153846,32.0,26.0,0.7721582548076923,-0.21392525961538467,2
260
- m9,m,tabpfgen,TabPFGen,0.58778728125,0.6282117692307693,32.0,26.0,0.6079995252403847,-0.04042448798076925,2
261
- m9,m,tabsyn,TabSyn,0.746633125,0.9084689230769231,32.0,26.0,0.8275510240384616,-0.16183579807692305,2
262
- m9,m,tvae,TVAE,0.3957408125,0.5842517307692308,32.0,26.0,0.48999627163461534,-0.18851091826923078,2
263
- m10,m,real,REAL,1.0,1.0,35.0,26.0,1.0,0.0,2
264
- m10,m,arf,ARF,0.5362522000000001,0.7783,35.0,26.0,0.6572761,-0.24204779999999992,2
265
- m10,m,bayesnet,BayesNet,0.9197526285714286,0.8836916153846155,35.0,26.0,0.901722121978022,0.036061013186813096,2
266
- m10,m,ctgan,CTGAN,0.5319793428571429,0.7549257692307693,35.0,26.0,0.6434525560439561,-0.22294642637362638,2
267
- m10,m,forestdiffusion,ForestDiffusion,0.24229968571428573,0.15709434615384615,35.0,26.0,0.19969701593406594,0.08520533956043957,2
268
- m10,m,realtabformer,RealTabFormer,0.9704626571428571,0.9817177307692309,35.0,26.0,0.976090193956044,-0.01125507362637379,2
269
- m10,m,tabbyflow,TabbyFlow,0.7131164571428571,0.8732985384615385,35.0,26.0,0.7932074978021978,-0.1601820813186814,2
270
- m10,m,tabddpm,TabDDPM,0.008556114285714286,0.015362807692307693,35.0,26.0,0.01195946098901099,-0.006806693406593407,2
271
- m10,m,tabpfgen,TabPFGen,0.5402908571428572,0.7637362692307692,35.0,26.0,0.6520135631868131,-0.22344541208791202,2
272
- m10,m,tabsyn,TabSyn,0.7377318285714285,0.8728783076923077,35.0,26.0,0.8053050681318681,-0.13514647912087918,2
273
- m10,m,tvae,TVAE,0.5293407142857143,0.7615384615384616,35.0,26.0,0.645439587912088,-0.23219774725274733,2
274
- m11,m,real,REAL,1.0,1.0,42.0,26.0,1.0,0.0,2
275
- m11,m,arf,ARF,0.7613211904761905,0.693406576923077,42.0,26.0,0.7273638836996337,0.06791461355311357,2
276
- m11,m,bayesnet,BayesNet,0.7432409047619049,0.694570153846154,42.0,26.0,0.7189055293040294,0.048670750915750904,2
277
- m11,m,ctgan,CTGAN,0.755135380952381,0.6986538461538461,42.0,26.0,0.7268946135531136,0.056481534798534905,2
278
- m11,m,forestdiffusion,ForestDiffusion,0.5588115714285715,0.46153846153846156,42.0,26.0,0.5101750164835166,0.09727310989010995,2
279
- m11,m,realtabformer,RealTabFormer,0.9515036428571428,0.9251559230769231,42.0,26.0,0.938329782967033,0.02634771978021977,2
280
- m11,m,tabbyflow,TabbyFlow,0.35693309523809524,0.30779026923076924,42.0,26.0,0.33236168223443224,0.049142826007326,2
281
- m11,m,tabddpm,TabDDPM,0.44581454761904765,0.34965034615384616,42.0,26.0,0.39773244688644693,0.0961642014652015,2
282
- m11,m,tabsyn,TabSyn,0.35693309523809524,0.30726692307692305,42.0,26.0,0.33210000915750915,0.049666172161172195,2
283
- m11,m,tvae,TVAE,0.6804946190476191,0.582750576923077,42.0,26.0,0.631622597985348,0.09774404212454213,2
284
- m12,m,real,REAL,1.0,1.0,42.0,8.0,1.0,0.0,2
285
- m12,m,arf,ARF,0.848567380952381,0.878185625,42.0,8.0,0.8633765029761905,-0.029618244047618925,2
286
- m12,m,bayesnet,BayesNet,0.7656653333333333,0.964197625,42.0,8.0,0.8649314791666667,-0.19853229166666664,2
287
- m12,m,ctgan,CTGAN,0.35691138095238095,0.5351241250000001,42.0,8.0,0.4460177529761905,-0.1782127440476191,2
288
- m12,m,realtabformer,RealTabFormer,0.8570308333333333,0.84827025,42.0,8.0,0.8526505416666667,0.008760583333333294,2
289
- m12,m,tabbyflow,TabbyFlow,0.7574845238095238,0.936111125,42.0,8.0,0.8467978244047619,-0.17862660119047624,2
290
- m12,m,tabsyn,TabSyn,0.7361557857142857,0.937323625,42.0,8.0,0.8367397053571428,-0.20116783928571425,2
291
- m12,m,tvae,TVAE,0.32031314285714285,0.43196225,42.0,8.0,0.3761376964285714,-0.11164910714285714,2
292
- n1,n,real,REAL,1.0,1.0,16.0,23.0,1.0,0.0,2
293
- n1,n,arf,ARF,1.0,1.0,16.0,23.0,1.0,0.0,2
294
- n1,n,bayesnet,BayesNet,1.0,1.0,16.0,23.0,1.0,0.0,2
295
- n1,n,ctgan,CTGAN,1.0,1.0,16.0,23.0,1.0,0.0,2
296
- n1,n,forestdiffusion,ForestDiffusion,0.0,0.0,16.0,23.0,0.0,0.0,2
297
- n1,n,realtabformer,RealTabFormer,1.0,1.0,16.0,23.0,1.0,0.0,2
298
- n1,n,tabbyflow,TabbyFlow,1.0,1.0,16.0,23.0,1.0,0.0,2
299
- n1,n,tabddpm,TabDDPM,0.0,0.0,16.0,23.0,0.0,0.0,2
300
- n1,n,tabpfgen,TabPFGen,1.0,1.0,16.0,23.0,1.0,0.0,2
301
- n1,n,tabsyn,TabSyn,1.0,1.0,16.0,23.0,1.0,0.0,2
302
- n1,n,tvae,TVAE,1.0,1.0,16.0,23.0,1.0,0.0,2
303
- n2,n,real,REAL,1.0,,38.0,,1.0,,1
304
- n2,n,arf,ARF,0.5302675789473684,,38.0,,0.5302675789473684,,1
305
- n2,n,bayesnet,BayesNet,1.0,,38.0,,1.0,,1
306
- n2,n,ctgan,CTGAN,0.0,,38.0,,0.0,,1
307
- n2,n,forestdiffusion,ForestDiffusion,0.0,,38.0,,0.0,,1
308
- n2,n,realtabformer,RealTabFormer,1.0,,38.0,,1.0,,1
309
- n2,n,tabbyflow,TabbyFlow,0.0,,38.0,,0.0,,1
310
- n2,n,tabddpm,TabDDPM,0.0,,38.0,,0.0,,1
311
- n2,n,tabdiff,TabDiff,0.0,,38.0,,0.0,,1
312
- n2,n,tabpfgen,TabPFGen,0.0,,38.0,,0.0,,1
313
- n2,n,tabsyn,TabSyn,0.6250044210526317,,38.0,,0.6250044210526317,,1
314
- n2,n,tvae,TVAE,0.0,,38.0,,0.0,,1
315
- n3,n,real,REAL,1.0,1.0,16.0,23.0,1.0,0.0,2
316
- n3,n,arf,ARF,0.0028125,0.019541304347826086,16.0,23.0,0.011176902173913043,-0.016728804347826087,2
317
- n3,n,bayesnet,BayesNet,0.0,0.0,16.0,23.0,0.0,0.0,2
318
- n3,n,ctgan,CTGAN,0.03571425,0.03933747826086957,16.0,23.0,0.03752586413043479,-0.003623228260869568,2
319
- n3,n,forestdiffusion,ForestDiffusion,0.10714275,0.10455478260869565,16.0,23.0,0.10584876630434782,0.0025879673913043466,2
320
- n3,n,realtabformer,RealTabFormer,0.859356625,0.8085836956521739,16.0,23.0,0.833970160326087,0.05077292934782607,2
321
- n3,n,tabbyflow,TabbyFlow,0.11980768750000001,0.41326739130434786,16.0,23.0,0.26653753940217395,-0.2934597038043478,2
322
- n3,n,tabddpm,TabDDPM,0.001771125,0.02156930434782609,16.0,23.0,0.011670214673913043,-0.01979817934782609,2
323
- n3,n,tabdiff,TabDiff,0.14626350000000002,0.43015486956521737,16.0,23.0,0.2882091847826087,-0.2838913695652173,2
324
- n3,n,tabpfgen,TabPFGen,0.0751105,0.08118130434782608,16.0,23.0,0.07814590217391304,-0.0060708043478260865,2
325
- n3,n,tabsyn,TabSyn,0.0470970625,0.355893,16.0,23.0,0.20149503125,-0.3087959375,2
326
- n3,n,tvae,TVAE,0.03571425,0.03209108695652174,16.0,23.0,0.03390266847826087,0.0036231630434782613,2
327
- n4,n,real,REAL,1.0,1.0,57.0,8.0,1.0,0.0,2
328
- n4,n,arf,ARF,0.21905545614035085,0.250714625,57.0,8.0,0.23488504057017545,-0.03165916885964917,2
329
- n4,n,bayesnet,BayesNet,0.14035087719298245,0.25,57.0,8.0,0.19517543859649122,-0.10964912280701755,2
330
- n4,n,ctgan,CTGAN,0.0456140350877193,0.125,57.0,8.0,0.08530701754385965,-0.0793859649122807,2
331
- n4,n,realtabformer,RealTabFormer,0.5597201754385965,0.587362375,57.0,8.0,0.5735412752192983,-0.027642199561403458,2
332
- n4,n,tabbyflow,TabbyFlow,0.22598056140350875,0.272304,57.0,8.0,0.24914228070175437,-0.04632343859649124,2
333
- n4,n,tabddpm,TabDDPM,0.04813317543859649,0.0,57.0,8.0,0.024066587719298246,0.04813317543859649,2
334
- n4,n,tabpfgen,TabPFGen,0.14035087719298245,0.25,57.0,8.0,0.19517543859649122,-0.10964912280701755,2
335
- n4,n,tabsyn,TabSyn,0.22490763157894736,0.254085625,57.0,8.0,0.23949662828947366,-0.029177993421052623,2
336
- n4,n,tvae,TVAE,0.049778526315789474,0.125318875,57.0,8.0,0.08754870065789473,-0.07554034868421053,2
337
- n5,n,real,REAL,1.0,1.0,57.0,8.0,1.0,0.0,2
338
- n5,n,arf,ARF,0.44327991228070174,0.50322375,57.0,8.0,0.47325183114035085,-0.05994383771929823,2
339
- n5,n,bayesnet,BayesNet,0.26562019298245615,0.50000725,57.0,8.0,0.38281372149122805,-0.23438705701754387,2
340
- n5,n,ctgan,CTGAN,0.23357850877192982,0.443796875,57.0,8.0,0.3386876918859649,-0.21021836622807016,2
341
- n5,n,forestdiffusion,ForestDiffusion,0.007590877192982457,0.0,57.0,8.0,0.0037954385964912283,0.007590877192982457,2
342
- n5,n,realtabformer,RealTabFormer,0.36396678947368416,0.5143575,57.0,8.0,0.4391621447368421,-0.15039071052631586,2
343
- n5,n,tabbyflow,TabbyFlow,0.32481292982456145,0.484292375,57.0,8.0,0.4045526524122807,-0.15947944517543855,2
344
- n5,n,tabddpm,TabDDPM,0.013543157894736842,0.001894,57.0,8.0,0.007718578947368421,0.011649157894736842,2
345
- n5,n,tabpfgen,TabPFGen,0.3262389122807018,0.497409375,57.0,8.0,0.4118241436403509,-0.1711704627192982,2
346
- n5,n,tabsyn,TabSyn,0.09264692982456141,0.001846375,57.0,8.0,0.0472466524122807,0.09080055482456141,2
347
- n5,n,tvae,TVAE,0.2347021403508772,0.42593975,57.0,8.0,0.3303209451754386,-0.19123760964912281,2
348
- n6,n,real,REAL,1.0,1.0,38.0,7.0,1.0,0.0,2
349
- n6,n,arf,ARF,1.0,1.0,38.0,7.0,1.0,0.0,2
350
- n6,n,bayesnet,BayesNet,1.0,1.0,38.0,7.0,1.0,0.0,2
351
- n6,n,ctgan,CTGAN,1.0,1.0,38.0,7.0,1.0,0.0,2
352
- n6,n,forestdiffusion,ForestDiffusion,0.0,0.0,38.0,7.0,0.0,0.0,2
353
- n6,n,realtabformer,RealTabFormer,1.0,1.0,38.0,7.0,1.0,0.0,2
354
- n6,n,tabbyflow,TabbyFlow,1.0,1.0,38.0,7.0,1.0,0.0,2
355
- n6,n,tabddpm,TabDDPM,0.0,0.0,38.0,7.0,0.0,0.0,2
356
- n6,n,tabdiff,TabDiff,1.0,1.0,38.0,7.0,1.0,0.0,2
357
- n6,n,tabpfgen,TabPFGen,1.0,1.0,38.0,7.0,1.0,0.0,2
358
- n6,n,tabsyn,TabSyn,0.0,0.0,38.0,7.0,0.0,0.0,2
359
- n6,n,tvae,TVAE,1.0,1.0,38.0,7.0,1.0,0.0,2
360
- n7,n,real,REAL,1.0,1.0,46.0,23.0,1.0,0.0,2
361
- n7,n,arf,ARF,0.9666666739130435,0.9049689565217391,46.0,23.0,0.9358178152173913,0.06169771739130436,2
362
- n7,n,bayesnet,BayesNet,0.9882677826086956,0.9695652173913044,46.0,23.0,0.9789165,0.01870256521739122,2
363
- n7,n,ctgan,CTGAN,0.9576086956521739,0.907608695652174,46.0,23.0,0.932608695652174,0.04999999999999993,2
364
- n7,n,forestdiffusion,ForestDiffusion,0.0,0.0,46.0,23.0,0.0,0.0,2
365
- n7,n,realtabformer,RealTabFormer,0.981461347826087,0.9713768260869565,46.0,23.0,0.9764190869565217,0.010084521739130436,2
366
- n7,n,tabbyflow,TabbyFlow,0.9793478260869565,0.9527433043478261,46.0,23.0,0.9660455652173913,0.026604521739130416,2
367
- n7,n,tabddpm,TabDDPM,0.859843,0.81294,46.0,23.0,0.8363915,0.04690300000000003,2
368
- n7,n,tabpfgen,TabPFGen,0.9882246304347827,0.991304347826087,46.0,23.0,0.9897644891304349,-0.003079717391304304,2
369
- n7,n,tabsyn,TabSyn,0.9794686086956522,0.9427536521739129,46.0,23.0,0.9611111304347826,0.036714956521739284,2
370
- n7,n,tvae,TVAE,0.9695048478260869,0.9460145217391305,46.0,23.0,0.9577596847826086,0.023490326086956448,2
371
- n8,n,real,REAL,1.0,1.0,42.0,26.0,1.0,0.0,2
372
- n8,n,arf,ARF,0.11659664285714287,0.0128205,42.0,26.0,0.06470857142857143,0.10377614285714287,2
373
- n8,n,bayesnet,BayesNet,0.01950111904761905,0.3557692307692308,42.0,26.0,0.1876351749084249,-0.33626811172161175,2
374
- n8,n,ctgan,CTGAN,0.15128954761904762,0.41025630769230764,42.0,26.0,0.28077292765567763,-0.25896676007326,2
375
- n8,n,realtabformer,RealTabFormer,0.095238,0.45221403846153846,42.0,26.0,0.2737260192307692,-0.35697603846153847,2
376
- n8,n,tabbyflow,TabbyFlow,0.12301576190476189,0.43158815384615384,42.0,26.0,0.27730195787545786,-0.30857239194139197,2
377
- n8,n,tabsyn,TabSyn,0.1438745238095238,0.49734146153846154,42.0,26.0,0.32060799267399265,-0.3534669377289377,2
378
- n8,n,tvae,TVAE,0.0,0.36594203846153844,42.0,26.0,0.18297101923076922,-0.36594203846153844,2
379
- n9,n,real,REAL,1.0,1.0,42.0,26.0,1.0,0.0,2
380
- n9,n,arf,ARF,0.7322930714285715,0.7457716538461538,42.0,26.0,0.7390323626373627,-0.013478582417582374,2
381
- n9,n,bayesnet,BayesNet,0.7459832619047619,0.7195981153846154,42.0,26.0,0.7327906886446887,0.026385146520146563,2
382
- n9,n,ctgan,CTGAN,0.6203777857142857,0.5612496538461539,42.0,26.0,0.5908137197802198,0.05912813186813182,2
383
- n9,n,forestdiffusion,ForestDiffusion,0.001605261904761905,0.0,42.0,26.0,0.0008026309523809525,0.001605261904761905,2
384
- n9,n,realtabformer,RealTabFormer,0.8524253333333334,0.8297140769230769,42.0,26.0,0.8410697051282051,0.02271125641025651,2
385
- n9,n,tabbyflow,TabbyFlow,0.7090654047619047,0.7010060384615385,42.0,26.0,0.7050357216117216,0.008059366300366189,2
386
- n9,n,tabddpm,TabDDPM,0.7505624285714285,0.7486198846153846,42.0,26.0,0.7495911565934066,0.001942543956043874,2
387
- n9,n,tabpfgen,TabPFGen,0.8077859761904762,0.8201093461538461,42.0,26.0,0.8139476611721612,-0.012323369963369912,2
388
- n9,n,tabsyn,TabSyn,0.02657102380952381,0.0,42.0,26.0,0.013285511904761904,0.02657102380952381,2
389
- n9,n,tvae,TVAE,0.639544380952381,0.6246397307692307,42.0,26.0,0.6320920558608059,0.014904650183150236,2
390
- n10,n,real,REAL,1.0,1.0,52.0,23.0,1.0,0.0,2
391
- n10,n,arf,ARF,0.9285715000000001,0.8530022173913043,52.0,23.0,0.8907868586956522,0.07556928260869578,2
392
- n10,n,bayesnet,BayesNet,0.9565933846153847,0.9080745217391304,52.0,23.0,0.9323339531772575,0.04851886287625429,2
393
- n10,n,ctgan,CTGAN,0.9285715000000001,0.8546585217391305,52.0,23.0,0.8916150108695653,0.07391297826086962,2
394
- n10,n,forestdiffusion,ForestDiffusion,0.0,0.0,52.0,23.0,0.0,0.0,2
395
- n10,n,realtabformer,RealTabFormer,0.93498175,0.8752589130434782,52.0,23.0,0.9051203315217391,0.0597228369565217,2
396
- n10,n,tabbyflow,TabbyFlow,0.9592490192307692,0.935817695652174,52.0,23.0,0.9475333574414716,0.02343132357859523,2
397
- n10,n,tabddpm,TabDDPM,0.9285715000000001,0.844720652173913,52.0,23.0,0.8866460760869566,0.0838508478260871,2
398
- n10,n,tabpfgen,TabPFGen,0.9628205192307693,0.9391304347826087,52.0,23.0,0.9509754770066889,0.023690084448160564,2
399
- n10,n,tabsyn,TabSyn,0.0,0.0,52.0,23.0,0.0,0.0,2
400
- n10,n,tvae,TVAE,0.968864423076923,0.9461697391304348,52.0,23.0,0.9575170811036788,0.022694683946488214,2
401
- n11,n,real,REAL,1.0,1.0,18.0,23.0,1.0,0.0,2
402
- n11,n,arf,ARF,1.0,1.0,18.0,23.0,1.0,0.0,2
403
- n11,n,bayesnet,BayesNet,1.0,1.0,18.0,23.0,1.0,0.0,2
404
- n11,n,ctgan,CTGAN,1.0,1.0,18.0,23.0,1.0,0.0,2
405
- n11,n,forestdiffusion,ForestDiffusion,0.0,0.0,18.0,23.0,0.0,0.0,2
406
- n11,n,realtabformer,RealTabFormer,1.0,1.0,18.0,23.0,1.0,0.0,2
407
- n11,n,tabbyflow,TabbyFlow,1.0,1.0,18.0,23.0,1.0,0.0,2
408
- n11,n,tabddpm,TabDDPM,1.0,1.0,18.0,23.0,1.0,0.0,2
409
- n11,n,tabpfgen,TabPFGen,1.0,1.0,18.0,23.0,1.0,0.0,2
410
- n11,n,tabsyn,TabSyn,0.0,0.0,18.0,23.0,0.0,0.0,2
411
- n11,n,tvae,TVAE,1.0,1.0,18.0,23.0,1.0,0.0,2
412
- n12,n,real,REAL,1.0,1.0,12.0,23.0,1.0,0.0,2
413
- n12,n,arf,ARF,0.5411871666666667,0.9540261304347826,12.0,23.0,0.7476066485507247,-0.4128389637681159,2
414
- n12,n,bayesnet,BayesNet,0.30482983333333336,0.622674652173913,12.0,23.0,0.4637522427536232,-0.3178448188405797,2
415
- n12,n,ctgan,CTGAN,0.237584,0.6666617826086957,12.0,23.0,0.45212289130434785,-0.42907778260869567,2
416
- n12,n,forestdiffusion,ForestDiffusion,0.009803916666666667,0.0,12.0,23.0,0.004901958333333334,0.009803916666666667,2
417
- n12,n,tabbyflow,TabbyFlow,0.0059524166666666675,0.014492739130434782,12.0,23.0,0.010222577898550725,-0.008540322463768114,2
418
- n12,n,tabddpm,TabDDPM,0.25819133333333333,0.7139623478260869,12.0,23.0,0.4860768405797101,-0.4557710144927536,2
419
- n12,n,tabpfgen,TabPFGen,0.07234016666666666,0.5743648260869565,12.0,23.0,0.32335249637681157,-0.5020246594202898,2
420
- n12,n,tabsyn,TabSyn,0.0128205,0.0,12.0,23.0,0.00641025,0.0128205,2
421
- n12,n,tvae,TVAE,0.28054025,0.7518098695652173,12.0,23.0,0.5161750597826087,-0.47126961956521735,2
422
- n14,n,real,REAL,1.0,1.0,20.0,26.0,1.0,0.0,2
423
- n14,n,arf,ARF,0.3290475,0.1603231923076923,20.0,26.0,0.24468534615384613,0.1687243076923077,2
424
- n14,n,bayesnet,BayesNet,0.174567,0.11819642307692307,20.0,26.0,0.14638171153846152,0.056370576923076926,2
425
- n14,n,ctgan,CTGAN,0.0833333,0.09615380769230769,20.0,26.0,0.08974355384615385,-0.012820507692307692,2
426
- n14,n,realtabformer,RealTabFormer,0.2314715,0.1687522307692308,20.0,26.0,0.2001118653846154,0.0627192692307692,2
427
- n14,n,tabddpm,TabDDPM,0.0666667,0.0769231153846154,20.0,26.0,0.0717949076923077,-0.0102564153846154,2
428
- n14,n,tabpfgen,TabPFGen,0.0833333,0.09615380769230769,20.0,26.0,0.08974355384615385,-0.012820507692307692,2
429
- n14,n,tabsyn,TabSyn,0.2363385,0.08819553846153846,20.0,26.0,0.16226701923076925,0.14814296153846154,2
430
- n14,n,tvae,TVAE,0.0833333,0.08974357692307693,20.0,26.0,0.08653843846153847,-0.006410276923076927,2
431
- n15,n,real,REAL,1.0,1.0,22.0,26.0,1.0,0.0,2
432
- n15,n,arf,ARF,0.9303030454545455,0.9474359230769231,22.0,26.0,0.9388694842657344,-0.017132877622377696,2
433
- n15,n,bayesnet,BayesNet,0.8968254545454546,0.9146297307692308,22.0,26.0,0.9057275926573427,-0.017804276223776228,2
434
- n15,n,ctgan,CTGAN,0.048015863636363634,0.07979246153846153,22.0,26.0,0.06390416258741258,-0.0317765979020979,2
435
- n15,n,realtabformer,RealTabFormer,0.9029220909090909,0.9082417692307693,22.0,26.0,0.9055819300699302,-0.005319678321678345,2
436
- n15,n,tabddpm,TabDDPM,0.0,0.0,22.0,26.0,0.0,0.0,2
437
- n15,n,tabpfgen,TabPFGen,0.9691919090909091,0.9645299230769232,22.0,26.0,0.9668609160839161,0.00466198601398593,2
438
- n15,n,tabsyn,TabSyn,0.0,0.0,22.0,26.0,0.0,0.0,2
439
- n15,n,tvae,TVAE,0.7398269090909092,0.7373483846153845,22.0,26.0,0.7385876468531469,0.002478524475524657,2
440
- n16,n,real,REAL,1.0,1.0,18.0,7.0,1.0,0.0,2
441
- n16,n,arf,ARF,0.0,0.0,18.0,7.0,0.0,0.0,2
442
- n16,n,bayesnet,BayesNet,1.0,1.0,18.0,7.0,1.0,0.0,2
443
- n16,n,ctgan,CTGAN,1.0,1.0,18.0,7.0,1.0,0.0,2
444
- n16,n,tabddpm,TabDDPM,0.0,0.0,18.0,7.0,0.0,0.0,2
445
- n16,n,tabsyn,TabSyn,0.0,0.0,18.0,7.0,0.0,0.0,2
446
- n16,n,tvae,TVAE,0.5,1.0,18.0,7.0,0.75,-0.5,2
447
- n17,n,real,REAL,1.0,,42.0,,1.0,,1
448
- n17,n,arf,ARF,0.711438380952381,,42.0,,0.711438380952381,,1
449
- n17,n,bayesnet,BayesNet,0.5866132857142857,,42.0,,0.5866132857142857,,1
450
- n17,n,ctgan,CTGAN,0.6049935,,42.0,,0.6049935,,1
451
- n17,n,realtabformer,RealTabFormer,0.5954431428571428,,42.0,,0.5954431428571428,,1
452
- n17,n,tabddpm,TabDDPM,0.7035091666666666,,42.0,,0.7035091666666666,,1
453
- n17,n,tabpfgen,TabPFGen,0.8013314761904761,,42.0,,0.8013314761904761,,1
454
- n17,n,tabsyn,TabSyn,0.024943309523809527,,42.0,,0.024943309523809527,,1
455
- n17,n,tvae,TVAE,0.5536538095238095,,42.0,,0.5536538095238095,,1
456
- n18,n,real,REAL,1.0,1.0,57.0,8.0,1.0,0.0,2
457
- n18,n,arf,ARF,0.356669350877193,0.6466197499999999,57.0,8.0,0.5016445504385965,-0.28995039912280696,2
458
- n18,n,bayesnet,BayesNet,0.07711054385964912,0.64372,57.0,8.0,0.36041527192982453,-0.5666094561403509,2
459
- n18,n,ctgan,CTGAN,0.10847398245614036,0.18900100000000003,57.0,8.0,0.1487374912280702,-0.08052701754385967,2
460
- n18,n,tvae,TVAE,0.10300861403508771,0.138428125,57.0,8.0,0.12071836951754386,-0.035419510964912304,2
461
- n19,n,real,REAL,1.0,1.0,35.0,26.0,1.0,0.0,2
462
- n19,n,arf,ARF,0.5303510857142857,0.3510676153846154,35.0,26.0,0.44070935054945054,0.1792834703296703,2
463
- n19,n,bayesnet,BayesNet,0.6144322571428571,0.3181470769230769,35.0,26.0,0.46628966703296704,0.2962851802197802,2
464
- n19,n,ctgan,CTGAN,0.3472913714285714,0.3141574615384615,35.0,26.0,0.33072441648351647,0.03313390989010989,2
465
- n19,n,tabddpm,TabDDPM,0.005024114285714286,0.047848192307692314,35.0,26.0,0.0264361532967033,-0.042824078021978025,2
466
- n19,n,tabpfgen,TabPFGen,0.7280837142857143,0.5129582692307693,35.0,26.0,0.6205209917582417,0.21512544505494502,2
467
- n19,n,tvae,TVAE,0.3573153142857143,0.16292615384615386,35.0,26.0,0.26012073406593406,0.19438916043956042,2
468
- n20,n,real,REAL,1.0,,38.0,,1.0,,1
469
- n20,n,arf,ARF,0.009414631578947369,,38.0,,0.009414631578947369,,1
470
- n20,n,bayesnet,BayesNet,0.0,,38.0,,0.0,,1
471
- n20,n,ctgan,CTGAN,0.0,,38.0,,0.0,,1
472
- n20,n,realtabformer,RealTabFormer,0.11557476315789472,,38.0,,0.11557476315789472,,1
473
- n20,n,tabddpm,TabDDPM,0.0,,38.0,,0.0,,1
474
- n20,n,tabpfgen,TabPFGen,0.0,,38.0,,0.0,,1
475
- n20,n,tabsyn,TabSyn,0.0009473684210526316,,38.0,,0.0009473684210526316,,1
476
- n20,n,tvae,TVAE,0.0,,38.0,,0.0,,1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ dataset_id,dataset_prefix,model_id,model_label,internal_profile_stability,subgroup_size_stability,internal_profile_stability__query_count,subgroup_size_stability__query_count,subgroup_structure_score,profile_minus_size,active_subitem_count
2
+ c2,c,real,REAL,1.0,1.0,25.0,33.0,1.0,0.0,2
3
+ c2,c,arf,ARF,1.0,0.9791057575757576,25.0,33.0,0.9895528787878788,0.020894242424242426,2
4
+ c2,c,bayesnet,BayesNet,1.0,0.987013,25.0,33.0,0.9935065000000001,0.01298699999999997,2
5
+ c2,c,ctgan,CTGAN,1.0,0.9585858787878788,25.0,33.0,0.9792929393939394,0.04141412121212118,2
6
+ c2,c,forestdiffusion,ForestDiffusion,1.0,0.9770396363636364,25.0,33.0,0.9885198181818182,0.022960363636363557,2
7
+ c2,c,realtabformer,RealTabFormer,1.0,0.987013,25.0,33.0,0.9935065000000001,0.01298699999999997,2
8
+ c2,c,tabbyflow,TabbyFlow,0.85333336,0.8186869393939394,25.0,33.0,0.8360101496969697,0.0346464206060606,2
9
+ c2,c,tabddpm,TabDDPM,1.0,0.9627181212121212,25.0,33.0,0.9813590606060606,0.03728187878787881,2
10
+ c2,c,tabdiff,TabDiff,0.85333336,0.819336303030303,25.0,33.0,0.8363348315151515,0.033997056969697015,2
11
+ c2,c,tabpfgen,TabPFGen,0.87,0.8234353939393939,25.0,33.0,0.846717696969697,0.046564606060606084,2
12
+ c2,c,tabsyn,TabSyn,0.91333336,0.8442114242424242,25.0,33.0,0.878772392121212,0.06912193575757575,2
13
+ c2,c,tvae,TVAE,1.0,0.9791057575757576,25.0,33.0,0.9895528787878788,0.020894242424242426,2
14
+ c3,c,real,REAL,1.0,1.0,6.0,7.0,1.0,0.0,2
15
+ c3,c,arf,ARF,1.0,1.0,6.0,7.0,1.0,0.0,2
16
+ c3,c,bayesnet,BayesNet,1.0,1.0,6.0,7.0,1.0,0.0,2
17
+ c3,c,ctgan,CTGAN,1.0,1.0,6.0,7.0,1.0,0.0,2
18
+ c3,c,forestdiffusion,ForestDiffusion,1.0,1.0,6.0,7.0,1.0,0.0,2
19
+ c3,c,realtabformer,RealTabFormer,1.0,1.0,6.0,7.0,1.0,0.0,2
20
+ c3,c,tabbyflow,TabbyFlow,1.0,1.0,6.0,7.0,1.0,0.0,2
21
+ c3,c,tabddpm,TabDDPM,1.0,1.0,6.0,7.0,1.0,0.0,2
22
+ c3,c,tabdiff,TabDiff,1.0,1.0,6.0,7.0,1.0,0.0,2
23
+ c3,c,tabpfgen,TabPFGen,1.0,1.0,6.0,7.0,1.0,0.0,2
24
+ c3,c,tabsyn,TabSyn,1.0,1.0,6.0,7.0,1.0,0.0,2
25
+ c3,c,tvae,TVAE,1.0,1.0,6.0,7.0,1.0,0.0,2
26
+ c4,c,real,REAL,1.0,1.0,21.0,20.0,1.0,0.0,2
27
+ c4,c,arf,ARF,1.0,0.9875,21.0,20.0,0.99375,0.012499999999999956,2
28
+ c4,c,bayesnet,BayesNet,1.0,0.9875,21.0,20.0,0.99375,0.012499999999999956,2
29
+ c4,c,ctgan,CTGAN,1.0,0.9875,21.0,20.0,0.99375,0.012499999999999956,2
30
+ c4,c,forestdiffusion,ForestDiffusion,1.0,0.975,21.0,20.0,0.9875,0.025000000000000022,2
31
+ c4,c,realtabformer,RealTabFormer,1.0,1.0,21.0,20.0,1.0,0.0,2
32
+ c4,c,tabbyflow,TabbyFlow,1.0,1.0,21.0,20.0,1.0,0.0,2
33
+ c4,c,tabddpm,TabDDPM,1.0,1.0,21.0,20.0,1.0,0.0,2
34
+ c4,c,tabdiff,TabDiff,1.0,0.9875,21.0,20.0,0.99375,0.012499999999999956,2
35
+ c4,c,tabpfgen,TabPFGen,1.0,1.0,21.0,20.0,1.0,0.0,2
36
+ c4,c,tabsyn,TabSyn,1.0,0.9625,21.0,20.0,0.98125,0.03749999999999998,2
37
+ c4,c,tvae,TVAE,1.0,1.0,21.0,20.0,1.0,0.0,2
38
+ c5,c,real,REAL,1.0,1.0,10.0,3.0,1.0,0.0,2
39
+ c5,c,arf,ARF,0.9800000000000001,0.7222223333333333,10.0,3.0,0.8511111666666666,0.2577776666666668,2
40
+ c5,c,bayesnet,BayesNet,0.9633333000000001,0.7222223333333333,10.0,3.0,0.8427778166666666,0.24111096666666676,2
41
+ c5,c,ctgan,CTGAN,0.9800000000000001,0.7222223333333333,10.0,3.0,0.8511111666666666,0.2577776666666668,2
42
+ c5,c,forestdiffusion,ForestDiffusion,0.9349999999999999,0.7222223333333333,10.0,3.0,0.8286111666666667,0.21277766666666664,2
43
+ c5,c,realtabformer,RealTabFormer,0.9800000000000001,0.7222223333333333,10.0,3.0,0.8511111666666666,0.2577776666666668,2
44
+ c5,c,tabbyflow,TabbyFlow,0.97,0.7222223333333333,10.0,3.0,0.8461111666666666,0.24777766666666667,2
45
+ c5,c,tabddpm,TabDDPM,0.9383333,0.7222223333333333,10.0,3.0,0.8302778166666667,0.21611096666666674,2
46
+ c5,c,tabdiff,TabDiff,0.9800000000000001,0.7222223333333333,10.0,3.0,0.8511111666666666,0.2577776666666668,2
47
+ c5,c,tabpfgen,TabPFGen,0.9888889000000001,0.8222223333333334,10.0,3.0,0.9055556166666667,0.16666656666666668,2
48
+ c5,c,tabsyn,TabSyn,0.9550000000000001,0.7222223333333333,10.0,3.0,0.8386111666666667,0.23277766666666677,2
49
+ c5,c,tvae,TVAE,0.9383333,0.7222223333333333,10.0,3.0,0.8302778166666667,0.21611096666666674,2
50
+ c6,c,real,REAL,1.0,1.0,11.0,4.0,1.0,0.0,2
51
+ c6,c,arf,ARF,0.55,0.55,11.0,4.0,0.55,0.0,2
52
+ c6,c,bayesnet,BayesNet,0.55,0.5548912500000001,11.0,4.0,0.552445625,-0.004891250000000014,2
53
+ c6,c,ctgan,CTGAN,0.55,0.55,11.0,4.0,0.55,0.0,2
54
+ c6,c,forestdiffusion,ForestDiffusion,0.5482954545454546,0.5453125000000001,11.0,4.0,0.5468039772727273,0.002982954545454497,2
55
+ c6,c,realtabformer,RealTabFormer,0.55,0.55,11.0,4.0,0.55,0.0,2
56
+ c6,c,tabbyflow,TabbyFlow,0.55,0.5523935,11.0,4.0,0.55119675,-0.0023934999999999373,2
57
+ c6,c,tabddpm,TabDDPM,0.5482954545454546,0.5453125000000001,11.0,4.0,0.5468039772727273,0.002982954545454497,2
58
+ c6,c,tabdiff,TabDiff,0.55,0.55,11.0,4.0,0.55,0.0,2
59
+ c6,c,tabpfgen,TabPFGen,0.55,0.55,11.0,4.0,0.55,0.0,2
60
+ c6,c,tabsyn,TabSyn,0.55,0.55,11.0,4.0,0.55,0.0,2
61
+ c6,c,tvae,TVAE,0.55,0.5523935,11.0,4.0,0.55119675,-0.0023934999999999373,2
62
+ c7,c,real,REAL,1.0,1.0,20.0,32.0,1.0,0.0,2
63
+ c7,c,arf,ARF,1.0,0.9561698750000001,20.0,32.0,0.9780849375,0.04383012499999994,2
64
+ c7,c,bayesnet,BayesNet,0.95,0.94286859375,20.0,32.0,0.9464342968749999,0.007131406249999972,2
65
+ c7,c,ctgan,CTGAN,1.0,0.9471268125,20.0,32.0,0.97356340625,0.05287318750000003,2
66
+ c7,c,forestdiffusion,ForestDiffusion,1.0,0.96447175,20.0,32.0,0.982235875,0.03552825000000004,2
67
+ c7,c,realtabformer,RealTabFormer,0.95,0.95035484375,20.0,32.0,0.950177421875,-0.00035484375000005564,2
68
+ c7,c,tabbyflow,TabbyFlow,0.9375,0.89427225,20.0,32.0,0.915886125,0.04322775000000001,2
69
+ c7,c,tabddpm,TabDDPM,1.0,0.9537889375,20.0,32.0,0.9768944687500001,0.046211062499999955,2
70
+ c7,c,tabdiff,TabDiff,0.9875,0.906428875,20.0,32.0,0.9469644375,0.08107112500000002,2
71
+ c7,c,tabpfgen,TabPFGen,1.0,0.90119046875,20.0,32.0,0.9505952343749999,0.09880953125000003,2
72
+ c7,c,tabsyn,TabSyn,0.9375,0.8906550625,20.0,32.0,0.91407753125,0.04684493749999996,2
73
+ c7,c,tvae,TVAE,0.95,0.94172678125,20.0,32.0,0.945863390625,0.008273218749999978,2
74
+ c8,c,real,REAL,1.0,1.0,18.0,8.0,1.0,0.0,2
75
+ c8,c,arf,ARF,1.0,1.0,18.0,8.0,1.0,0.0,2
76
+ c8,c,bayesnet,BayesNet,1.0,1.0,18.0,8.0,1.0,0.0,2
77
+ c8,c,ctgan,CTGAN,1.0,1.0,18.0,8.0,1.0,0.0,2
78
+ c8,c,forestdiffusion,ForestDiffusion,0.9444444444444444,1.0,18.0,8.0,0.9722222222222222,-0.05555555555555558,2
79
+ c8,c,realtabformer,RealTabFormer,1.0,1.0,18.0,8.0,1.0,0.0,2
80
+ c8,c,tabbyflow,TabbyFlow,0.9074074444444444,1.0,18.0,8.0,0.9537037222222222,-0.09259255555555557,2
81
+ c8,c,tabddpm,TabDDPM,0.9074074444444444,1.0,18.0,8.0,0.9537037222222222,-0.09259255555555557,2
82
+ c8,c,tabdiff,TabDiff,0.9444444444444444,1.0,18.0,8.0,0.9722222222222222,-0.05555555555555558,2
83
+ c8,c,tabpfgen,TabPFGen,1.0,1.0,18.0,8.0,1.0,0.0,2
84
+ c8,c,tabsyn,TabSyn,1.0,1.0,18.0,8.0,1.0,0.0,2
85
+ c8,c,tvae,TVAE,0.962963,0.958333375,18.0,8.0,0.9606481875,0.004629624999999971,2
86
+ c9,c,real,REAL,1.0,1.0,18.0,8.0,1.0,0.0,2
87
+ c9,c,arf,ARF,0.2222222222222222,0.25,18.0,8.0,0.2361111111111111,-0.02777777777777779,2
88
+ c9,c,bayesnet,BayesNet,0.2485637777777778,0.2740745,18.0,8.0,0.2613191388888889,-0.0255107222222222,2
89
+ c9,c,ctgan,CTGAN,0.24633288888888888,0.27211225,18.0,8.0,0.25922256944444444,-0.02577936111111112,2
90
+ c9,c,forestdiffusion,ForestDiffusion,0.2222222222222222,0.25,18.0,8.0,0.2361111111111111,-0.02777777777777779,2
91
+ c9,c,realtabformer,RealTabFormer,0.9741185555555556,0.97514475,18.0,8.0,0.9746316527777779,-0.001026194444444406,2
92
+ c9,c,tabbyflow,TabbyFlow,0.2222222222222222,0.25,18.0,8.0,0.2361111111111111,-0.02777777777777779,2
93
+ c9,c,tabddpm,TabDDPM,0.2222222222222222,0.25,18.0,8.0,0.2361111111111111,-0.02777777777777779,2
94
+ c9,c,tabdiff,TabDiff,0.2222222222222222,0.25,18.0,8.0,0.2361111111111111,-0.02777777777777779,2
95
+ c9,c,tabpfgen,TabPFGen,0.2222222222222222,0.25,18.0,8.0,0.2361111111111111,-0.02777777777777779,2
96
+ c9,c,tabsyn,TabSyn,0.2222222222222222,0.25,18.0,8.0,0.2361111111111111,-0.02777777777777779,2
97
+ c9,c,tvae,TVAE,0.24786544444444447,0.273729625,18.0,8.0,0.2607975347222222,-0.025864180555555505,2
98
+ c10,c,real,REAL,1.0,1.0,18.0,8.0,1.0,0.0,2
99
+ c10,c,arf,ARF,1.0,1.0,18.0,8.0,1.0,0.0,2
100
+ c10,c,bayesnet,BayesNet,1.0,1.0,18.0,8.0,1.0,0.0,2
101
+ c10,c,ctgan,CTGAN,1.0,1.0,18.0,8.0,1.0,0.0,2
102
+ c10,c,forestdiffusion,ForestDiffusion,1.0,1.0,18.0,8.0,1.0,0.0,2
103
+ c10,c,realtabformer,RealTabFormer,1.0,1.0,18.0,8.0,1.0,0.0,2
104
+ c10,c,tabbyflow,TabbyFlow,1.0,1.0,18.0,8.0,1.0,0.0,2
105
+ c10,c,tabddpm,TabDDPM,1.0,1.0,18.0,8.0,1.0,0.0,2
106
+ c10,c,tabdiff,TabDiff,1.0,1.0,18.0,8.0,1.0,0.0,2
107
+ c10,c,tabpfgen,TabPFGen,1.0,1.0,18.0,8.0,1.0,0.0,2
108
+ c10,c,tvae,TVAE,0.9658120000000001,0.9615385,18.0,8.0,0.9636752500000001,0.004273500000000152,2
109
+ c11,c,real,REAL,1.0,1.0,23.0,29.0,1.0,0.0,2
110
+ c11,c,arf,ARF,0.9855072608695652,0.9367816206896552,23.0,29.0,0.9611444407796101,0.04872564017990999,2
111
+ c11,c,bayesnet,BayesNet,1.0,0.9157087931034482,23.0,29.0,0.9578543965517241,0.08429120689655178,2
112
+ c11,c,ctgan,CTGAN,0.9855072608695652,0.9022988275862068,23.0,29.0,0.943903044227886,0.08320843328335836,2
113
+ c11,c,forestdiffusion,ForestDiffusion,0.9855072608695652,0.9252873448275862,23.0,29.0,0.9553973028485757,0.06021991604197896,2
114
+ c11,c,realtabformer,RealTabFormer,1.0,1.0,23.0,29.0,1.0,0.0,2
115
+ c11,c,tabbyflow,TabbyFlow,1.0,0.952107275862069,23.0,29.0,0.9760536379310345,0.047892724137931,2
116
+ c11,c,tabddpm,TabDDPM,1.0,0.9454022758620689,23.0,29.0,0.9727011379310344,0.05459772413793107,2
117
+ c11,c,tabdiff,TabDiff,0.9855072608695652,0.9712643793103448,23.0,29.0,0.978385820089955,0.014242881559220377,2
118
+ c11,c,tabpfgen,TabPFGen,1.0,0.9727011379310345,23.0,29.0,0.9863505689655172,0.02729886206896548,2
119
+ c11,c,tabsyn,TabSyn,1.0,0.9501915517241378,23.0,29.0,0.9750957758620689,0.04980844827586217,2
120
+ c11,c,tvae,TVAE,1.0,0.9578544137931035,23.0,29.0,0.9789272068965518,0.04214558620689646,2
121
+ c12,c,real,REAL,1.0,1.0,12.0,1.0,1.0,0.0,2
122
+ c12,c,arf,ARF,1.0,1.0,12.0,1.0,1.0,0.0,2
123
+ c12,c,bayesnet,BayesNet,1.0,1.0,12.0,1.0,1.0,0.0,2
124
+ c12,c,ctgan,CTGAN,1.0,1.0,12.0,1.0,1.0,0.0,2
125
+ c12,c,forestdiffusion,ForestDiffusion,0.5833333333333334,1.0,12.0,1.0,0.7916666666666667,-0.41666666666666663,2
126
+ c12,c,realtabformer,RealTabFormer,1.0,1.0,12.0,1.0,1.0,0.0,2
127
+ c12,c,tabpfgen,TabPFGen,1.0,1.0,12.0,1.0,1.0,0.0,2
128
+ c12,c,tabsyn,TabSyn,1.0,1.0,12.0,1.0,1.0,0.0,2
129
+ c12,c,tvae,TVAE,0.6666666666666666,0.5,12.0,1.0,0.5833333333333333,0.16666666666666663,2
130
+ c13,c,real,REAL,1.0,1.0,12.0,3.0,1.0,0.0,2
131
+ c13,c,arf,ARF,1.0,1.0,12.0,3.0,1.0,0.0,2
132
+ c13,c,bayesnet,BayesNet,1.0,1.0,12.0,3.0,1.0,0.0,2
133
+ c13,c,ctgan,CTGAN,0.18472208333333331,0.6969696666666666,12.0,3.0,0.44084587499999994,-0.5122475833333333,2
134
+ c13,c,forestdiffusion,ForestDiffusion,1.0,1.0,12.0,3.0,1.0,0.0,2
135
+ c13,c,realtabformer,RealTabFormer,1.0,1.0,12.0,3.0,1.0,0.0,2
136
+ c13,c,tabbyflow,TabbyFlow,1.0,1.0,12.0,3.0,1.0,0.0,2
137
+ c13,c,tabddpm,TabDDPM,0.5027779166666667,0.7272726666666666,12.0,3.0,0.6150252916666666,-0.22449474999999985,2
138
+ c13,c,tabdiff,TabDiff,0.9263889166666667,1.0,12.0,3.0,0.9631944583333334,-0.07361108333333333,2
139
+ c13,c,tabpfgen,TabPFGen,0.09999999999999999,0.0,12.0,3.0,0.049999999999999996,0.09999999999999999,2
140
+ c13,c,tabsyn,TabSyn,1.0,1.0,12.0,3.0,1.0,0.0,2
141
+ c13,c,tvae,TVAE,0.18472208333333331,0.6969696666666666,12.0,3.0,0.44084587499999994,-0.5122475833333333,2
142
+ c14,c,real,REAL,1.0,1.0,18.0,8.0,1.0,0.0,2
143
+ c14,c,arf,ARF,1.0,1.0,18.0,8.0,1.0,0.0,2
144
+ c14,c,bayesnet,BayesNet,1.0,1.0,18.0,8.0,1.0,0.0,2
145
+ c14,c,ctgan,CTGAN,1.0,0.77827375,18.0,8.0,0.8891368749999999,0.22172625,2
146
+ c14,c,forestdiffusion,ForestDiffusion,0.7222222222222222,0.838392875,18.0,8.0,0.7803075486111111,-0.11617065277777783,2
147
+ c14,c,realtabformer,RealTabFormer,1.0,1.0,18.0,8.0,1.0,0.0,2
148
+ c14,c,tabbyflow,TabbyFlow,1.0,0.986858875,18.0,8.0,0.9934294375,0.013141124999999976,2
149
+ c14,c,tabddpm,TabDDPM,0.40740744444444443,0.34141475,18.0,8.0,0.3744110972222222,0.06599269444444444,2
150
+ c14,c,tabdiff,TabDiff,1.0,1.0,18.0,8.0,1.0,0.0,2
151
+ c14,c,tabpfgen,TabPFGen,1.0,1.0,18.0,8.0,1.0,0.0,2
152
+ c14,c,tabsyn,TabSyn,1.0,1.0,18.0,8.0,1.0,0.0,2
153
+ c14,c,tvae,TVAE,0.8148148888888889,0.69109425,18.0,8.0,0.7529545694444444,0.12372063888888885,2
154
+ c15,c,real,REAL,1.0,1.0,18.0,8.0,1.0,0.0,2
155
+ c15,c,arf,ARF,0.8888889999999999,0.848214375,18.0,8.0,0.8685516874999999,0.040674624999999964,2
156
+ c15,c,bayesnet,BayesNet,0.7394182222222222,0.817915125,18.0,8.0,0.7786666736111111,-0.07849690277777777,2
157
+ c15,c,ctgan,CTGAN,0.7777776666666667,0.592948625,18.0,8.0,0.6853631458333334,0.1848290416666667,2
158
+ c15,c,forestdiffusion,ForestDiffusion,0.5944445555555555,0.816147375,18.0,8.0,0.7052959652777777,-0.22170281944444448,2
159
+ c15,c,realtabformer,RealTabFormer,1.0,1.0,18.0,8.0,1.0,0.0,2
160
+ c15,c,tabbyflow,TabbyFlow,0.6500001111111111,0.81133175,18.0,8.0,0.7306659305555556,-0.1613316388888889,2
161
+ c15,c,tabdiff,TabDiff,0.6500001111111111,0.836541875,18.0,8.0,0.7432709930555556,-0.18654176388888888,2
162
+ c15,c,tabpfgen,TabPFGen,0.7394182222222222,0.817915125,18.0,8.0,0.7786666736111111,-0.07849690277777777,2
163
+ c15,c,tabsyn,TabSyn,0.6500001111111111,0.836541875,18.0,8.0,0.7432709930555556,-0.18654176388888888,2
164
+ c15,c,tvae,TVAE,0.5595237777777777,0.5476795,18.0,8.0,0.5536016388888889,0.011844277777777745,2
165
+ c16,c,real,REAL,1.0,1.0,16.0,8.0,1.0,0.0,2
166
+ c16,c,arf,ARF,0.875,0.875,16.0,8.0,0.875,0.0,2
167
+ c16,c,bayesnet,BayesNet,0.6520833125,0.636111125,16.0,8.0,0.64409721875,0.015972187499999957,2
168
+ c16,c,ctgan,CTGAN,0.875,0.875,16.0,8.0,0.875,0.0,2
169
+ c16,c,forestdiffusion,ForestDiffusion,0.651879125,0.627777875,16.0,8.0,0.6398285,0.024101249999999963,2
170
+ c16,c,realtabformer,RealTabFormer,0.850786125,0.850786125,16.0,8.0,0.850786125,0.0,2
171
+ c16,c,tabbyflow,TabbyFlow,0.2978069375,0.31754387500000003,16.0,8.0,0.30767540625,-0.01973693750000005,2
172
+ c16,c,tabdiff,TabDiff,0.584795375,0.550438625,16.0,8.0,0.567617,0.03435675000000005,2
173
+ c16,c,tabsyn,TabSyn,0.557383125,0.5542765000000001,16.0,8.0,0.5558298125000001,0.0031066249999999185,2
174
+ c16,c,tvae,TVAE,0.4308365625,0.451424875,16.0,8.0,0.44113071875,-0.020588312499999983,2
175
+ c17,c,real,REAL,1.0,1.0,14.0,7.0,1.0,0.0,2
176
+ c17,c,arf,ARF,0.6883422857142857,0.6883422857142857,14.0,7.0,0.6883422857142857,0.0,2
177
+ c17,c,bayesnet,BayesNet,0.6890161428571429,0.6890161428571429,14.0,7.0,0.6890161428571429,0.0,2
178
+ c17,c,ctgan,CTGAN,0.9483648571428571,0.9483648571428571,14.0,7.0,0.9483648571428571,0.0,2
179
+ c17,c,forestdiffusion,ForestDiffusion,0.5178571428571429,0.5178571428571429,14.0,7.0,0.5178571428571429,0.0,2
180
+ c17,c,realtabformer,RealTabFormer,0.551304,0.551304,14.0,7.0,0.551304,0.0,2
181
+ c17,c,tabbyflow,TabbyFlow,0.30357142857142855,0.30357142857142855,14.0,7.0,0.30357142857142855,0.0,2
182
+ c17,c,tabdiff,TabDiff,0.5378151428571429,0.5378151428571429,14.0,7.0,0.5378151428571429,0.0,2
183
+ c17,c,tabpfgen,TabPFGen,0.6809298571428571,0.6809298571428571,14.0,7.0,0.6809298571428571,0.0,2
184
+ c17,c,tabsyn,TabSyn,0.5210082857142857,0.5210082857142857,14.0,7.0,0.5210082857142857,0.0,2
185
+ c17,c,tvae,TVAE,0.8465467142857143,0.8465467142857143,14.0,7.0,0.8465467142857143,0.0,2
186
+ c18,c,real,REAL,1.0,1.0,14.0,7.0,1.0,0.0,2
187
+ c18,c,arf,ARF,0.41077457142857143,0.6975441428571428,14.0,7.0,0.5541593571428571,-0.2867695714285714,2
188
+ c18,c,bayesnet,BayesNet,0.3697487857142857,0.6252537142857142,14.0,7.0,0.49750124999999995,-0.2555049285714285,2
189
+ c18,c,ctgan,CTGAN,0.4567326428571428,0.7246898571428572,14.0,7.0,0.59071125,-0.26795721428571434,2
190
+ c18,c,forestdiffusion,ForestDiffusion,0.3610025,0.6077452857142857,14.0,7.0,0.48437389285714283,-0.24674278571428565,2
191
+ c18,c,realtabformer,RealTabFormer,0.8228398571428571,0.8467141428571429,14.0,7.0,0.834777,-0.023874285714285737,2
192
+ c18,c,tabbyflow,TabbyFlow,0.25040414285714285,0.39837214285714284,14.0,7.0,0.32438814285714285,-0.147968,2
193
+ c18,c,tvae,TVAE,0.46506757142857147,0.7246914285714287,14.0,7.0,0.5948795,-0.2596238571428572,2
194
+ c19,c,real,REAL,1.0,1.0,16.0,7.0,1.0,0.0,2
195
+ c19,c,arf,ARF,1.0,1.0,16.0,7.0,1.0,0.0,2
196
+ c19,c,bayesnet,BayesNet,1.0,1.0,16.0,7.0,1.0,0.0,2
197
+ c19,c,ctgan,CTGAN,0.78125,0.75,16.0,7.0,0.765625,0.03125,2
198
+ c19,c,forestdiffusion,ForestDiffusion,0.8125,0.7857142857142857,16.0,7.0,0.7991071428571428,0.0267857142857143,2
199
+ c19,c,realtabformer,RealTabFormer,0.53125,0.5357142857142857,16.0,7.0,0.5334821428571428,-0.004464285714285698,2
200
+ c19,c,tabbyflow,TabbyFlow,0.65625,0.6785714285714286,16.0,7.0,0.6674107142857143,-0.022321428571428603,2
201
+ c19,c,tabdiff,TabDiff,0.8125,0.7857142857142857,16.0,7.0,0.7991071428571428,0.0267857142857143,2
202
+ c19,c,tabpfgen,TabPFGen,1.0,1.0,16.0,7.0,1.0,0.0,2
203
+ c19,c,tabsyn,TabSyn,0.859375,0.9107142857142857,16.0,7.0,0.8850446428571428,-0.0513392857142857,2
204
+ c19,c,tvae,TVAE,0.796875,0.7678571428571429,16.0,7.0,0.7823660714285714,0.029017857142857095,2
205
+ c20,c,real,REAL,1.0,1.0,11.0,2.0,1.0,0.0,2
206
+ c20,c,arf,ARF,1.0,1.0,11.0,2.0,1.0,0.0,2
207
+ c20,c,bayesnet,BayesNet,1.0,1.0,11.0,2.0,1.0,0.0,2
208
+ c20,c,ctgan,CTGAN,1.0,1.0,11.0,2.0,1.0,0.0,2
209
+ c20,c,forestdiffusion,ForestDiffusion,1.0,1.0,11.0,2.0,1.0,0.0,2
210
+ c20,c,realtabformer,RealTabFormer,1.0,1.0,11.0,2.0,1.0,0.0,2
211
+ c20,c,tabbyflow,TabbyFlow,1.0,1.0,11.0,2.0,1.0,0.0,2
212
+ c20,c,tabddpm,TabDDPM,0.8363636363636363,0.7,11.0,2.0,0.7681818181818181,0.13636363636363635,2
213
+ c20,c,tabpfgen,TabPFGen,1.0,1.0,11.0,2.0,1.0,0.0,2
214
+ c20,c,tabsyn,TabSyn,1.0,1.0,11.0,2.0,1.0,0.0,2
215
+ c20,c,tvae,TVAE,1.0,1.0,11.0,2.0,1.0,0.0,2
216
+ m1,m,real,REAL,1.0,1.0,18.0,8.0,1.0,0.0,2
217
+ m1,m,arf,ARF,1.0,0.998975375,18.0,8.0,0.9994876875,0.0010246250000000012,2
218
+ m1,m,bayesnet,BayesNet,1.0,1.0,18.0,8.0,1.0,0.0,2
219
+ m1,m,ctgan,CTGAN,1.0,1.0,18.0,8.0,1.0,0.0,2
220
+ m1,m,forestdiffusion,ForestDiffusion,0.9259258888888888,0.85,18.0,8.0,0.8879629444444443,0.07592588888888885,2
221
+ m1,m,realtabformer,RealTabFormer,0.9407406666666667,0.847131125,18.0,8.0,0.8939358958333333,0.09360954166666668,2
222
+ m1,m,tabbyflow,TabbyFlow,0.9814814444444444,0.875,18.0,8.0,0.9282407222222222,0.1064814444444444,2
223
+ m1,m,tabddpm,TabDDPM,1.0,0.675,18.0,8.0,0.8375,0.32499999999999996,2
224
+ m1,m,tabdiff,TabDiff,1.0,0.875,18.0,8.0,0.9375,0.125,2
225
+ m1,m,tabpfgen,TabPFGen,1.0,0.9146175,18.0,8.0,0.9573087499999999,0.08538250000000003,2
226
+ m1,m,tabsyn,TabSyn,1.0,0.875,18.0,8.0,0.9375,0.125,2
227
+ m1,m,tvae,TVAE,0.6722222222222222,0.681523125,18.0,8.0,0.676872673611111,-0.009300902777777842,2
228
+ m2,m,real,REAL,1.0,1.0,3.0,1.0,1.0,0.0,2
229
+ m2,m,arf,ARF,0.40001766666666666,0.55,3.0,1.0,0.4750088333333333,-0.14998233333333338,2
230
+ m2,m,bayesnet,BayesNet,0.4000156666666667,0.55,3.0,1.0,0.4750078333333334,-0.14998433333333333,2
231
+ m2,m,ctgan,CTGAN,0.40018866666666675,0.55,3.0,1.0,0.4750943333333334,-0.1498113333333333,2
232
+ m2,m,forestdiffusion,ForestDiffusion,0.400025,0.55,3.0,1.0,0.47501250000000006,-0.14997500000000002,2
233
+ m2,m,realtabformer,RealTabFormer,0.481818,0.55,3.0,1.0,0.5159090000000001,-0.06818200000000002,2
234
+ m2,m,tabbyflow,TabbyFlow,0.366733,0.55,3.0,1.0,0.4583665,-0.18326700000000007,2
235
+ m2,m,tabddpm,TabDDPM,0.405303,0.55,3.0,1.0,0.4776515,-0.14469700000000002,2
236
+ m2,m,tabpfgen,TabPFGen,0.40001633333333336,0.55,3.0,1.0,0.4750081666666667,-0.14998366666666668,2
237
+ m2,m,tabsyn,TabSyn,0.4021316666666667,0.55,3.0,1.0,0.4760658333333334,-0.14786833333333332,2
238
+ m2,m,tvae,TVAE,0.400239,0.55,3.0,1.0,0.47511950000000003,-0.14976100000000003,2
239
+ m4,m,real,REAL,1.0,1.0,14.0,7.0,1.0,0.0,2
240
+ m4,m,arf,ARF,1.0,1.0,14.0,7.0,1.0,0.0,2
241
+ m4,m,bayesnet,BayesNet,1.0,1.0,14.0,7.0,1.0,0.0,2
242
+ m4,m,ctgan,CTGAN,0.7619048571428572,0.7619048571428572,14.0,7.0,0.7619048571428572,0.0,2
243
+ m4,m,forestdiffusion,ForestDiffusion,1.0,1.0,14.0,7.0,1.0,0.0,2
244
+ m4,m,realtabformer,RealTabFormer,1.0,1.0,14.0,7.0,1.0,0.0,2
245
+ m4,m,tabbyflow,TabbyFlow,1.0,1.0,14.0,7.0,1.0,0.0,2
246
+ m4,m,tabddpm,TabDDPM,0.9523808571428571,0.9523808571428571,14.0,7.0,0.9523808571428571,0.0,2
247
+ m4,m,tabdiff,TabDiff,1.0,1.0,14.0,7.0,1.0,0.0,2
248
+ m4,m,tabpfgen,TabPFGen,1.0,1.0,14.0,7.0,1.0,0.0,2
249
+ m4,m,tabsyn,TabSyn,1.0,1.0,14.0,7.0,1.0,0.0,2
250
+ m4,m,tvae,TVAE,0.7619048571428572,0.7619048571428572,14.0,7.0,0.7619048571428572,0.0,2
251
+ m5,m,real,REAL,1.0,1.0,6.0,1.0,1.0,0.0,2
252
+ m5,m,arf,ARF,0.555,0.55,6.0,1.0,0.5525,0.0050000000000000044,2
253
+ m5,m,bayesnet,BayesNet,0.555,0.55,6.0,1.0,0.5525,0.0050000000000000044,2
254
+ m5,m,ctgan,CTGAN,0.2641543333333333,0.55,6.0,1.0,0.4070771666666667,-0.2858456666666667,2
255
+ m5,m,forestdiffusion,ForestDiffusion,0.3725141666666667,0.55,6.0,1.0,0.4612570833333334,-0.17748583333333334,2
256
+ m5,m,realtabformer,RealTabFormer,0.5305465,0.55,6.0,1.0,0.54027325,-0.019453500000000012,2
257
+ m5,m,tabbyflow,TabbyFlow,0.5177083333333333,0.55,6.0,1.0,0.5338541666666667,-0.03229166666666672,2
258
+ m5,m,tabddpm,TabDDPM,0.24656183333333334,0.55,6.0,1.0,0.3982809166666667,-0.3034381666666667,2
259
+ m5,m,tabdiff,TabDiff,0.433125,0.55,6.0,1.0,0.4915625,-0.11687500000000006,2
260
+ m5,m,tabpfgen,TabPFGen,0.5599025000000001,1.0,6.0,1.0,0.7799512500000001,-0.4400974999999999,2
261
+ m5,m,tabsyn,TabSyn,0.5177083333333333,0.55,6.0,1.0,0.5338541666666667,-0.03229166666666672,2
262
+ m5,m,tvae,TVAE,0.23296566666666665,0.325,6.0,1.0,0.27898283333333335,-0.09203433333333336,2
263
+ m6,m,real,REAL,1.0,1.0,18.0,8.0,1.0,0.0,2
264
+ m6,m,arf,ARF,0.983634888888889,0.986397,18.0,8.0,0.9850159444444444,-0.002762111111111021,2
265
+ m6,m,bayesnet,BayesNet,0.982812888888889,0.985294125,18.0,8.0,0.9840535069444445,-0.0024812361111110626,2
266
+ m6,m,ctgan,CTGAN,0.30043444444444445,0.32356562499999997,18.0,8.0,0.3120000347222222,-0.02313118055555552,2
267
+ m6,m,forestdiffusion,ForestDiffusion,0.7799243333333333,0.877414875,18.0,8.0,0.8286696041666667,-0.09749054166666671,2
268
+ m6,m,realtabformer,RealTabFormer,0.9512066666666666,0.954722875,18.0,8.0,0.9529647708333333,-0.003516208333333326,2
269
+ m6,m,tabbyflow,TabbyFlow,0.8496732222222223,0.9558823750000001,18.0,8.0,0.9027777986111112,-0.10620915277777776,2
270
+ m6,m,tabddpm,TabDDPM,0.7612968888888889,0.856459,18.0,8.0,0.8088779444444445,-0.09516211111111106,2
271
+ m6,m,tabdiff,TabDiff,0.8888888888888888,1.0,18.0,8.0,0.9444444444444444,-0.11111111111111116,2
272
+ m6,m,tabpfgen,TabPFGen,0.8551784444444445,0.96207575,18.0,8.0,0.9086270972222222,-0.10689730555555554,2
273
+ m6,m,tabsyn,TabSyn,0.882352888888889,0.9926470000000001,18.0,8.0,0.9374999444444445,-0.11029411111111109,2
274
+ m6,m,tvae,TVAE,0.25171644444444446,0.273565625,18.0,8.0,0.2626410347222222,-0.021849180555555514,2
275
+ m7,m,real,REAL,1.0,1.0,18.0,8.0,1.0,0.0,2
276
+ m7,m,arf,ARF,1.0,1.0,18.0,8.0,1.0,0.0,2
277
+ m7,m,bayesnet,BayesNet,1.0,1.0,18.0,8.0,1.0,0.0,2
278
+ m7,m,ctgan,CTGAN,1.0,1.0,18.0,8.0,1.0,0.0,2
279
+ m7,m,forestdiffusion,ForestDiffusion,1.0,1.0,18.0,8.0,1.0,0.0,2
280
+ m7,m,realtabformer,RealTabFormer,1.0,1.0,18.0,8.0,1.0,0.0,2
281
+ m7,m,tabbyflow,TabbyFlow,1.0,1.0,18.0,8.0,1.0,0.0,2
282
+ m7,m,tabddpm,TabDDPM,1.0,1.0,18.0,8.0,1.0,0.0,2
283
+ m7,m,tabdiff,TabDiff,1.0,1.0,18.0,8.0,1.0,0.0,2
284
+ m7,m,tabpfgen,TabPFGen,0.9444444444444444,0.9375,18.0,8.0,0.9409722222222222,0.00694444444444442,2
285
+ m7,m,tabsyn,TabSyn,1.0,1.0,18.0,8.0,1.0,0.0,2
286
+ m7,m,tvae,TVAE,0.9555555555555555,0.95,18.0,8.0,0.9527777777777777,0.005555555555555536,2
287
+ m8,m,real,REAL,1.0,1.0,3.0,8.0,1.0,0.0,2
288
+ m8,m,arf,ARF,0.55,0.43757625,3.0,8.0,0.493788125,0.11242375000000004,2
289
+ m8,m,bayesnet,BayesNet,0.55,0.43753937500000006,3.0,8.0,0.49376968750000005,0.11246062499999998,2
290
+ m8,m,ctgan,CTGAN,0.55,0.45230262500000007,3.0,8.0,0.5011513125,0.09769737499999998,2
291
+ m8,m,forestdiffusion,ForestDiffusion,0.55,0.437566,3.0,8.0,0.493783,0.11243400000000003,2
292
+ m8,m,realtabformer,RealTabFormer,0.55,0.54257575,3.0,8.0,0.546287875,0.007424250000000021,2
293
+ m8,m,tabbyflow,TabbyFlow,0.55,0.43801500000000004,3.0,8.0,0.49400750000000004,0.111985,2
294
+ m8,m,tabddpm,TabDDPM,0.55,0.43815350000000003,3.0,8.0,0.49407675000000006,0.11184650000000002,2
295
+ m8,m,tabdiff,TabDiff,0.55,0.43851875,3.0,8.0,0.49425937500000006,0.11148125000000003,2
296
+ m8,m,tabpfgen,TabPFGen,0.55,0.43754087500000005,3.0,8.0,0.49377043750000005,0.112459125,2
297
+ m8,m,tabsyn,TabSyn,0.55,0.43878275,3.0,8.0,0.494391375,0.11121725000000005,2
298
+ m8,m,tvae,TVAE,0.42500000000000004,0.40690787500000003,3.0,8.0,0.41595393750000004,0.018092125000000014,2
299
+ m9,m,real,REAL,1.0,1.0,16.0,8.0,1.0,0.0,2
300
+ m9,m,arf,ARF,0.875323375,0.875323375,16.0,8.0,0.875323375,0.0,2
301
+ m9,m,bayesnet,BayesNet,0.875,0.875,16.0,8.0,0.875,0.0,2
302
+ m9,m,ctgan,CTGAN,0.875,0.875,16.0,8.0,0.875,0.0,2
303
+ m9,m,forestdiffusion,ForestDiffusion,0.672619125,0.672619125,16.0,8.0,0.672619125,0.0,2
304
+ m9,m,realtabformer,RealTabFormer,0.954241125,0.954241125,16.0,8.0,0.954241125,0.0,2
305
+ m9,m,tabbyflow,TabbyFlow,0.5688865,0.5688865,16.0,8.0,0.5688865,0.0,2
306
+ m9,m,tabddpm,TabDDPM,0.672619125,0.672619125,16.0,8.0,0.672619125,0.0,2
307
+ m9,m,tabdiff,TabDiff,0.669871375,0.6698713749999999,16.0,8.0,0.669871375,1.1102230246251565e-16,2
308
+ m9,m,tabpfgen,TabPFGen,0.754485875,0.754485875,16.0,8.0,0.754485875,0.0,2
309
+ m9,m,tabsyn,TabSyn,0.67006475,0.67006475,16.0,8.0,0.67006475,0.0,2
310
+ m9,m,tvae,TVAE,0.655365875,0.655365875,16.0,8.0,0.655365875,0.0,2
311
+ m10,m,real,REAL,1.0,1.0,18.0,8.0,1.0,0.0,2
312
+ m10,m,arf,ARF,0.7778467777777778,0.875077625,18.0,8.0,0.8264622013888889,-0.0972308472222222,2
313
+ m10,m,bayesnet,BayesNet,0.8890408888888888,0.875171,18.0,8.0,0.8821059444444443,0.013869888888888737,2
314
+ m10,m,ctgan,CTGAN,0.8611111111111112,0.875,18.0,8.0,0.8680555555555556,-0.01388888888888884,2
315
+ m10,m,forestdiffusion,ForestDiffusion,0.7723654444444444,0.868911125,18.0,8.0,0.8206382847222222,-0.09654568055555557,2
316
+ m10,m,realtabformer,RealTabFormer,0.9944444444444444,0.99375,18.0,8.0,0.9940972222222222,0.000694444444444331,2
317
+ m10,m,tabbyflow,TabbyFlow,0.7805592222222222,0.878129125,18.0,8.0,0.8293441736111111,-0.09756990277777777,2
318
+ m10,m,tabddpm,TabDDPM,0.7290848888888889,0.841053875,18.0,8.0,0.7850693819444444,-0.11196898611111106,2
319
+ m10,m,tabdiff,TabDiff,0.7808546666666667,0.8784615,18.0,8.0,0.8296580833333334,-0.09760683333333331,2
320
+ m10,m,tabpfgen,TabPFGen,0.7777777777777778,0.875,18.0,8.0,0.8263888888888888,-0.09722222222222221,2
321
+ m10,m,tabsyn,TabSyn,0.7814814444444445,0.879166625,18.0,8.0,0.8303240347222223,-0.09768518055555553,2
322
+ m10,m,tvae,TVAE,0.8419753333333334,0.875,18.0,8.0,0.8584876666666668,-0.03302466666666659,2
323
+ m11,m,real,REAL,1.0,1.0,4.0,8.0,1.0,0.0,2
324
+ m11,m,arf,ARF,0.43752450000000004,0.381291625,4.0,8.0,0.40940806250000006,0.056232875000000015,2
325
+ m11,m,bayesnet,BayesNet,0.43750425000000004,0.38127025000000003,4.0,8.0,0.40938725000000004,0.056234000000000006,2
326
+ m11,m,ctgan,CTGAN,0.43750425000000004,0.433209,4.0,8.0,0.43535662500000005,0.004295250000000028,2
327
+ m11,m,forestdiffusion,ForestDiffusion,0.43750500000000003,0.381270875,4.0,8.0,0.4093879375,0.056234125000000024,2
328
+ m11,m,realtabformer,RealTabFormer,0.55,0.5452693750000001,4.0,8.0,0.5476346875,0.004730624999999988,2
329
+ m11,m,tabbyflow,TabbyFlow,0.43796750000000007,0.381726,4.0,8.0,0.40984675000000004,0.056241500000000055,2
330
+ m11,m,tabddpm,TabDDPM,0.437882,0.38174537500000005,4.0,8.0,0.4098136875,0.05613662499999994,2
331
+ m11,m,tabdiff,TabDiff,0.437906,0.38180925000000004,4.0,8.0,0.409857625,0.05609674999999997,2
332
+ m11,m,tabpfgen,TabPFGen,0.437508,0.38127925,4.0,8.0,0.409393625,0.056228749999999994,2
333
+ m11,m,tabsyn,TabSyn,0.4379155,0.38189075000000006,4.0,8.0,0.40990312500000003,0.056024749999999957,2
334
+ m11,m,tvae,TVAE,0.43750425000000004,0.40704137500000004,4.0,8.0,0.42227281250000004,0.030462875,2
335
+ m12,m,real,REAL,1.0,1.0,18.0,8.0,1.0,0.0,2
336
+ m12,m,arf,ARF,0.5327668333333333,0.85,18.0,8.0,0.6913834166666666,-0.3172331666666667,2
337
+ m12,m,bayesnet,BayesNet,0.6093189999999999,0.85625,18.0,8.0,0.7327845,-0.246931,2
338
+ m12,m,ctgan,CTGAN,0.45042400000000005,0.880952375,18.0,8.0,0.6656881875,-0.43052837499999996,2
339
+ m12,m,forestdiffusion,ForestDiffusion,0.4291938888888889,0.7375,18.0,8.0,0.5833469444444445,-0.30830611111111117,2
340
+ m12,m,realtabformer,RealTabFormer,0.9454102222222223,0.982142875,18.0,8.0,0.9637765486111112,-0.03673265277777771,2
341
+ m12,m,tabbyflow,TabbyFlow,0.6111111111111112,0.81041675,18.0,8.0,0.7107639305555555,-0.19930563888888886,2
342
+ m12,m,tabdiff,TabDiff,0.6045751111111112,0.866666625,18.0,8.0,0.7356208680555556,-0.26209151388888885,2
343
+ m12,m,tabpfgen,TabPFGen,0.5832312222222222,0.85,18.0,8.0,0.716615611111111,-0.26676877777777774,2
344
+ m12,m,tabsyn,TabSyn,0.5915032222222222,0.791666625,18.0,8.0,0.6915849236111111,-0.20016340277777778,2
345
+ m12,m,tvae,TVAE,0.4636686666666667,0.797619,18.0,8.0,0.6306438333333333,-0.3339503333333333,2
346
+ n1,n,real,REAL,1.0,1.0,16.0,7.0,1.0,0.0,2
347
+ n1,n,arf,ARF,1.0,1.0,16.0,7.0,1.0,0.0,2
348
+ n1,n,bayesnet,BayesNet,1.0,1.0,16.0,7.0,1.0,0.0,2
349
+ n1,n,ctgan,CTGAN,1.0,1.0,16.0,7.0,1.0,0.0,2
350
+ n1,n,forestdiffusion,ForestDiffusion,1.0,1.0,16.0,7.0,1.0,0.0,2
351
+ n1,n,realtabformer,RealTabFormer,1.0,1.0,16.0,7.0,1.0,0.0,2
352
+ n1,n,tabbyflow,TabbyFlow,0.5,0.5,16.0,7.0,0.5,0.0,2
353
+ n1,n,tabddpm,TabDDPM,1.0,1.0,16.0,7.0,1.0,0.0,2
354
+ n1,n,tabdiff,TabDiff,1.0,1.0,16.0,7.0,1.0,0.0,2
355
+ n1,n,tabpfgen,TabPFGen,1.0,1.0,16.0,7.0,1.0,0.0,2
356
+ n1,n,tabsyn,TabSyn,1.0,1.0,16.0,7.0,1.0,0.0,2
357
+ n1,n,tvae,TVAE,1.0,1.0,16.0,7.0,1.0,0.0,2
358
+ n2,n,real,REAL,1.0,1.0,16.0,7.0,1.0,0.0,2
359
+ n2,n,arf,ARF,1.0,1.0,16.0,7.0,1.0,0.0,2
360
+ n2,n,bayesnet,BayesNet,1.0,1.0,16.0,7.0,1.0,0.0,2
361
+ n2,n,ctgan,CTGAN,1.0,1.0,16.0,7.0,1.0,0.0,2
362
+ n2,n,forestdiffusion,ForestDiffusion,0.25,0.25,16.0,7.0,0.25,0.0,2
363
+ n2,n,realtabformer,RealTabFormer,1.0,1.0,16.0,7.0,1.0,0.0,2
364
+ n2,n,tabbyflow,TabbyFlow,0.25,0.25,16.0,7.0,0.25,0.0,2
365
+ n2,n,tabddpm,TabDDPM,0.25,0.25,16.0,7.0,0.25,0.0,2
366
+ n2,n,tabdiff,TabDiff,0.25,0.25,16.0,7.0,0.25,0.0,2
367
+ n2,n,tabpfgen,TabPFGen,1.0,1.0,16.0,7.0,1.0,0.0,2
368
+ n2,n,tvae,TVAE,1.0,1.0,16.0,7.0,1.0,0.0,2
369
+ n3,n,real,REAL,1.0,1.0,16.0,7.0,1.0,0.0,2
370
+ n3,n,arf,ARF,0.21452225000000003,0.23050957142857142,16.0,7.0,0.22251591071428573,-0.0159873214285714,2
371
+ n3,n,bayesnet,BayesNet,0.2138785,0.22986242857142858,16.0,7.0,0.22187046428571428,-0.01598392857142858,2
372
+ n3,n,ctgan,CTGAN,0.11745,0.11965842857142857,16.0,7.0,0.11855421428571428,-0.0022084285714285695,2
373
+ n3,n,forestdiffusion,ForestDiffusion,0.16566575,0.1747617142857143,16.0,7.0,0.17021373214285715,-0.009095964285714297,2
374
+ n3,n,realtabformer,RealTabFormer,0.497819,0.5083114285714286,16.0,7.0,0.5030652142857144,-0.010492428571428625,2
375
+ n3,n,tabbyflow,TabbyFlow,0.17318962499999999,0.1817647142857143,16.0,7.0,0.17747716964285715,-0.008575089285714321,2
376
+ n3,n,tabddpm,TabDDPM,0.16868775,0.177584,16.0,7.0,0.173135875,-0.008896249999999994,2
377
+ n3,n,tabdiff,TabDiff,0.173040625,0.18163314285714285,16.0,7.0,0.17733688392857144,-0.00859251785714285,2
378
+ n3,n,tabpfgen,TabPFGen,0.149620125,0.15641914285714284,16.0,7.0,0.15301963392857143,-0.006799017857142847,2
379
+ n3,n,tabsyn,TabSyn,0.22186075000000002,0.23744657142857142,16.0,7.0,0.22965366071428572,-0.0155858214285714,2
380
+ n3,n,tvae,TVAE,0.11745,0.11965842857142857,16.0,7.0,0.11855421428571428,-0.0022084285714285695,2
381
+ n4,n,real,REAL,1.0,1.0,10.0,8.0,1.0,0.0,2
382
+ n4,n,arf,ARF,0.3657007,0.42132275,10.0,8.0,0.393511725,-0.055622050000000034,2
383
+ n4,n,bayesnet,BayesNet,0.36647660000000004,0.420376375,10.0,8.0,0.39342648750000003,-0.05389977499999998,2
384
+ n4,n,ctgan,CTGAN,0.1996016,0.211782625,10.0,8.0,0.2056921125,-0.012181025000000012,2
385
+ n4,n,forestdiffusion,ForestDiffusion,0.3669676,0.42078787500000003,10.0,8.0,0.3938777375,-0.05382027500000003,2
386
+ n4,n,realtabformer,RealTabFormer,0.4777089,0.50990725,10.0,8.0,0.493808075,-0.03219835000000004,2
387
+ n4,n,tabbyflow,TabbyFlow,0.3736602,0.42407625000000004,10.0,8.0,0.398868225,-0.050416050000000046,2
388
+ n4,n,tabddpm,TabDDPM,0.21060120000000002,0.23482887500000002,10.0,8.0,0.22271503750000002,-0.024227675000000004,2
389
+ n4,n,tabdiff,TabDiff,0.37236220000000003,0.42470675,10.0,8.0,0.39853447500000005,-0.05234454999999999,2
390
+ n4,n,tabpfgen,TabPFGen,0.3665061,0.437580125,10.0,8.0,0.4020431125,-0.07107402499999999,2
391
+ n4,n,tvae,TVAE,0.23904200000000003,0.26105612499999997,10.0,8.0,0.25004906250000003,-0.02201412499999994,2
392
+ n5,n,real,REAL,1.0,1.0,18.0,8.0,1.0,0.0,2
393
+ n5,n,arf,ARF,0.33787033333333333,0.37822374999999997,18.0,8.0,0.3580470416666667,-0.04035341666666664,2
394
+ n5,n,bayesnet,BayesNet,0.5077209444444445,0.473076375,18.0,8.0,0.49039865972222224,0.034644569444444495,2
395
+ n5,n,ctgan,CTGAN,0.43829399999999996,0.434040375,18.0,8.0,0.43616718749999994,0.004253624999999983,2
396
+ n5,n,forestdiffusion,ForestDiffusion,0.3333916111111111,0.375,18.0,8.0,0.3541958055555555,-0.0416083888888889,2
397
+ n5,n,realtabformer,RealTabFormer,0.5628286111111112,0.49233775,18.0,8.0,0.5275831805555555,0.07049086111111114,2
398
+ n5,n,tabbyflow,TabbyFlow,0.3233216666666666,0.34143525,18.0,8.0,0.33237845833333335,-0.018113583333333405,2
399
+ n5,n,tabddpm,TabDDPM,0.13962872222222222,0.12887800000000002,18.0,8.0,0.13425336111111114,0.010750722222222203,2
400
+ n5,n,tabdiff,TabDiff,0.3380756111111111,0.376271625,18.0,8.0,0.3571736180555556,-0.03819601388888888,2
401
+ n5,n,tabpfgen,TabPFGen,0.3333433333333333,0.375,18.0,8.0,0.35417166666666666,-0.041656666666666675,2
402
+ n5,n,tvae,TVAE,0.43785544444444446,0.407008,18.0,8.0,0.42243172222222225,0.030847444444444483,2
403
+ n6,n,real,REAL,1.0,1.0,2.0,7.0,1.0,0.0,2
404
+ n6,n,arf,ARF,0.55,0.55,2.0,7.0,0.55,0.0,2
405
+ n6,n,bayesnet,BayesNet,0.55,0.55,2.0,7.0,0.55,0.0,2
406
+ n6,n,ctgan,CTGAN,0.2125,0.2125,2.0,7.0,0.2125,0.0,2
407
+ n6,n,forestdiffusion,ForestDiffusion,0.55,0.55,2.0,7.0,0.55,0.0,2
408
+ n6,n,realtabformer,RealTabFormer,0.55,0.55,2.0,7.0,0.55,0.0,2
409
+ n6,n,tabbyflow,TabbyFlow,0.55,0.55,2.0,7.0,0.55,0.0,2
410
+ n6,n,tabddpm,TabDDPM,0.55,0.55,2.0,7.0,0.55,0.0,2
411
+ n6,n,tabdiff,TabDiff,0.55,0.55,2.0,7.0,0.55,0.0,2
412
+ n6,n,tabpfgen,TabPFGen,0.55,0.55,2.0,7.0,0.55,0.0,2
413
+ n6,n,tabsyn,TabSyn,0.55,0.55,2.0,7.0,0.55,0.0,2
414
+ n6,n,tvae,TVAE,0.2125,0.2125,2.0,7.0,0.2125,0.0,2
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419
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420
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+ n9,n,realtabformer,RealTabFormer,0.0,0.0,18.0,8.0,0.0,0.0,2
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+ n9,n,tabbyflow,TabbyFlow,0.0,0.0,18.0,8.0,0.0,0.0,2
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+ n9,n,tabddpm,TabDDPM,0.0,0.0,18.0,8.0,0.0,0.0,2
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+ n9,n,tabdiff,TabDiff,0.0,0.0,18.0,8.0,0.0,0.0,2
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+ n9,n,tabpfgen,TabPFGen,0.0,0.0,18.0,8.0,0.0,0.0,2
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+ n10,n,arf,ARF,1.0,1.0,16.0,7.0,1.0,0.0,2
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+ n10,n,bayesnet,BayesNet,1.0,1.0,16.0,7.0,1.0,0.0,2
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+ n10,n,ctgan,CTGAN,1.0,1.0,16.0,7.0,1.0,0.0,2
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+ n10,n,forestdiffusion,ForestDiffusion,1.0,1.0,16.0,7.0,1.0,0.0,2
452
+ n10,n,realtabformer,RealTabFormer,1.0,1.0,16.0,7.0,1.0,0.0,2
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+ n10,n,tabddpm,TabDDPM,1.0,1.0,16.0,7.0,1.0,0.0,2
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+ n10,n,tabdiff,TabDiff,1.0,1.0,16.0,7.0,1.0,0.0,2
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+ n10,n,tabpfgen,TabPFGen,1.0,1.0,16.0,7.0,1.0,0.0,2
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+ n11,n,real,REAL,1.0,1.0,16.0,7.0,1.0,0.0,2
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+ n11,n,arf,ARF,1.0,1.0,16.0,7.0,1.0,0.0,2
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+ n11,n,bayesnet,BayesNet,1.0,1.0,16.0,7.0,1.0,0.0,2
461
+ n11,n,ctgan,CTGAN,1.0,1.0,16.0,7.0,1.0,0.0,2
462
+ n11,n,forestdiffusion,ForestDiffusion,1.0,1.0,16.0,7.0,1.0,0.0,2
463
+ n11,n,realtabformer,RealTabFormer,1.0,1.0,16.0,7.0,1.0,0.0,2
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+ n11,n,tabbyflow,TabbyFlow,1.0,1.0,16.0,7.0,1.0,0.0,2
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+ n11,n,tabddpm,TabDDPM,1.0,1.0,16.0,7.0,1.0,0.0,2
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+ n11,n,tabdiff,TabDiff,1.0,1.0,16.0,7.0,1.0,0.0,2
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+ n11,n,tabpfgen,TabPFGen,1.0,1.0,16.0,7.0,1.0,0.0,2
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+ n11,n,tabsyn,TabSyn,1.0,1.0,16.0,7.0,1.0,0.0,2
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+ n12,n,real,REAL,1.0,1.0,14.0,7.0,1.0,0.0,2
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+ n12,n,tabdiff,TabDiff,0.07142857142857142,0.07142857142857142,14.0,7.0,0.07142857142857142,0.0,2
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+ n12,n,tabpfgen,TabPFGen,0.07142857142857142,0.07142857142857142,14.0,7.0,0.07142857142857142,0.0,2
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+ n14,n,real,REAL,1.0,,1.0,,1.0,,1
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+ n14,n,arf,ARF,0.007686,,1.0,,0.007686,,1
483
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+ n14,n,ctgan,CTGAN,0.0,,1.0,,0.0,,1
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+ n15,n,tabdiff,TabDiff,0.8888888888888888,1.0,18.0,8.0,0.9444444444444444,-0.11111111111111116,2
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+ n15,n,tabpfgen,TabPFGen,0.8283951111111111,1.0,18.0,8.0,0.9141975555555555,-0.17160488888888892,2
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evaluation/query_family/subgroup/data/dataset_model_subitems.csv CHANGED
The diff for this file is too large to render. See raw diff
 
evaluation/query_family/subgroup/data/dataset_summary.csv CHANGED
@@ -1,49 +1,50 @@
1
- dataset_id,dataset_prefix,model_count,internal_profile_stability,subgroup_size_stability,subgroup_structure_score,profile_minus_size,score_std_across_models
2
- c2,c,12,0.5945,0.568874,0.581687,0.025626,0.490912
3
- c3,c,11,0.909091,0.909091,0.909091,0.0,0.301511
4
- c4,c,12,0.981667,0.976852,0.979259,0.004815,0.016896
5
- c5,c,11,0.97204,0.926773,0.949407,0.045268,0.035823
6
- c6,c,10,0.928352,0.883346,0.905849,0.045006,0.091722
7
- c7,c,12,0.953035,0.953443,0.953239,-0.000408,0.04744
8
- c8,c,12,0.697222,0.69765,0.697436,-0.000427,0.426337
9
- c9,c,12,0.490472,0.538721,0.514597,-0.048249,0.29243
10
- c10,c,11,0.344992,0.332394,0.338693,0.012598,0.463817
11
- c11,c,10,0.597333,0.587374,0.592354,0.00996,0.509899
12
- c12,c,7,0.917293,0.914835,0.916064,0.002458,0.182193
13
- c14,c,7,0.674487,0.652788,0.663637,0.021699,0.330704
14
- c15,c,6,0.673336,0.514416,0.593876,0.158921,0.368944
15
- c16,c,7,0.579062,0.569902,0.574482,0.00916,0.325693
16
- c17,c,8,0.673709,0.654727,0.664218,0.018982,0.290637
17
- c18,c,5,0.456377,0.567419,0.511898,-0.111042,0.350348
18
- c19,c,8,0.537942,0.592991,0.565467,-0.055049,0.387446
19
- c20,c,11,0.370248,0.447066,0.408657,-0.076818,0.433734
20
- m1,m,11,0.875805,0.96875,0.922278,-0.092945,0.112627
21
- m2,m,9,0.834233,0.840112,0.837172,-0.005879,0.168701
22
- m4,m,12,0.770455,0.805556,0.788005,-0.035101,0.287364
23
- m5,m,12,0.652107,0.73639,0.694248,-0.084282,0.294143
24
- m6,m,12,0.590078,0.494887,0.542483,0.095191,0.199533
25
- m7,m,12,0.405443,0.87056,0.638002,-0.465117,0.196685
26
- m8,m,11,0.849836,0.92397,0.886903,-0.074134,0.131211
27
- m9,m,10,0.626326,0.750486,0.688406,-0.124161,0.279239
28
- m10,m,11,0.611798,0.712959,0.662378,-0.10116,0.30743
29
- m11,m,10,0.661019,0.602078,0.631549,0.05894,0.236727
30
- m12,m,8,0.705266,0.816397,0.760831,-0.111131,0.222721
31
- n1,n,11,0.818182,0.818182,0.818182,0.0,0.40452
32
- n2,n,12,0.346273,,0.346273,,0.450551
33
- n3,n,12,0.202566,0.275515,0.23904,-0.072949,0.333666
34
- n4,n,10,0.265389,0.311479,0.288434,-0.046089,0.291227
35
- n5,n,11,0.300544,0.397524,0.349034,-0.096981,0.279767
36
- n6,n,12,0.75,0.75,0.75,0.0,0.452267
37
- n7,n,11,0.879127,0.85448,0.866803,0.024647,0.290831
38
- n8,n,8,0.206189,0.440741,0.323465,-0.234552,0.285176
39
- n9,n,11,0.626019,0.613701,0.61986,0.012319,0.321607
40
- n10,n,11,0.778929,0.74153,0.76023,0.037399,0.377449
41
- n11,n,11,0.818182,0.818182,0.818182,0.0,0.40452
42
- n12,n,10,0.272325,0.529799,0.401062,-0.257474,0.329532
43
- n14,n,9,0.254232,0.210494,0.232363,0.043739,0.293788
44
- n15,n,9,0.609676,0.616886,0.613281,-0.00721,0.450179
45
- n16,n,7,0.5,0.571429,0.535714,-0.071429,0.50885
46
- n17,n,9,0.620214,,0.620214,,0.262929
47
- n18,n,5,0.329052,0.523554,0.426303,-0.194501,0.356921
48
- n19,n,7,0.511785,0.386729,0.449257,0.125056,0.305945
49
- n20,n,9,0.125104,,0.125104,,0.330263
 
 
1
+ dataset_id,dataset_prefix,model_count,internal_profile_stability,subgroup_size_stability,subgroup_structure_score,profile_minus_size,score_std_across_models
2
+ c2,c,12,0.9575,0.928021,0.94276,0.029479,0.069912
3
+ c3,c,12,1.0,1.0,1.0,0.0,0.0
4
+ c4,c,12,1.0,0.990625,0.995312,0.009375,0.006033
5
+ c5,c,12,0.967407,0.753704,0.860556,0.213704,0.048323
6
+ c6,c,12,0.587216,0.587525,0.587371,-0.000309,0.129955
7
+ c7,c,12,0.976042,0.937421,0.956731,0.03862,0.02621
8
+ c8,c,12,0.972222,0.996528,0.984375,-0.024306,0.020111
9
+ c9,c,12,0.356036,0.378755,0.367396,-0.022719,0.28981
10
+ c10,c,11,0.996892,0.996503,0.996698,0.000389,0.010952
11
+ c11,c,12,0.995169,0.952466,0.973818,0.042703,0.017143
12
+ c12,c,9,0.916667,0.944444,0.930556,-0.027778,0.147314
13
+ c13,c,12,0.741551,0.843434,0.792493,-0.101883,0.324829
14
+ c14,c,12,0.912037,0.886336,0.899187,0.025701,0.188543
15
+ c15,c,11,0.749952,0.811385,0.780669,-0.061433,0.132501
16
+ c16,c,10,0.677557,0.673836,0.675696,0.003721,0.219613
17
+ c17,c,11,0.662251,0.662251,0.662251,0.0,0.207097
18
+ c18,c,8,0.517071,0.703126,0.610099,-0.186055,0.212588
19
+ c19,c,11,0.840909,0.837662,0.839286,0.003247,0.155036
20
+ c20,c,11,0.985124,0.972727,0.978926,0.012397,0.069896
21
+ m1,m,12,0.960031,0.882687,0.921359,0.077344,0.093026
22
+ m2,m,11,0.459681,0.590909,0.525295,-0.131228,0.158037
23
+ m4,m,12,0.956349,0.956349,0.956349,0.0,0.091841
24
+ m5,m,12,0.482099,0.60625,0.544174,-0.124151,0.186787
25
+ m6,m,12,0.790593,0.847335,0.818964,-0.056742,0.255329
26
+ m7,m,12,0.991667,0.990625,0.991146,0.001042,0.020831
27
+ m8,m,12,0.577083,0.492123,0.534603,0.08496,0.14928
28
+ m9,m,12,0.77029,0.77029,0.77029,0.0,0.139086
29
+ m10,m,12,0.832212,0.892893,0.862553,-0.060682,0.067568
30
+ m11,m,12,0.493893,0.45315,0.473522,0.040743,0.170405
31
+ m12,m,11,0.620109,0.856656,0.738383,-0.236546,0.128782
32
+ n1,n,12,0.958333,0.958333,0.958333,0.0,0.144338
33
+ n2,n,11,0.727273,0.727273,0.727273,0.0,0.378394
34
+ n3,n,12,0.267765,0.276467,0.272116,-0.008702,0.250347
35
+ n4,n,11,0.394421,0.433311,0.413866,-0.038891,0.214123
36
+ n5,n,11,0.43203,0.434661,0.433346,-0.002631,0.213779
37
+ n6,n,12,0.53125,0.53125,0.53125,0.0,0.196814
38
+ n7,n,11,0.588133,0.590909,0.589521,-0.002776,0.136217
39
+ n8,n,10,0.569206,0.642238,0.605722,-0.073031,0.160939
40
+ n9,n,11,0.090909,0.090909,0.090909,0.0,0.301511
41
+ n10,n,11,1.0,1.0,1.0,0.0,0.0
42
+ n11,n,12,1.0,1.0,1.0,0.0,0.0
43
+ n12,n,11,0.404465,0.404465,0.404465,-0.0,0.435138
44
+ n14,n,11,0.104628,,0.104628,,0.298358
45
+ n15,n,12,0.748198,0.849653,0.798925,-0.101455,0.2828
46
+ n16,n,12,1.0,1.0,1.0,0.0,0.0
47
+ n17,n,11,0.336317,0.372045,0.354181,-0.035728,0.345937
48
+ n18,n,11,0.25048,0.232477,0.241478,0.018003,0.254008
49
+ n19,n,12,0.412123,0.294865,0.353494,0.117258,0.346815
50
+ n20,n,11,0.160951,0.153941,0.157446,0.00701,0.354575
evaluation/query_family/subgroup/data/duplicate_asset_audit.csv CHANGED
@@ -1,38 +1 @@
1
- dataset_id,model_id,kept_asset_key,dropped_asset_key,kept_run_id,dropped_run_id
2
- c2,arf,c2__rtx_5090__arf__arf-c2-20260501_224900__arf-c2-1382-20260501_224905,c2__rtx_pro_6000__arf__arf-c2-20260422_055912,arf-c2-20260501_224900__arf-c2-1382-20260501_224905,arf-c2-20260422_055912
3
- c2,bayesnet,c2__rtx_5090__bayesnet__bayesnet-c2-20260501_224919__bayesnet-c2-1382-20260501_224928,c2__rtx_pro_6000__bayesnet__bayesnet-c2-20260422_060152,bayesnet-c2-20260501_224919__bayesnet-c2-1382-20260501_224928,bayesnet-c2-20260422_060152
4
- c2,ctgan,c2__rtx_5090__ctgan__ctgan-c2-20260504_152521__ctgan-c2-1382-20260504_152602,c2__rtx_pro_6000__ctgan__ctgan-c2-20260414_051434,ctgan-c2-20260504_152521__ctgan-c2-1382-20260504_152602,ctgan-c2-20260414_051434
5
- c2,forestdiffusion,c2__rtx_5090__forestdiffusion__forest-c2-20260501_180312__forest-c2-1382-20260501_180507,c2__rtx_pro_6000__forestdiffusion__forest-c2-20260414_032137,forest-c2-20260501_180312__forest-c2-1382-20260501_180507,forest-c2-20260414_032137
6
- c2,realtabformer,c2__rtx_5090__realtabformer__rtf-c2-20260501_033610__rtf-c2-1382-20260501_034209,c2__rtx_pro_6000__realtabformer__rtf-c2-20260414_051904,rtf-c2-20260501_033610__rtf-c2-1382-20260501_034209,rtf-c2-20260414_051904
7
- c2,tabbyflow,c2__rtx_5090__tabbyflow__tabbyflow-c2-20260501_052813__tabbyflow-c2-1382-20260501_053427,c2__rtx_pro_6000__tabbyflow__tabbyflow-c2-20260414_034222,tabbyflow-c2-20260501_052813__tabbyflow-c2-1382-20260501_053427,tabbyflow-c2-20260414_034222
8
- c2,tabddpm,c2__rtx_5090__tabddpm__tabddpm-c2-20260501_053445__tabddpm-c2-1382-20260501_053541,c2__rtx_pro_6000__tabddpm__tabddpm-c2-20260422_210001,tabddpm-c2-20260501_053445__tabddpm-c2-1382-20260501_053541,tabddpm-c2-20260422_210001
9
- c2,tabdiff,c2__rtx_5090__tabdiff__tabdiff-c2-20260501_053602__tabdiff-c2-1382-20260501_054253,c2__rtx_pro_6000__tabdiff__tabdiff-c2-20260414_034133,tabdiff-c2-20260501_053602__tabdiff-c2-1382-20260501_054253,tabdiff-c2-20260414_034133
10
- c2,tabpfgen,c2__rtx_5090__tabpfgen__tabpfgen-c2-20260501_054310__tabpfgen-c2-1382-20260501_054310,c2__rtx_pro_6000__tabpfgen__tabpfgen-c2-20260422_200030,tabpfgen-c2-20260501_054310__tabpfgen-c2-1382-20260501_054310,tabpfgen-c2-20260422_200030
11
- c2,tabsyn,c2__rtx_5090__tabsyn__tabsyn-c2-20260501_054336__tabsyn-c2-1382-20260501_060640,c2__rtx_pro_6000__tabsyn__tabsyn-c2-20260420_233446,tabsyn-c2-20260501_054336__tabsyn-c2-1382-20260501_060640,tabsyn-c2-20260420_233446
12
- c2,tvae,c2__rtx_5090__tvae__tvae-c2-20260501_060652__tvae-c2-1382-20260501_060709,c2__rtx_pro_6000__tvae__tvae-c2-20260414_051505,tvae-c2-20260501_060652__tvae-c2-1382-20260501_060709,tvae-c2-20260414_051505
13
- c3,tabsyn,c3__rtx_5090__tabsyn__tabsyn-c3-20260422_031342__tabsyn-c3-2551-20260422_035033,c3__rtx_pro_6000__tabsyn__tabsyn-c3-20260420_233446,tabsyn-c3-20260422_031342__tabsyn-c3-2551-20260422_035033,tabsyn-c3-20260420_233446
14
- c4,tabsyn,c4__rtx_5090__tabsyn__tabsyn-c4-20260422_035041__tabsyn-c4-2557-20260422_043125,c4__rtx_pro_6000__tabsyn__tabsyn-c4-20260420_233446,tabsyn-c4-20260422_035041__tabsyn-c4-2557-20260422_043125,tabsyn-c4-20260420_233446
15
- c5,tabsyn,c5__rtx_5090__tabsyn__tabsyn-c5-20260422_043132__tabsyn-c5-6732-20260422_051543,c5__rtx_pro_6000__tabsyn__tabsyn-c5-20260420_233446,tabsyn-c5-20260422_043132__tabsyn-c5-6732-20260422_051543,tabsyn-c5-20260420_233446
16
- c6,tabsyn,c6__rtx_5090__tabsyn__tabsyn-c6-20260422_051551__tabsyn-c6-7636-20260422_055242,c6__rtx_pro_6000__tabsyn__tabsyn-c6-20260420_233446,tabsyn-c6-20260422_051551__tabsyn-c6-7636-20260422_055242,tabsyn-c6-20260420_233446
17
- c7,tabsyn,c7__rtx_5090__tabsyn__tabsyn-c7-20260422_055250__tabsyn-c7-10368-20260422_063105,c7__rtx_pro_6000__tabsyn__tabsyn-c7-20260420_233446,tabsyn-c7-20260422_055250__tabsyn-c7-10368-20260422_063105,tabsyn-c7-20260420_233446
18
- c8,tabsyn,c8__rtx_5090__tabsyn__tabsyn-c8-20260422_063113__tabsyn-c8-8844-20260422_071553,c8__rtx_pro_6000__tabsyn__tabsyn-c8-20260420_233446,tabsyn-c8-20260422_063113__tabsyn-c8-8844-20260422_071553,tabsyn-c8-20260420_233446
19
- c9,tabsyn,c9__rtx_5090__tabsyn__tabsyn-c9-20260422_071602__tabsyn-c9-26215-20260422_075912,c9__rtx_pro_6000__tabsyn__tabsyn-c9-20260420_233446,tabsyn-c9-20260422_071602__tabsyn-c9-26215-20260422_075912,tabsyn-c9-20260420_233446
20
- m1,tabsyn,m1__rtx_5090__tabsyn__tabsyn-m1-20260426_023700__tabsyn-m1-1200-20260426_030635,m1__rtx_pro_6000__tabsyn__tabsyn-m1-20260421_023648,tabsyn-m1-20260426_023700__tabsyn-m1-1200-20260426_030635,tabsyn-m1-20260421_023648
21
- m2,tabsyn,m2__rtx_5090__tabsyn__tabsyn-m2-20260426_023700__tabsyn-m2-46873-20260426_034933,m2__rtx_pro_6000__tabsyn__tabsyn-m2-20260421_023648,tabsyn-m2-20260426_023700__tabsyn-m2-46873-20260426_034933,tabsyn-m2-20260421_023648
22
- m4,arf,m4__rtx_5090__arf__arf-m4-20260501_224942__arf-m4-2217-20260501_224949,m4__rtx_pro_6000__arf__arf-m4-20260321_063209,arf-m4-20260501_224942__arf-m4-2217-20260501_224949,arf-m4-20260321_063209
23
- m4,bayesnet,m4__rtx_5090__bayesnet__bayesnet-m4-20260501_224959__bayesnet-m4-2217-20260501_225008,m4__rtx_pro_6000__bayesnet__bayesnet-m4-20260321_061211,bayesnet-m4-20260501_224959__bayesnet-m4-2217-20260501_225008,bayesnet-m4-20260321_061211
24
- m4,ctgan,m4__rtx_5090__ctgan__ctgan-m4-20260501_005319__ctgan-m4-2217-20260501_005357,m4__rtx_pro_6000__ctgan__ctgan-m4-20260321_063700,ctgan-m4-20260501_005319__ctgan-m4-2217-20260501_005357,ctgan-m4-20260321_063700
25
- m4,realtabformer,m4__rtx_5090__realtabformer__rtf-m4-20260501_033611__rtf-m4-2217-20260501_034506,m4__rtx_pro_6000__realtabformer__rtf-m4-20260321_172613,rtf-m4-20260501_033611__rtf-m4-2217-20260501_034506,rtf-m4-20260321_172613
26
- m4,tabddpm,m4__rtx_5090__tabddpm__tabddpm-m4-20260501_002012__tabddpm-m4-2217-20260501_002103,m4__rtx_pro_6000__tabddpm__tabddpm-m4-20260424_033725,tabddpm-m4-20260501_002012__tabddpm-m4-2217-20260501_002103,tabddpm-m4-20260424_033725
27
- m4,tabpfgen,m4__rtx_5090__tabpfgen__tabpfgen-m4-20260501_005403__tabpfgen-m4-2217-20260501_005403,m4__rtx_pro_6000__tabpfgen__m4-migrated-20260422_193053,tabpfgen-m4-20260501_005403__tabpfgen-m4-2217-20260501_005403,m4-migrated-20260422_193053
28
- m4,tabsyn,m4__rtx_5090__tabsyn__tabsyn-m4-20260426_023700__tabsyn-m4-2217-20260426_030908,m4__rtx_pro_6000__tabsyn__tabsyn-m4-20260421_023648,tabsyn-m4-20260426_023700__tabsyn-m4-2217-20260426_030908,tabsyn-m4-20260421_023648
29
- m4,tvae,m4__rtx_5090__tvae__tvae-m4-20260501_055812__tvae-m4-2217-20260501_055834,m4__rtx_pro_6000__tvae__tvae-m4-20260321_065714,tvae-m4-20260501_055812__tvae-m4-2217-20260501_055834,tvae-m4-20260321_065714
30
- n1,tabsyn,n1__rtx_5090__tabsyn__tabsyn-n1-20260424_081230__tabsyn-n1-3680-20260424_084526,n1__rtx_pro_6000__tabsyn__tabsyn-n1-20260413_054310,tabsyn-n1-20260424_081230__tabsyn-n1-3680-20260424_084526,tabsyn-n1-20260413_054310
31
- n3,arf,n3__rtx_5090__arf__arf-n3-20260501_225023__arf-n3-3918-20260501_225052,n3__rtx_pro_6000__arf__arf-n3-20260422_055912,arf-n3-20260501_225023__arf-n3-3918-20260501_225052,arf-n3-20260422_055912
32
- n3,bayesnet,n3__rtx_5090__bayesnet__bayesnet-n3-20260501_225103__bayesnet-n3-3918-20260501_225112,n3__rtx_pro_6000__bayesnet__bayesnet-n3-20260422_060152,bayesnet-n3-20260501_225103__bayesnet-n3-3918-20260501_225112,bayesnet-n3-20260422_060152
33
- n3,ctgan,n3__rtx_5090__ctgan__ctgan-n3-20260501_005113__ctgan-n3-3918-20260501_005206,n3__rtx_pro_6000__ctgan__ctgan-n3-20260422_025941,ctgan-n3-20260501_005113__ctgan-n3-3918-20260501_005206,ctgan-n3-20260422_025941
34
- n3,realtabformer,n3__rtx_5090__realtabformer__rtf-n3-20260501_010320__rtf-n3-3918-20260501_011818,n3__rtx_pro_6000__realtabformer__rtf-n3-20260330_160436,rtf-n3-20260501_010320__rtf-n3-3918-20260501_011818,rtf-n3-20260330_160436
35
- n3,tabddpm,n3__rtx_5090__tabddpm__tabddpm-n3-20260501_002012__tabddpm-n3-3918-20260501_002035,n3__rtx_pro_6000__tabddpm__tabddpm-n3-20260424_033725,tabddpm-n3-20260501_002012__tabddpm-n3-3918-20260501_002035,tabddpm-n3-20260424_033725
36
- n3,tabpfgen,n3__rtx_5090__tabpfgen__tabpfgen-n3-20260501_005212__tabpfgen-n3-3918-20260501_005212,n3__rtx_pro_6000__tabpfgen__tabpfgen-n3-20260422_200720,tabpfgen-n3-20260501_005212__tabpfgen-n3-3918-20260501_005212,tabpfgen-n3-20260422_200720
37
- n3,tvae,n3__rtx_5090__tvae__tvae-n3-20260501_060320__tvae-n3-3918-20260501_060403,n3__rtx_pro_6000__tvae__tvae-n3-20260419_194337,tvae-n3-20260501_060320__tvae-n3-3918-20260501_060403,tvae-n3-20260419_194337
38
- c11,tabsyn,c11__rtx_5090__tabsyn__tabsyn-c11-20260422_165523__tabsyn-c11-54045-20260422_185444,c11__rtx_pro_6000__tabsyn__tabsyn-c11-20260420_233446,tabsyn-c11-20260422_165523__tabsyn-c11-54045-20260422_185444,tabsyn-c11-20260420_233446
 
1
+
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
evaluation/query_family/subgroup/data/model_subitem_heatmap.csv CHANGED
@@ -1,4 +1,4 @@
1
- subitem_id,subitem_label,arf,bayesnet,ctgan,forestdiffusion,realtabformer,tabbyflow,tabddpm,tabdiff,tabpfgen,tabsyn,tvae
2
- internal_profile_stability,Internal profile stability,0.676563,0.679959,0.62376,0.261531,0.815889,0.573997,0.324354,0.675925,0.636702,0.360899,0.561952
3
- subgroup_size_stability,Subgroup size stability,0.709892,0.737025,0.702291,0.274505,0.858648,0.64279,0.381291,0.770208,0.712937,0.414758,0.652603
4
- family_mean,Family mean,0.684076,0.701987,0.646701,0.262739,0.82744,0.598026,0.346872,0.700413,0.657221,0.381235,0.59234
 
1
+ subitem_id,subitem_label,arf,bayesnet,ctgan,forestdiffusion,realtabformer,tabbyflow,tabddpm,tabdiff,tabpfgen,tabsyn,tvae
2
+ internal_profile_stability,Internal profile stability,0.691823,0.705327,0.657997,0.614168,0.789807,0.618007,0.586464,0.649159,0.663403,0.693785,0.61906
3
+ subgroup_size_stability,Subgroup size stability,0.711284,0.71791,0.684272,0.660166,0.804929,0.635508,0.601335,0.671455,0.686325,0.710633,0.664407
4
+ family_mean,Family mean,0.694374,0.704299,0.664152,0.630431,0.79015,0.626758,0.586383,0.652927,0.667404,0.693614,0.634954
evaluation/query_family/subgroup/data/model_summary.csv CHANGED
@@ -1,13 +1,13 @@
1
- model_id,model_label,dataset_count,dataset_prefixes,internal_profile_stability__mean,internal_profile_stability__std,internal_profile_stability__se,internal_profile_stability__ci95_low,internal_profile_stability__ci95_high,internal_profile_stability__ci95_radius,subgroup_size_stability__mean,subgroup_size_stability__std,subgroup_size_stability__se,subgroup_size_stability__ci95_low,subgroup_size_stability__ci95_high,subgroup_size_stability__ci95_radius,subgroup_structure_score__mean,subgroup_structure_score__std,subgroup_structure_score__se,subgroup_structure_score__ci95_low,subgroup_structure_score__ci95_high,subgroup_structure_score__ci95_radius,profile_minus_size__mean,profile_minus_size__std,profile_minus_size__se,profile_minus_size__ci95_low,profile_minus_size__ci95_high,profile_minus_size__ci95_radius
2
- real,REAL,48,"c,m,n",1.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
3
- arf,ARF,48,"c,m,n",0.676563,0.328719,0.047446,0.583568,0.769558,0.092995,0.709892,0.326187,0.048625,0.614587,0.805197,0.095305,0.684076,0.321546,0.046411,0.59311,0.775042,0.090966,-0.016027,0.157798,0.023523,-0.062133,0.030078,0.046105
4
- bayesnet,BayesNet,48,"c,m,n",0.679959,0.335581,0.048437,0.585023,0.774895,0.094936,0.737025,0.296328,0.044174,0.650444,0.823606,0.086581,0.701987,0.311266,0.044927,0.613929,0.790044,0.088058,-0.046993,0.1749,0.026073,-0.098095,0.004109,0.051102
5
- ctgan,CTGAN,46,"c,m,n",0.62376,0.351715,0.051858,0.522119,0.725401,0.101641,0.702291,0.300701,0.045856,0.612412,0.792169,0.089879,0.646701,0.331962,0.048945,0.550768,0.742633,0.095933,-0.049083,0.136261,0.02078,-0.089811,-0.008354,0.040728
6
- forestdiffusion,ForestDiffusion,26,"c,m,n",0.261531,0.370151,0.072592,0.119249,0.403812,0.142281,0.274505,0.372723,0.074545,0.128397,0.420612,0.146107,0.262739,0.366351,0.071847,0.121918,0.403559,0.140821,-0.002513,0.100507,0.020101,-0.041912,0.036886,0.039399
7
- realtabformer,RealTabFormer,44,"c,m,n",0.815889,0.25102,0.037843,0.741718,0.890061,0.074172,0.858648,0.191576,0.029919,0.800007,0.91729,0.058641,0.82744,0.229083,0.034536,0.75975,0.89513,0.06769,-0.024792,0.119972,0.018737,-0.061515,0.011932,0.036724
8
- tabbyflow,TabbyFlow,31,"c,m,n",0.573997,0.400779,0.071982,0.432912,0.715081,0.141085,0.64279,0.386824,0.070624,0.504367,0.781213,0.138423,0.598026,0.392722,0.070535,0.459777,0.736274,0.138249,-0.04966,0.144525,0.026386,-0.101378,0.002057,0.051718
9
- tabddpm,TabDDPM,37,"c,m,n",0.324354,0.401073,0.065936,0.19512,0.453589,0.129234,0.381291,0.423077,0.072557,0.239079,0.523503,0.142212,0.346872,0.403939,0.066407,0.216714,0.47703,0.130158,-0.049009,0.142651,0.024464,-0.096959,-0.001059,0.04795
10
- tabdiff,TabDiff,17,"c,m,n",0.675925,0.379459,0.092032,0.495541,0.856309,0.180384,0.770208,0.32777,0.081943,0.609601,0.930816,0.160607,0.700413,0.364624,0.088434,0.527082,0.873745,0.173331,-0.052038,0.170473,0.042618,-0.13557,0.031494,0.083532
11
- tabpfgen,TabPFGen,38,"c,m,n",0.636702,0.377427,0.061227,0.516698,0.756706,0.120004,0.712937,0.331918,0.056104,0.602972,0.822902,0.109965,0.657221,0.361244,0.058602,0.542362,0.77208,0.114859,-0.044556,0.140208,0.0237,-0.091007,0.001895,0.046451
12
- tabsyn,TabSyn,45,"c,m,n",0.360899,0.395347,0.058935,0.245387,0.476411,0.115512,0.414758,0.427986,0.06604,0.28532,0.544196,0.129438,0.381235,0.404316,0.060272,0.263102,0.499368,0.118133,-0.043578,0.132267,0.020409,-0.08358,-0.003576,0.040002
13
- tvae,TVAE,47,"c,m,n",0.561952,0.334175,0.048744,0.466413,0.657491,0.095539,0.652603,0.30385,0.045807,0.562821,0.742385,0.089782,0.59234,0.318457,0.046452,0.501294,0.683385,0.091046,-0.064919,0.165716,0.024983,-0.113885,-0.015953,0.048966
 
1
+ model_id,model_label,dataset_count,dataset_prefixes,internal_profile_stability__mean,internal_profile_stability__std,internal_profile_stability__se,internal_profile_stability__ci95_low,internal_profile_stability__ci95_high,internal_profile_stability__ci95_radius,subgroup_size_stability__mean,subgroup_size_stability__std,subgroup_size_stability__se,subgroup_size_stability__ci95_low,subgroup_size_stability__ci95_high,subgroup_size_stability__ci95_radius,subgroup_structure_score__mean,subgroup_structure_score__std,subgroup_structure_score__se,subgroup_structure_score__ci95_low,subgroup_structure_score__ci95_high,subgroup_structure_score__ci95_radius,profile_minus_size__mean,profile_minus_size__std,profile_minus_size__se,profile_minus_size__ci95_low,profile_minus_size__ci95_high,profile_minus_size__ci95_radius
2
+ real,REAL,49,"c,m,n",1.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
3
+ arf,ARF,49,"c,m,n",0.691823,0.347951,0.049707,0.594396,0.789249,0.097426,0.711284,0.337711,0.048744,0.615744,0.806823,0.095539,0.694374,0.345097,0.0493,0.597746,0.791001,0.096627,-0.005208,0.097578,0.014084,-0.032813,0.022397,0.027605
4
+ bayesnet,BayesNet,49,"c,m,n",0.705327,0.328912,0.046987,0.613232,0.797423,0.092095,0.71791,0.32201,0.046478,0.626813,0.809007,0.091097,0.704299,0.328232,0.04689,0.612394,0.796204,0.091905,0.002099,0.098408,0.014204,-0.025741,0.029939,0.02784
5
+ ctgan,CTGAN,49,"c,m,n",0.657997,0.353802,0.050543,0.558933,0.757062,0.099065,0.684272,0.318042,0.045905,0.594298,0.774247,0.089975,0.664152,0.335732,0.047962,0.570147,0.758157,0.094005,-0.012567,0.130527,0.01884,-0.049493,0.024359,0.036926
6
+ forestdiffusion,ForestDiffusion,49,"c,m,n",0.614168,0.344612,0.04923,0.517677,0.71066,0.096491,0.660166,0.335519,0.048428,0.565247,0.755085,0.094919,0.630431,0.340664,0.048666,0.535045,0.725817,0.095386,-0.033202,0.108514,0.015663,-0.063901,-0.002503,0.030699
7
+ realtabformer,RealTabFormer,49,"c,m,n",0.789807,0.262948,0.037564,0.716182,0.863433,0.073625,0.804929,0.243997,0.035218,0.735901,0.873956,0.069027,0.79015,0.260209,0.037173,0.717291,0.863008,0.072859,-0.0007,0.067493,0.009742,-0.019794,0.018394,0.019094
8
+ tabbyflow,TabbyFlow,46,"c,m,n",0.618007,0.334339,0.049296,0.521388,0.714626,0.096619,0.635508,0.33154,0.048883,0.539698,0.731319,0.09581,0.626758,0.330113,0.048673,0.531359,0.722156,0.095398,-0.017501,0.086621,0.012772,-0.042533,0.007531,0.025032
9
+ tabddpm,TabDDPM,40,"c,m,n",0.586464,0.373769,0.059098,0.470632,0.702296,0.115832,0.601335,0.352847,0.056501,0.490594,0.712077,0.110742,0.586383,0.363952,0.057546,0.473593,0.699173,0.11279,0.000167,0.102626,0.016433,-0.032043,0.032376,0.032209
10
+ tabdiff,TabDiff,44,"c,m,n",0.649159,0.336942,0.050796,0.549599,0.748719,0.09956,0.671455,0.332929,0.050771,0.571943,0.770966,0.099511,0.652927,0.337062,0.050814,0.553331,0.752522,0.099596,-0.00771,0.092258,0.014069,-0.035286,0.019865,0.027576
11
+ tabpfgen,TabPFGen,46,"c,m,n",0.663403,0.358289,0.052827,0.559863,0.766944,0.103541,0.686325,0.361571,0.0539,0.580682,0.791969,0.105644,0.667404,0.359994,0.053078,0.563371,0.771437,0.104033,-0.00818,0.121754,0.01815,-0.043754,0.027394,0.035574
12
+ tabsyn,TabSyn,40,"c,m,n",0.693785,0.324861,0.051365,0.593109,0.79446,0.100676,0.710633,0.322337,0.051615,0.609467,0.811799,0.101166,0.693614,0.326967,0.051698,0.592286,0.794942,0.101328,0.00035,0.09902,0.015856,-0.030727,0.031428,0.031077
13
+ tvae,TVAE,49,"c,m,n",0.61906,0.327773,0.046825,0.527283,0.710836,0.091776,0.664407,0.301879,0.043572,0.579005,0.749809,0.085402,0.634954,0.314432,0.044919,0.546913,0.722995,0.088041,-0.03245,0.127273,0.01837,-0.068456,0.003555,0.036006
evaluation/query_family/subgroup/data/prefix_plot_data.csv CHANGED
@@ -1,13 +1,13 @@
1
- model_id,model_label,c,m,n
2
- real,REAL,1.0,1.0,1.0
3
- arf,ARF,0.755689,0.796267,0.551279
4
- bayesnet,BayesNet,0.754772,0.79733,0.596781
5
- ctgan,CTGAN,0.844435,0.671791,0.465661
6
- forestdiffusion,ForestDiffusion,0.36523,0.474252,0.011535
7
- realtabformer,RealTabFormer,0.890188,0.884023,0.710648
8
- tabbyflow,TabbyFlow,0.514889,0.75608,0.568864
9
- tabddpm,TabDDPM,0.415738,0.387299,0.282582
10
- tabdiff,TabDiff,0.696081,0.841695,0.429403
11
- tabpfgen,TabPFGen,0.688725,0.753259,0.577603
12
- tabsyn,TabSyn,0.288085,0.786848,0.21193
13
- tvae,TVAE,0.736194,0.556068,0.484627
 
1
+ model_id,model_label,c,m,n
2
+ real,REAL,1.0,1.0,1.0
3
+ arf,ARF,0.870832,0.755307,0.482638
4
+ bayesnet,BayesNet,0.850388,0.764055,0.523615
5
+ ctgan,CTGAN,0.828731,0.663757,0.499803
6
+ forestdiffusion,ForestDiffusion,0.800834,0.69388,0.423294
7
+ realtabformer,RealTabFormer,0.899462,0.80992,0.669392
8
+ tabbyflow,TabbyFlow,0.757901,0.712372,0.432503
9
+ tabddpm,TabDDPM,0.788882,0.683627,0.374328
10
+ tabdiff,TabDiff,0.810993,0.751277,0.457785
11
+ tabpfgen,TabPFGen,0.822643,0.751138,0.469619
12
+ tabsyn,TabSyn,0.828181,0.725563,0.473691
13
+ tvae,TVAE,0.761926,0.581002,0.539217
evaluation/query_family/subgroup/data/prefix_summary.csv CHANGED
@@ -1,37 +1,37 @@
1
- model_id,model_label,dataset_prefix,dataset_count,internal_profile_stability,subgroup_size_stability,subgroup_structure_score,profile_minus_size
2
- real,REAL,c,18,1.0,1.0,1.0,0.0
3
- real,REAL,m,11,1.0,1.0,1.0,0.0
4
- real,REAL,n,19,1.0,1.0,1.0,0.0
5
- arf,ARF,c,18,0.76538,0.745998,0.755689,0.019382
6
- arf,ARF,m,11,0.759112,0.833423,0.796267,-0.074311
7
- arf,ARF,n,19,0.544629,0.584345,0.551279,-0.015793
8
- bayesnet,BayesNet,c,18,0.759906,0.749639,0.754772,0.010267
9
- bayesnet,BayesNet,m,11,0.744457,0.850202,0.79733,-0.105745
10
- bayesnet,BayesNet,n,19,0.566879,0.645024,0.596781,-0.071019
11
- ctgan,CTGAN,c,16,0.848594,0.840277,0.844435,0.008316
12
- ctgan,CTGAN,m,11,0.610273,0.733309,0.671791,-0.123036
13
- ctgan,CTGAN,n,19,0.442234,0.54298,0.465661,-0.055639
14
- forestdiffusion,ForestDiffusion,c,8,0.352112,0.378347,0.36523,-0.026235
15
- forestdiffusion,ForestDiffusion,m,8,0.482094,0.466411,0.474252,0.015684
16
- forestdiffusion,ForestDiffusion,n,10,0.012614,0.011617,0.011535,0.002399
17
- realtabformer,RealTabFormer,c,18,0.888578,0.891799,0.890188,-0.003221
18
- realtabformer,RealTabFormer,m,11,0.855652,0.912395,0.884023,-0.056743
19
- realtabformer,RealTabFormer,n,15,0.699504,0.759655,0.710648,-0.02786
20
- tabbyflow,TabbyFlow,c,11,0.520855,0.508923,0.514889,0.011932
21
- tabbyflow,TabbyFlow,m,8,0.702157,0.810004,0.75608,-0.107848
22
- tabbyflow,TabbyFlow,n,12,0.537269,0.655047,0.568864,-0.068935
23
- tabddpm,TabDDPM,c,10,0.413465,0.418011,0.415738,-0.004546
24
- tabddpm,TabDDPM,m,10,0.323065,0.451532,0.387299,-0.128467
25
- tabddpm,TabDDPM,n,17,0.272695,0.304891,0.282582,-0.024012
26
- tabdiff,TabDiff,c,8,0.701718,0.690444,0.696081,0.011274
27
- tabdiff,TabDiff,m,6,0.788453,0.894937,0.841695,-0.106485
28
- tabdiff,TabDiff,n,3,0.382088,0.715077,0.429403,-0.141946
29
- tabpfgen,TabPFGen,c,13,0.689467,0.687984,0.688725,0.001483
30
- tabpfgen,TabPFGen,m,9,0.697422,0.809096,0.753259,-0.111674
31
- tabpfgen,TabPFGen,n,16,0.559676,0.671319,0.577603,-0.044128
32
- tabsyn,TabSyn,c,17,0.279223,0.296947,0.288085,-0.017725
33
- tabsyn,TabSyn,m,11,0.734459,0.839237,0.786848,-0.104778
34
- tabsyn,TabSyn,n,17,0.20086,0.224294,0.21193,-0.026885
35
- tvae,TVAE,c,17,0.741124,0.731265,0.736194,0.009859
36
- tvae,TVAE,m,11,0.481531,0.630605,0.556068,-0.149074
37
- tvae,TVAE,n,19,0.448199,0.584148,0.484627,-0.086515
 
1
+ model_id,model_label,dataset_prefix,dataset_count,internal_profile_stability,subgroup_size_stability,subgroup_structure_score,profile_minus_size
2
+ real,REAL,c,19,1.0,1.0,1.0,0.0
3
+ real,REAL,m,11,1.0,1.0,1.0,0.0
4
+ real,REAL,n,19,1.0,1.0,1.0,0.0
5
+ arf,ARF,c,19,0.873723,0.867941,0.870832,0.005782
6
+ arf,ARF,m,11,0.737465,0.773149,0.755307,-0.035684
7
+ arf,ARF,n,19,0.483498,0.508116,0.482638,0.001816
8
+ bayesnet,BayesNet,c,19,0.85064,0.850136,0.850388,0.000505
9
+ bayesnet,BayesNet,m,11,0.754427,0.773684,0.764055,-0.019257
10
+ bayesnet,BayesNet,n,19,0.531589,0.544254,0.523615,0.016834
11
+ ctgan,CTGAN,c,19,0.830826,0.826636,0.828731,0.004189
12
+ ctgan,CTGAN,m,11,0.627338,0.700176,0.663757,-0.072838
13
+ ctgan,CTGAN,n,19,0.502919,0.52428,0.499803,0.006578
14
+ forestdiffusion,ForestDiffusion,c,19,0.78309,0.818577,0.800834,-0.035487
15
+ forestdiffusion,ForestDiffusion,m,11,0.667279,0.72048,0.69388,-0.053201
16
+ forestdiffusion,ForestDiffusion,n,19,0.414499,0.456095,0.423294,-0.018569
17
+ realtabformer,RealTabFormer,c,19,0.905805,0.893119,0.899462,0.012687
18
+ realtabformer,RealTabFormer,m,11,0.808946,0.810894,0.80992,-0.001948
19
+ realtabformer,RealTabFormer,n,19,0.662728,0.708194,0.669392,-0.014067
20
+ tabbyflow,TabbyFlow,c,18,0.755472,0.76033,0.757901,-0.004858
21
+ tabbyflow,TabbyFlow,m,11,0.696738,0.728005,0.712372,-0.031267
22
+ tabbyflow,TabbyFlow,n,17,0.421512,0.443493,0.432503,-0.021981
23
+ tabddpm,TabDDPM,c,13,0.797139,0.780626,0.788882,0.016514
24
+ tabddpm,TabDDPM,m,10,0.675513,0.691741,0.683627,-0.016228
25
+ tabddpm,TabDDPM,n,17,0.372978,0.399158,0.374328,-0.002869
26
+ tabdiff,TabDiff,c,16,0.814657,0.807329,0.810993,0.007328
27
+ tabdiff,TabDiff,m,10,0.736522,0.766033,0.751277,-0.029511
28
+ tabdiff,TabDiff,n,18,0.453516,0.487939,0.457785,-0.00904
29
+ tabpfgen,TabPFGen,c,17,0.832439,0.812847,0.822643,0.019592
30
+ tabpfgen,TabPFGen,m,11,0.714777,0.7875,0.751138,-0.072723
31
+ tabpfgen,TabPFGen,n,18,0.472363,0.494338,0.469619,0.005812
32
+ tabsyn,TabSyn,c,17,0.833284,0.823078,0.828181,0.010206
33
+ tabsyn,TabSyn,m,11,0.712105,0.73902,0.725563,-0.026915
34
+ tabsyn,TabSyn,n,12,0.479367,0.508467,0.473691,0.012384
35
+ tvae,TVAE,c,19,0.756844,0.767009,0.761926,-0.010165
36
+ tvae,TVAE,m,11,0.554374,0.60763,0.581002,-0.053255
37
+ tvae,TVAE,n,19,0.518725,0.590803,0.539217,-0.043259
evaluation/query_family/subgroup/figures/subgroup_branch_dumbbell_main.tex ADDED
@@ -0,0 +1,90 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \documentclass[tikz,border=4pt]{standalone}
2
+ \usepackage{pgfplots}
3
+ \usepackage{xcolor}
4
+ \usetikzlibrary{patterns}
5
+ \pgfplotsset{compat=1.18}
6
+
7
+ \definecolor{modelreal}{HTML}{000000}
8
+ \definecolor{modelarf}{HTML}{777777}
9
+ \definecolor{modelbayesnet}{HTML}{CCBB44}
10
+ \definecolor{modelctgan}{HTML}{EE6677}
11
+ \definecolor{modelforestdiffusion}{HTML}{228833}
12
+ \definecolor{modelrealtabformer}{HTML}{332288}
13
+ \definecolor{modeltabbyflow}{HTML}{882255}
14
+ \definecolor{modeltabddpm}{HTML}{EE7733}
15
+ \definecolor{modeltabdiff}{HTML}{AA3377}
16
+ \definecolor{modeltabpfgen}{HTML}{009988}
17
+ \definecolor{modeltabsyn}{HTML}{66CCEE}
18
+ \definecolor{modeltvae}{HTML}{4477AA}
19
+ \begin{document}
20
+ \begin{tikzpicture}
21
+ \begin{axis}[
22
+ width=13.2cm,
23
+ height=9.8cm,
24
+ xmin=0.15, xmax=1.03,
25
+ ytick={12,11,10,9,8,7,6,5,4,3,2,1},
26
+ yticklabels={REAL,ARF,BayesNet,CTGAN,ForestDiffusion,RealTabFormer,TabbyFlow,TabDDPM,TabDiff,TabPFGen,TabSyn,TVAE},
27
+ y dir=reverse,
28
+ xlabel={Score},
29
+ grid=both,
30
+ grid style={draw=gray!18},
31
+ tick style={draw=black!70},
32
+ legend style={draw=none, fill=none, font=\scriptsize, at={(0.03,0.03)}, anchor=south west},
33
+ ]
34
+ \draw[line width=0.9pt, color=modelreal!70] (axis cs:1.0000,12) -- (axis cs:1.0000,12);
35
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modelreal, fill=modelreal] coordinates { (1.0000,12) };
36
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modelreal, fill=modelreal] coordinates { (1.0000,12) };
37
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (1.0000,12) };
38
+ \draw[line width=0.9pt, color=modelarf!70] (axis cs:0.7113,11) -- (axis cs:0.6918,11);
39
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modelarf, fill=modelarf] coordinates { (0.7113,11) };
40
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modelarf, fill=modelarf] coordinates { (0.6918,11) };
41
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.6944,11) };
42
+ \draw[line width=0.9pt, color=modelbayesnet!70] (axis cs:0.7179,10) -- (axis cs:0.7053,10);
43
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modelbayesnet, fill=modelbayesnet] coordinates { (0.7179,10) };
44
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modelbayesnet, fill=modelbayesnet] coordinates { (0.7053,10) };
45
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.7043,10) };
46
+ \draw[line width=0.9pt, color=modelctgan!70] (axis cs:0.6843,9) -- (axis cs:0.6580,9);
47
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modelctgan, fill=modelctgan] coordinates { (0.6843,9) };
48
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modelctgan, fill=modelctgan] coordinates { (0.6580,9) };
49
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.6642,9) };
50
+ \draw[line width=0.9pt, color=modelforestdiffusion!70] (axis cs:0.6602,8) -- (axis cs:0.6142,8);
51
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modelforestdiffusion, fill=modelforestdiffusion] coordinates { (0.6602,8) };
52
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modelforestdiffusion, fill=modelforestdiffusion] coordinates { (0.6142,8) };
53
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.6304,8) };
54
+ \draw[line width=0.9pt, color=modelrealtabformer!70] (axis cs:0.8049,7) -- (axis cs:0.7898,7);
55
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modelrealtabformer, fill=modelrealtabformer] coordinates { (0.8049,7) };
56
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modelrealtabformer, fill=modelrealtabformer] coordinates { (0.7898,7) };
57
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.7902,7) };
58
+ \draw[line width=0.9pt, color=modeltabbyflow!70] (axis cs:0.6355,6) -- (axis cs:0.6180,6);
59
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modeltabbyflow, fill=modeltabbyflow] coordinates { (0.6355,6) };
60
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modeltabbyflow, fill=modeltabbyflow] coordinates { (0.6180,6) };
61
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.6268,6) };
62
+ \draw[line width=0.9pt, color=modeltabddpm!70] (axis cs:0.6013,5) -- (axis cs:0.5865,5);
63
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modeltabddpm, fill=modeltabddpm] coordinates { (0.6013,5) };
64
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modeltabddpm, fill=modeltabddpm] coordinates { (0.5865,5) };
65
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.5864,5) };
66
+ \draw[line width=0.9pt, color=modeltabdiff!70] (axis cs:0.6715,4) -- (axis cs:0.6492,4);
67
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modeltabdiff, fill=modeltabdiff] coordinates { (0.6715,4) };
68
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modeltabdiff, fill=modeltabdiff] coordinates { (0.6492,4) };
69
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.6529,4) };
70
+ \draw[line width=0.9pt, color=modeltabpfgen!70] (axis cs:0.6863,3) -- (axis cs:0.6634,3);
71
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modeltabpfgen, fill=modeltabpfgen] coordinates { (0.6863,3) };
72
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modeltabpfgen, fill=modeltabpfgen] coordinates { (0.6634,3) };
73
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.6674,3) };
74
+ \draw[line width=0.9pt, color=modeltabsyn!70] (axis cs:0.7106,2) -- (axis cs:0.6938,2);
75
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modeltabsyn, fill=modeltabsyn] coordinates { (0.7106,2) };
76
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modeltabsyn, fill=modeltabsyn] coordinates { (0.6938,2) };
77
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.6936,2) };
78
+ \draw[line width=0.9pt, color=modeltvae!70] (axis cs:0.6644,1) -- (axis cs:0.6191,1);
79
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modeltvae, fill=modeltvae] coordinates { (0.6644,1) };
80
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modeltvae, fill=modeltvae] coordinates { (0.6191,1) };
81
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.6350,1) };
82
+ \addlegendimage{only marks, mark=square*, mark size=2.4pt, draw=black, fill=black}
83
+ \addlegendentry{Subgroup size stability}
84
+ \addlegendimage{only marks, mark=*, mark size=2.6pt, draw=black, fill=black}
85
+ \addlegendentry{Internal profile stability}
86
+ \addlegendimage{only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black}
87
+ \addlegendentry{Canonical subgroup score}
88
+ \end{axis}
89
+ \end{tikzpicture}
90
+ \end{document}
evaluation/query_family/subgroup/figures/subgroup_dataset_model_heatmap_appendix.tex ADDED
@@ -0,0 +1,62 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \documentclass{standalone}
2
+ \usepackage[table]{xcolor}
3
+ \usepackage{booktabs}
4
+ \begin{document}
5
+ \scriptsize
6
+ \setlength{\tabcolsep}{4pt}
7
+ \begin{tabular}{lcccccccccccc}
8
+ \toprule
9
+ Dataset & REAL & ARF & BayesNet & CTGAN & ForestDiffusion & RealTabFormer & TabbyFlow & TabDDPM & TabDiff & TabPFGen & TabSyn & TVAE \\
10
+ \midrule
11
+ C2 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{0A1E5C} & \cellcolor[HTML]{091E5A} & \cellcolor[HTML]{0D2161} & \cellcolor[HTML]{0A1E5C} & \cellcolor[HTML]{091E5A} & \cellcolor[HTML]{24409A} & \cellcolor[HTML]{0C2060} & \cellcolor[HTML]{24409A} & \cellcolor[HTML]{243D98} & \cellcolor[HTML]{243392} & \cellcolor[HTML]{0A1E5C} \\
12
+ C3 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} \\
13
+ C4 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{091E5A} & \cellcolor[HTML]{091E5A} & \cellcolor[HTML]{091E5A} & \cellcolor[HTML]{0B1F5E} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{091E5A} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{0C2060} & \cellcolor[HTML]{081D58} \\
14
+ C5 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{243C98} & \cellcolor[HTML]{243F99} & \cellcolor[HTML]{243C98} & \cellcolor[HTML]{24439B} & \cellcolor[HTML]{243C98} & \cellcolor[HTML]{243D98} & \cellcolor[HTML]{24439B} & \cellcolor[HTML]{243C98} & \cellcolor[HTML]{1E2E85} & \cellcolor[HTML]{24409A} & \cellcolor[HTML]{24439B} \\
15
+ C6 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{32A6C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{34A9C3} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{32A6C2} & \cellcolor[HTML]{34A9C3} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{32A6C2} \\
16
+ C7 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{0D2161} & \cellcolor[HTML]{142670} & \cellcolor[HTML]{0D2163} & \cellcolor[HTML]{0C2060} & \cellcolor[HTML]{13266F} & \cellcolor[HTML]{1B2C80} & \cellcolor[HTML]{0D2161} & \cellcolor[HTML]{142670} & \cellcolor[HTML]{13266F} & \cellcolor[HTML]{1B2C80} & \cellcolor[HTML]{142670} \\
17
+ C8 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{0E2265} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{12256D} & \cellcolor[HTML]{12256D} & \cellcolor[HTML]{0E2265} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{11246B} \\
18
+ C9 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{CBEBB4} & \cellcolor[HTML]{C2E7B4} & \cellcolor[HTML]{C2E7B4} & \cellcolor[HTML]{CBEBB4} & \cellcolor[HTML]{0D2163} & \cellcolor[HTML]{CBEBB4} & \cellcolor[HTML]{CBEBB4} & \cellcolor[HTML]{CBEBB4} & \cellcolor[HTML]{CBEBB4} & \cellcolor[HTML]{CBEBB4} & \cellcolor[HTML]{C2E7B4} \\
19
+ C10 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & & \cellcolor[HTML]{102369} \\
20
+ C11 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{102369} & \cellcolor[HTML]{11246B} & \cellcolor[HTML]{152772} & \cellcolor[HTML]{12256D} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{0D2163} & \cellcolor[HTML]{0D2163} & \cellcolor[HTML]{0D2161} & \cellcolor[HTML]{0B1F5E} & \cellcolor[HTML]{0D2163} & \cellcolor[HTML]{0D2161} \\
21
+ C12 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2350A1} & \cellcolor[HTML]{081D58} & & & & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{299DC1} \\
22
+ C13 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{5FC1C0} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2094C0} & \cellcolor[HTML]{102369} & \cellcolor[HTML]{F8FCCA} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{5FC1C0} \\
23
+ C14 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{21318D} & \cellcolor[HTML]{2354A3} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{091E5A} & \cellcolor[HTML]{80CEBB} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{225DA8} \\
24
+ C15 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{253595} & \cellcolor[HTML]{2354A3} & \cellcolor[HTML]{1F78B4} & \cellcolor[HTML]{2070B0} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2165AB} & & \cellcolor[HTML]{2260A9} & \cellcolor[HTML]{2354A3} & \cellcolor[HTML]{2260A9} & \cellcolor[HTML]{32A6C2} \\
25
+ C16 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{243392} & \cellcolor[HTML]{1E8ABD} & \cellcolor[HTML]{243392} & \cellcolor[HTML]{1E8BBD} & \cellcolor[HTML]{243C98} & \cellcolor[HTML]{A7DCB7} & & \cellcolor[HTML]{2DA2C2} & & \cellcolor[HTML]{31A5C2} & \cellcolor[HTML]{5FC1C0} \\
26
+ C17 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2076B3} & \cellcolor[HTML]{2076B3} & \cellcolor[HTML]{142670} & \cellcolor[HTML]{3CB1C3} & \cellcolor[HTML]{32A6C2} & \cellcolor[HTML]{A9DDB7} & & \cellcolor[HTML]{36ABC3} & \cellcolor[HTML]{1F7AB5} & \cellcolor[HTML]{3BB0C3} & \cellcolor[HTML]{243D98} \\
27
+ C18 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{32A6C2} & \cellcolor[HTML]{42B6C4} & \cellcolor[HTML]{269BC1} & \cellcolor[HTML]{4AB9C3} & \cellcolor[HTML]{24419A} & \cellcolor[HTML]{9CD8B8} & & & & & \cellcolor[HTML]{259AC1} \\
28
+ C19 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2258A5} & \cellcolor[HTML]{234DA0} & \cellcolor[HTML]{37ACC3} & \cellcolor[HTML]{1F80B8} & & \cellcolor[HTML]{234DA0} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{22328F} & \cellcolor[HTML]{2352A3} \\
29
+ C20 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2258A5} & & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} \\
30
+ M1 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{21318D} & \cellcolor[HTML]{21308B} & \cellcolor[HTML]{182A7A} & \cellcolor[HTML]{24409A} & \cellcolor[HTML]{162874} & \cellcolor[HTML]{11246B} & \cellcolor[HTML]{162874} & \cellcolor[HTML]{1F7BB6} \\
31
+ M2 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{4EBBC2} & \cellcolor[HTML]{4EBBC2} & \cellcolor[HTML]{4EBBC2} & \cellcolor[HTML]{4EBBC2} & \cellcolor[HTML]{3CB1C3} & \cellcolor[HTML]{55BEC1} & \cellcolor[HTML]{4CBAC2} & & \cellcolor[HTML]{4EBBC2} & \cellcolor[HTML]{4EBBC2} & \cellcolor[HTML]{4EBBC2} \\
32
+ M4 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2259A6} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{13266F} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2259A6} \\
33
+ M5 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{32A6C2} & \cellcolor[HTML]{32A6C2} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{53BDC1} & \cellcolor[HTML]{35AAC3} & \cellcolor[HTML]{37ACC3} & \cellcolor[HTML]{75C9BD} & \cellcolor[HTML]{46B8C3} & \cellcolor[HTML]{2354A3} & \cellcolor[HTML]{37ACC3} & \cellcolor[HTML]{B7E3B6} \\
34
+ M6 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{0B1F5E} & \cellcolor[HTML]{0C2060} & \cellcolor[HTML]{A5DCB7} & \cellcolor[HTML]{24439B} & \cellcolor[HTML]{13266F} & \cellcolor[HTML]{1E2E85} & \cellcolor[HTML]{23499E} & \cellcolor[HTML]{152772} & \cellcolor[HTML]{1D2E83} & \cellcolor[HTML]{172976} & \cellcolor[HTML]{C0E6B5} \\
35
+ M7 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{162874} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{13266F} \\
36
+ M8 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{40B5C4} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{34A9C3} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{6BC6BE} \\
37
+ M9 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{243392} & \cellcolor[HTML]{243392} & \cellcolor[HTML]{243392} & \cellcolor[HTML]{1F7DB6} & \cellcolor[HTML]{12256D} & \cellcolor[HTML]{2DA2C2} & \cellcolor[HTML]{1F7DB6} & \cellcolor[HTML]{1F7EB7} & \cellcolor[HTML]{225CA7} & \cellcolor[HTML]{1F7EB7} & \cellcolor[HTML]{1E85BA} \\
38
+ M10 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{24449C} & \cellcolor[HTML]{233390} & \cellcolor[HTML]{253595} & \cellcolor[HTML]{24459C} & \cellcolor[HTML]{091E5A} & \cellcolor[HTML]{24439B} & \cellcolor[HTML]{2352A3} & \cellcolor[HTML]{24439B} & \cellcolor[HTML]{24449C} & \cellcolor[HTML]{24439B} & \cellcolor[HTML]{253997} \\
39
+ M11 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{61C2BF} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{67C4BE} \\
40
+ M12 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2076B3} & \cellcolor[HTML]{2165AB} & \cellcolor[HTML]{1F80B8} & \cellcolor[HTML]{299DC1} & \cellcolor[HTML]{102369} & \cellcolor[HTML]{206EB0} & & \cellcolor[HTML]{2163AA} & \cellcolor[HTML]{216BAE} & \cellcolor[HTML]{2075B3} & \cellcolor[HTML]{1D8EBF} \\
41
+ N1 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{40B5C4} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} \\
42
+ N2 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{C6E9B4} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{C6E9B4} & \cellcolor[HTML]{C6E9B4} & \cellcolor[HTML]{C6E9B4} & \cellcolor[HTML]{081D58} & & \cellcolor[HTML]{081D58} \\
43
+ N3 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{D0EDB3} & \cellcolor[HTML]{D0EDB3} & \cellcolor[HTML]{EEF8B3} & \cellcolor[HTML]{E0F3B2} & \cellcolor[HTML]{40B5C4} & \cellcolor[HTML]{DDF2B2} & \cellcolor[HTML]{DFF2B2} & \cellcolor[HTML]{DDF2B2} & \cellcolor[HTML]{E5F5B2} & \cellcolor[HTML]{CEECB3} & \cellcolor[HTML]{EEF8B3} \\
44
+ N4 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{76CABC} & \cellcolor[HTML]{76CABC} & \cellcolor[HTML]{D5EFB3} & \cellcolor[HTML]{76CABC} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{73C8BD} & \cellcolor[HTML]{CFECB3} & \cellcolor[HTML]{73C8BD} & \cellcolor[HTML]{73C8BD} & & \cellcolor[HTML]{C6E9B4} \\
45
+ N5 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{89D1BA} & \cellcolor[HTML]{46B8C3} & \cellcolor[HTML]{61C2BF} & \cellcolor[HTML]{8CD2BA} & \cellcolor[HTML]{39ADC3} & \cellcolor[HTML]{97D6B9} & \cellcolor[HTML]{EAF7B1} & \cellcolor[HTML]{89D1BA} & \cellcolor[HTML]{8CD2BA} & & \cellcolor[HTML]{67C4BE} \\
46
+ N6 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{D3EEB3} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{D3EEB3} \\
47
+ N7 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{37ACC3} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & & \cellcolor[HTML]{33A7C2} \\
48
+ N8 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2296C1} & \cellcolor[HTML]{2498C1} & \cellcolor[HTML]{87D0BA} & \cellcolor[HTML]{35AAC3} & \cellcolor[HTML]{1F7AB5} & \cellcolor[HTML]{2296C1} & & \cellcolor[HTML]{31A5C2} & & \cellcolor[HTML]{31A5C2} & \cellcolor[HTML]{35AAC3} \\
49
+ N9 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & & \cellcolor[HTML]{FFFFD9} \\
50
+ N10 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & & \cellcolor[HTML]{081D58} \\
51
+ N11 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} \\
52
+ N12 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{E8F6B1} & \cellcolor[HTML]{E8F6B1} & \cellcolor[HTML]{1C2D81} & \cellcolor[HTML]{F5FBC2} & \cellcolor[HTML]{0F2367} & \cellcolor[HTML]{F5FBC2} & \cellcolor[HTML]{F5FBC2} & \cellcolor[HTML]{F5FBC2} & \cellcolor[HTML]{F5FBC2} & & \cellcolor[HTML]{182A7A} \\
53
+ N14 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{FEFFD8} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{F1FABB} & & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FCFED3} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FCFED3} & \cellcolor[HTML]{FFFFD9} \\
54
+ N15 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{152772} & \cellcolor[HTML]{0B1F5E} & \cellcolor[HTML]{EDF8B2} & \cellcolor[HTML]{192B7C} & \cellcolor[HTML]{142670} & \cellcolor[HTML]{216AAD} & \cellcolor[HTML]{9ED9B8} & \cellcolor[HTML]{152772} & \cellcolor[HTML]{1B2C80} & \cellcolor[HTML]{152772} & \cellcolor[HTML]{24479D} \\
55
+ N16 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} \\
56
+ N17 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{F3FABF} & \cellcolor[HTML]{1D90C0} & \cellcolor[HTML]{259AC1} & \cellcolor[HTML]{F8FCCA} & \cellcolor[HTML]{2075B3} & & \cellcolor[HTML]{F4FBC1} & \cellcolor[HTML]{F4FBC1} & \cellcolor[HTML]{F4FBC0} & \cellcolor[HTML]{F8FCCA} & \cellcolor[HTML]{2DA2C2} \\
57
+ N18 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{EAF7B1} & \cellcolor[HTML]{E2F4B2} & \cellcolor[HTML]{E1F3B2} & \cellcolor[HTML]{E7F6B1} & \cellcolor[HTML]{BDE5B5} & \cellcolor[HTML]{E1F3B2} & & \cellcolor[HTML]{E3F4B2} & \cellcolor[HTML]{E8F6B1} & \cellcolor[HTML]{E3F4B2} & \cellcolor[HTML]{E5F5B2} \\
58
+ N19 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{E0F3B2} & \cellcolor[HTML]{CEECB3} & \cellcolor[HTML]{24489D} & \cellcolor[HTML]{F9FDCC} & \cellcolor[HTML]{216DAF} & \cellcolor[HTML]{FBFDD0} & \cellcolor[HTML]{FBFDD0} & \cellcolor[HTML]{EDF8B1} & \cellcolor[HTML]{CBEBB4} & \cellcolor[HTML]{E0F3B2} & \cellcolor[HTML]{1F7AB5} \\
59
+ N20 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{2166AC} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} \\
60
+ \bottomrule
61
+ \end{tabular}
62
+ \end{document}
evaluation/query_family/subgroup/figures/subgroup_family_subitem_bars_appendix.tex ADDED
@@ -0,0 +1,66 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \documentclass[tikz,border=4pt]{standalone}
2
+ \usepackage{pgfplots}
3
+ \usepackage{xcolor}
4
+ \pgfplotsset{compat=1.18}
5
+
6
+ \definecolor{barreal}{HTML}{000000}
7
+ \definecolor{bararf}{HTML}{777777}
8
+ \definecolor{barbayesnet}{HTML}{CCBB44}
9
+ \definecolor{barctgan}{HTML}{EE6677}
10
+ \definecolor{barforestdiffusion}{HTML}{228833}
11
+ \definecolor{barrealtabformer}{HTML}{332288}
12
+ \definecolor{bartabbyflow}{HTML}{882255}
13
+ \definecolor{bartabddpm}{HTML}{EE7733}
14
+ \definecolor{bartabdiff}{HTML}{AA3377}
15
+ \definecolor{bartabpfgen}{HTML}{009988}
16
+ \definecolor{bartabsyn}{HTML}{66CCEE}
17
+ \definecolor{bartvae}{HTML}{4477AA}
18
+ \begin{document}
19
+ \begin{tikzpicture}
20
+ \begin{axis}[
21
+ width=13.50cm,
22
+ height=8.8cm,
23
+ ymin=0.0, ymax=1.08,
24
+ ylabel={Score},
25
+ title={Subgroup family and subitem bars},
26
+ ymajorgrids,
27
+ grid style={draw=gray!22},
28
+ major grid style={draw=gray!30},
29
+ axis line style={draw=black!70},
30
+ tick style={draw=black!70},
31
+ xtick={0.0000,1.1000,2.2000,3.3000,4.4000,5.5000,6.6000,7.7000,8.8000,9.9000,11.0000,12.1000,14.5500,15.6500,16.7500,17.8500,18.9500,20.0500,21.1500,22.2500,23.3500,24.4500,25.5500,26.6500},
32
+ xticklabels={REAL,ARF,BayesNet,CTGAN,ForestDiffusion,RealTabFormer,TabbyFlow,TabDDPM,TabDiff,TabPFGen,TabSyn,TVAE,REAL,ARF,BayesNet,CTGAN,ForestDiffusion,RealTabFormer,TabbyFlow,TabDDPM,TabDiff,TabPFGen,TabSyn,TVAE},
33
+ x tick label style={rotate=90, anchor=east, font=\scriptsize},
34
+ enlarge x limits=0.01,
35
+ clip=false,
36
+ ]
37
+ \addplot+[ybar, bar width=5.8pt, draw=barreal, fill=barreal] coordinates {(0.0000,1.000000)};
38
+ \addplot+[ybar, bar width=5.8pt, draw=bararf, fill=bararf] coordinates {(1.1000,0.691823)};
39
+ \addplot+[ybar, bar width=5.8pt, draw=barbayesnet, fill=barbayesnet] coordinates {(2.2000,0.705327)};
40
+ \addplot+[ybar, bar width=5.8pt, draw=barctgan, fill=barctgan] coordinates {(3.3000,0.657997)};
41
+ \addplot+[ybar, bar width=5.8pt, draw=barforestdiffusion, fill=barforestdiffusion] coordinates {(4.4000,0.614168)};
42
+ \addplot+[ybar, bar width=5.8pt, draw=barrealtabformer, fill=barrealtabformer] coordinates {(5.5000,0.789807)};
43
+ \addplot+[ybar, bar width=5.8pt, draw=bartabbyflow, fill=bartabbyflow] coordinates {(6.6000,0.618007)};
44
+ \addplot+[ybar, bar width=5.8pt, draw=bartabddpm, fill=bartabddpm] coordinates {(7.7000,0.586464)};
45
+ \addplot+[ybar, bar width=5.8pt, draw=bartabdiff, fill=bartabdiff] coordinates {(8.8000,0.649159)};
46
+ \addplot+[ybar, bar width=5.8pt, draw=bartabpfgen, fill=bartabpfgen] coordinates {(9.9000,0.663403)};
47
+ \addplot+[ybar, bar width=5.8pt, draw=bartabsyn, fill=bartabsyn] coordinates {(11.0000,0.693785)};
48
+ \addplot+[ybar, bar width=5.8pt, draw=bartvae, fill=bartvae] coordinates {(12.1000,0.619060)};
49
+ \addplot+[ybar, bar width=5.8pt, draw=barreal, fill=barreal] coordinates {(14.5500,1.000000)};
50
+ \addplot+[ybar, bar width=5.8pt, draw=bararf, fill=bararf] coordinates {(15.6500,0.711284)};
51
+ \addplot+[ybar, bar width=5.8pt, draw=barbayesnet, fill=barbayesnet] coordinates {(16.7500,0.717910)};
52
+ \addplot+[ybar, bar width=5.8pt, draw=barctgan, fill=barctgan] coordinates {(17.8500,0.684272)};
53
+ \addplot+[ybar, bar width=5.8pt, draw=barforestdiffusion, fill=barforestdiffusion] coordinates {(18.9500,0.660166)};
54
+ \addplot+[ybar, bar width=5.8pt, draw=barrealtabformer, fill=barrealtabformer] coordinates {(20.0500,0.804929)};
55
+ \addplot+[ybar, bar width=5.8pt, draw=bartabbyflow, fill=bartabbyflow] coordinates {(21.1500,0.635508)};
56
+ \addplot+[ybar, bar width=5.8pt, draw=bartabddpm, fill=bartabddpm] coordinates {(22.2500,0.601335)};
57
+ \addplot+[ybar, bar width=5.8pt, draw=bartabdiff, fill=bartabdiff] coordinates {(23.3500,0.671455)};
58
+ \addplot+[ybar, bar width=5.8pt, draw=bartabpfgen, fill=bartabpfgen] coordinates {(24.4500,0.686325)};
59
+ \addplot+[ybar, bar width=5.8pt, draw=bartabsyn, fill=bartabsyn] coordinates {(25.5500,0.710633)};
60
+ \addplot+[ybar, bar width=5.8pt, draw=bartvae, fill=bartvae] coordinates {(26.6500,0.664407)};
61
+ \draw[dashed, gray!70, line width=0.6pt] (axis cs:13.8250,0) -- (axis cs:13.8250,1.08);
62
+ \node[anchor=south, font=\bfseries\small] at (axis cs:6.0500,1.035) {Internal profile stability};
63
+ \node[anchor=south, font=\bfseries\small] at (axis cs:20.6000,1.035) {Subgroup size stability};
64
+ \end{axis}
65
+ \end{tikzpicture}
66
+ \end{document}
evaluation/query_family/subgroup/figures/subgroup_model_subitem_heatmap_appendix.tex ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \documentclass{standalone}
2
+ \usepackage[table]{xcolor}
3
+ \usepackage{xcolor}
4
+ \usepackage{booktabs}
5
+
6
+ \begin{document}
7
+ \scriptsize
8
+ \textbf{Subgroup model-subitem heatmap}\\[0.4em]
9
+ \emph{Mean score, 0--1; missing cells stay white.}\\[0.5em]
10
+ \setlength{\tabcolsep}{4pt}
11
+ \begin{tabular}{lccccccccccc}
12
+ \toprule
13
+ Subitem & ARF & BayesNet & CTGAN & ForestDiffusion & RealTabFormer & TabbyFlow & TabDDPM & TabDiff & TabPFGen & TabSyn & TVAE \\
14
+ \midrule
15
+ Internal profile stability & \cellcolor[HTML]{2075B3} & \cellcolor[HTML]{2070B0} & \cellcolor[HTML]{1E83BA} & \cellcolor[HTML]{2094C0} & \cellcolor[HTML]{2350A1} & \cellcolor[HTML]{1F93C0} & \cellcolor[HTML]{289CC1} & \cellcolor[HTML]{1E86BB} & \cellcolor[HTML]{1F82B9} & \cellcolor[HTML]{2075B3} & \cellcolor[HTML]{1F93C0} \\
16
+ Subgroup size stability & \cellcolor[HTML]{216DAF} & \cellcolor[HTML]{216BAE} & \cellcolor[HTML]{1F78B4} & \cellcolor[HTML]{1F82B9} & \cellcolor[HTML]{234B9F} & \cellcolor[HTML]{1D8DBE} & \cellcolor[HTML]{2498C1} & \cellcolor[HTML]{1F7EB7} & \cellcolor[HTML]{1F78B4} & \cellcolor[HTML]{206EB0} & \cellcolor[HTML]{1F80B8} \\
17
+ Family mean & \cellcolor[HTML]{2075B3} & \cellcolor[HTML]{2070B0} & \cellcolor[HTML]{1F80B8} & \cellcolor[HTML]{1D8EBF} & \cellcolor[HTML]{2350A1} & \cellcolor[HTML]{1D90C0} & \cellcolor[HTML]{289CC1} & \cellcolor[HTML]{1E85BA} & \cellcolor[HTML]{1F80B8} & \cellcolor[HTML]{2075B3} & \cellcolor[HTML]{1D8DBE} \\
18
+ \bottomrule
19
+ \end{tabular}
20
+ \end{document}
evaluation/query_family/subgroup/figures/subgroup_prefix_bars_appendix.tex ADDED
@@ -0,0 +1,77 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \documentclass[tikz,border=4pt]{standalone}
2
+ \usepackage{pgfplots}
3
+ \usepackage{xcolor}
4
+ \usetikzlibrary{patterns}
5
+ \pgfplotsset{compat=1.18}
6
+
7
+ \usepgfplotslibrary{groupplots}
8
+ \definecolor{modelreal}{HTML}{000000}
9
+ \definecolor{modelarf}{HTML}{777777}
10
+ \definecolor{modelbayesnet}{HTML}{CCBB44}
11
+ \definecolor{modelctgan}{HTML}{EE6677}
12
+ \definecolor{modelforestdiffusion}{HTML}{228833}
13
+ \definecolor{modelrealtabformer}{HTML}{332288}
14
+ \definecolor{modeltabbyflow}{HTML}{882255}
15
+ \definecolor{modeltabddpm}{HTML}{EE7733}
16
+ \definecolor{modeltabdiff}{HTML}{AA3377}
17
+ \definecolor{modeltabpfgen}{HTML}{009988}
18
+ \definecolor{modeltabsyn}{HTML}{66CCEE}
19
+ \definecolor{modeltvae}{HTML}{4477AA}
20
+ \begin{document}
21
+ \begin{tikzpicture}
22
+ \begin{groupplot}[
23
+ group style={group size=3 by 1, horizontal sep=1.15cm},
24
+ width=5.0cm,
25
+ height=7.0cm,
26
+ ymin=0.0, ymax=1.0,
27
+ ymajorgrids,
28
+ grid style={draw=gray!20},
29
+ major grid style={draw=gray!30},
30
+ symbolic x coords={REAL,ARF,BayesNet,CTGAN,ForestDiffusion,RealTabFormer,TabbyFlow,TabDDPM,TabDiff,TabPFGen,TabSyn,TVAE},
31
+ xtick=data,
32
+ x tick label style={rotate=45, anchor=east, font=\scriptsize},
33
+ tick style={draw=black!70},
34
+ axis line style={draw=black!70},
35
+ ]
36
+ \nextgroupplot[title={Categorical}, ylabel={Subgroup structure score}]
37
+ \addplot+[ybar, bar width=7.0pt, draw=modelreal, fill=modelreal] coordinates { (REAL,1.0000) };
38
+ \addplot+[ybar, bar width=7.0pt, draw=modelarf, fill=modelarf] coordinates { (ARF,0.8708) };
39
+ \addplot+[ybar, bar width=7.0pt, draw=modelbayesnet, fill=modelbayesnet] coordinates { (BayesNet,0.8504) };
40
+ \addplot+[ybar, bar width=7.0pt, draw=modelctgan, fill=modelctgan] coordinates { (CTGAN,0.8287) };
41
+ \addplot+[ybar, bar width=7.0pt, draw=modelforestdiffusion, fill=modelforestdiffusion] coordinates { (ForestDiffusion,0.8008) };
42
+ \addplot+[ybar, bar width=7.0pt, draw=modelrealtabformer, fill=modelrealtabformer] coordinates { (RealTabFormer,0.8995) };
43
+ \addplot+[ybar, bar width=7.0pt, draw=modeltabbyflow, fill=modeltabbyflow] coordinates { (TabbyFlow,0.7579) };
44
+ \addplot+[ybar, bar width=7.0pt, draw=modeltabddpm, fill=modeltabddpm] coordinates { (TabDDPM,0.7889) };
45
+ \addplot+[ybar, bar width=7.0pt, draw=modeltabdiff, fill=modeltabdiff] coordinates { (TabDiff,0.8110) };
46
+ \addplot+[ybar, bar width=7.0pt, draw=modeltabpfgen, fill=modeltabpfgen] coordinates { (TabPFGen,0.8226) };
47
+ \addplot+[ybar, bar width=7.0pt, draw=modeltabsyn, fill=modeltabsyn] coordinates { (TabSyn,0.8282) };
48
+ \addplot+[ybar, bar width=7.0pt, draw=modeltvae, fill=modeltvae] coordinates { (TVAE,0.7619) };
49
+ \nextgroupplot[title={Mixed}, ylabel={}]
50
+ \addplot+[ybar, bar width=7.0pt, draw=modelreal, fill=modelreal] coordinates { (REAL,1.0000) };
51
+ \addplot+[ybar, bar width=7.0pt, draw=modelarf, fill=modelarf] coordinates { (ARF,0.7553) };
52
+ \addplot+[ybar, bar width=7.0pt, draw=modelbayesnet, fill=modelbayesnet] coordinates { (BayesNet,0.7641) };
53
+ \addplot+[ybar, bar width=7.0pt, draw=modelctgan, fill=modelctgan] coordinates { (CTGAN,0.6638) };
54
+ \addplot+[ybar, bar width=7.0pt, draw=modelforestdiffusion, fill=modelforestdiffusion] coordinates { (ForestDiffusion,0.6939) };
55
+ \addplot+[ybar, bar width=7.0pt, draw=modelrealtabformer, fill=modelrealtabformer] coordinates { (RealTabFormer,0.8099) };
56
+ \addplot+[ybar, bar width=7.0pt, draw=modeltabbyflow, fill=modeltabbyflow] coordinates { (TabbyFlow,0.7124) };
57
+ \addplot+[ybar, bar width=7.0pt, draw=modeltabddpm, fill=modeltabddpm] coordinates { (TabDDPM,0.6836) };
58
+ \addplot+[ybar, bar width=7.0pt, draw=modeltabdiff, fill=modeltabdiff] coordinates { (TabDiff,0.7513) };
59
+ \addplot+[ybar, bar width=7.0pt, draw=modeltabpfgen, fill=modeltabpfgen] coordinates { (TabPFGen,0.7511) };
60
+ \addplot+[ybar, bar width=7.0pt, draw=modeltabsyn, fill=modeltabsyn] coordinates { (TabSyn,0.7256) };
61
+ \addplot+[ybar, bar width=7.0pt, draw=modeltvae, fill=modeltvae] coordinates { (TVAE,0.5810) };
62
+ \nextgroupplot[title={Numerical}, ylabel={}]
63
+ \addplot+[ybar, bar width=7.0pt, draw=modelreal, fill=modelreal] coordinates { (REAL,1.0000) };
64
+ \addplot+[ybar, bar width=7.0pt, draw=modelarf, fill=modelarf] coordinates { (ARF,0.4826) };
65
+ \addplot+[ybar, bar width=7.0pt, draw=modelbayesnet, fill=modelbayesnet] coordinates { (BayesNet,0.5236) };
66
+ \addplot+[ybar, bar width=7.0pt, draw=modelctgan, fill=modelctgan] coordinates { (CTGAN,0.4998) };
67
+ \addplot+[ybar, bar width=7.0pt, draw=modelforestdiffusion, fill=modelforestdiffusion] coordinates { (ForestDiffusion,0.4233) };
68
+ \addplot+[ybar, bar width=7.0pt, draw=modelrealtabformer, fill=modelrealtabformer] coordinates { (RealTabFormer,0.6694) };
69
+ \addplot+[ybar, bar width=7.0pt, draw=modeltabbyflow, fill=modeltabbyflow] coordinates { (TabbyFlow,0.4325) };
70
+ \addplot+[ybar, bar width=7.0pt, draw=modeltabddpm, fill=modeltabddpm] coordinates { (TabDDPM,0.3743) };
71
+ \addplot+[ybar, bar width=7.0pt, draw=modeltabdiff, fill=modeltabdiff] coordinates { (TabDiff,0.4578) };
72
+ \addplot+[ybar, bar width=7.0pt, draw=modeltabpfgen, fill=modeltabpfgen] coordinates { (TabPFGen,0.4696) };
73
+ \addplot+[ybar, bar width=7.0pt, draw=modeltabsyn, fill=modeltabsyn] coordinates { (TabSyn,0.4737) };
74
+ \addplot+[ybar, bar width=7.0pt, draw=modeltvae, fill=modeltvae] coordinates { (TVAE,0.5392) };
75
+ \end{groupplot}
76
+ \end{tikzpicture}
77
+ \end{document}
evaluation/query_family/subgroup/figures/subgroup_tradeoff_scatter_main.tex ADDED
@@ -0,0 +1,116 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \documentclass[tikz,border=4pt]{standalone}
2
+ \usepackage{pgfplots}
3
+ \usepackage{xcolor}
4
+ \usetikzlibrary{patterns}
5
+ \pgfplotsset{compat=1.18}
6
+
7
+ \definecolor{modelreal}{HTML}{000000}
8
+ \definecolor{modelarf}{HTML}{777777}
9
+ \definecolor{modelbayesnet}{HTML}{CCBB44}
10
+ \definecolor{modelctgan}{HTML}{EE6677}
11
+ \definecolor{modelforestdiffusion}{HTML}{228833}
12
+ \definecolor{modelrealtabformer}{HTML}{332288}
13
+ \definecolor{modeltabbyflow}{HTML}{882255}
14
+ \definecolor{modeltabddpm}{HTML}{EE7733}
15
+ \definecolor{modeltabdiff}{HTML}{AA3377}
16
+ \definecolor{modeltabpfgen}{HTML}{009988}
17
+ \definecolor{modeltabsyn}{HTML}{66CCEE}
18
+ \definecolor{modeltvae}{HTML}{4477AA}
19
+ \begin{document}
20
+ \begin{tikzpicture}
21
+ \begin{axis}[
22
+ width=14.6cm,
23
+ height=8.4cm,
24
+ ymin=0.0, ymax=1.03,
25
+ xlabel={Model},
26
+ ylabel={Score},
27
+ ymajorgrids,
28
+ grid style={draw=gray!20},
29
+ major grid style={draw=gray!30},
30
+ axis line style={draw=black!70},
31
+ tick style={draw=black!70},
32
+ symbolic x coords={REAL,ARF,BayesNet,CTGAN,ForestDiffusion,RealTabFormer,TabbyFlow,TabDDPM,TabDiff,TabPFGen,TabSyn,TVAE},
33
+ xtick=data,
34
+ xticklabel style={rotate=45, anchor=east, font=\scriptsize},
35
+ legend style={draw=none, fill=none, font=\scriptsize, at={(0.98,0.98)}, anchor=north east},
36
+ ]
37
+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modelreal, fill=modelreal,
38
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
39
+ coordinates { (REAL,1.0000) +- (0,0.0000) };
40
+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modelreal, fill=white, pattern=north east lines, pattern color=modelreal,
41
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
42
+ coordinates { (REAL,1.0000) +- (0,0.0000) };
43
+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modelarf, fill=modelarf,
44
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
45
+ coordinates { (ARF,0.6918) +- (0,0.0974) };
46
+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modelarf, fill=white, pattern=north east lines, pattern color=modelarf,
47
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
48
+ coordinates { (ARF,0.7113) +- (0,0.0955) };
49
+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modelbayesnet, fill=modelbayesnet,
50
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
51
+ coordinates { (BayesNet,0.7053) +- (0,0.0921) };
52
+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modelbayesnet, fill=white, pattern=north east lines, pattern color=modelbayesnet,
53
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
54
+ coordinates { (BayesNet,0.7179) +- (0,0.0911) };
55
+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modelctgan, fill=modelctgan,
56
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
57
+ coordinates { (CTGAN,0.6580) +- (0,0.0991) };
58
+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modelctgan, fill=white, pattern=north east lines, pattern color=modelctgan,
59
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
60
+ coordinates { (CTGAN,0.6843) +- (0,0.0900) };
61
+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modelforestdiffusion, fill=modelforestdiffusion,
62
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
63
+ coordinates { (ForestDiffusion,0.6142) +- (0,0.0965) };
64
+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modelforestdiffusion, fill=white, pattern=north east lines, pattern color=modelforestdiffusion,
65
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
66
+ coordinates { (ForestDiffusion,0.6602) +- (0,0.0949) };
67
+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modelrealtabformer, fill=modelrealtabformer,
68
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
69
+ coordinates { (RealTabFormer,0.7898) +- (0,0.0736) };
70
+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modelrealtabformer, fill=white, pattern=north east lines, pattern color=modelrealtabformer,
71
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
72
+ coordinates { (RealTabFormer,0.8049) +- (0,0.0690) };
73
+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modeltabbyflow, fill=modeltabbyflow,
74
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
75
+ coordinates { (TabbyFlow,0.6180) +- (0,0.0966) };
76
+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modeltabbyflow, fill=white, pattern=north east lines, pattern color=modeltabbyflow,
77
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
78
+ coordinates { (TabbyFlow,0.6355) +- (0,0.0958) };
79
+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modeltabddpm, fill=modeltabddpm,
80
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
81
+ coordinates { (TabDDPM,0.5865) +- (0,0.1158) };
82
+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modeltabddpm, fill=white, pattern=north east lines, pattern color=modeltabddpm,
83
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
84
+ coordinates { (TabDDPM,0.6013) +- (0,0.1107) };
85
+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modeltabdiff, fill=modeltabdiff,
86
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
87
+ coordinates { (TabDiff,0.6492) +- (0,0.0996) };
88
+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modeltabdiff, fill=white, pattern=north east lines, pattern color=modeltabdiff,
89
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
90
+ coordinates { (TabDiff,0.6715) +- (0,0.0995) };
91
+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modeltabpfgen, fill=modeltabpfgen,
92
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
93
+ coordinates { (TabPFGen,0.6634) +- (0,0.1035) };
94
+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modeltabpfgen, fill=white, pattern=north east lines, pattern color=modeltabpfgen,
95
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
96
+ coordinates { (TabPFGen,0.6863) +- (0,0.1056) };
97
+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modeltabsyn, fill=modeltabsyn,
98
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
99
+ coordinates { (TabSyn,0.6938) +- (0,0.1007) };
100
+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modeltabsyn, fill=white, pattern=north east lines, pattern color=modeltabsyn,
101
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
102
+ coordinates { (TabSyn,0.7106) +- (0,0.1012) };
103
+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modeltvae, fill=modeltvae,
104
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
105
+ coordinates { (TVAE,0.6191) +- (0,0.0918) };
106
+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modeltvae, fill=white, pattern=north east lines, pattern color=modeltvae,
107
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
108
+ coordinates { (TVAE,0.6644) +- (0,0.0854) };
109
+ \addlegendimage{area legend, draw=black, fill=black}
110
+ \addlegendentry{Internal profile stability}
111
+ \addlegendimage{area legend, draw=black, fill=white, pattern=north east lines, pattern color=black}
112
+ \addlegendentry{Subgroup size stability}
113
+ \node[anchor=west, font=\scriptsize] at (rel axis cs:0.02,0.90) {$\uparrow$ better};
114
+ \end{axis}
115
+ \end{tikzpicture}
116
+ \end{document}
evaluation/query_family/subgroup/final/README.md ADDED
@@ -0,0 +1,48 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Subgroup Breakdown Final
2
+
3
+ This directory contains the paper-facing subgroup breakdown artifacts for `v2_current` (`v2`), with the standardized must-do bundle mirrored into `final/must_do/` and `final/v2/must_do/`.
4
+
5
+ Primary paper-facing files:
6
+
7
+ - `subgroup_tradeoff_scatter_main__v2.tex`
8
+ - `subgroup_tradeoff_scatter_main__v2.pdf`
9
+ - `subgroup_tradeoff_scatter_main__v2.png`
10
+ - `subgroup_branch_dumbbell_main__v2.tex`
11
+ - `subgroup_branch_dumbbell_main__v2.pdf`
12
+ - `subgroup_branch_dumbbell_main__v2.png`
13
+ - `subgroup_prefix_bars_appendix__v2.tex`
14
+ - `subgroup_prefix_bars_appendix__v2.pdf`
15
+ - `subgroup_prefix_bars_appendix__v2.png`
16
+ - `subgroup_dataset_model_heatmap_appendix__v2.tex`
17
+ - `subgroup_dataset_model_heatmap_appendix__v2.pdf`
18
+ - `subgroup_dataset_model_heatmap_appendix__v2.png`
19
+ - `subgroup_model_subitem_heatmap_appendix__v2.tex`
20
+ - `subgroup_model_subitem_heatmap_appendix__v2.pdf`
21
+ - `subgroup_model_subitem_heatmap_appendix__v2.png`
22
+ - `subgroup_family_subitem_bars_appendix__v2.tex`
23
+ - `subgroup_family_subitem_bars_appendix__v2.pdf`
24
+ - `subgroup_family_subitem_bars_appendix__v2.png`
25
+ - `subgroup_model_summary_generated__v2.tex`
26
+ - `model_summary__v2.csv`
27
+ - `prefix_summary__v2.csv`
28
+
29
+ Must-do bundle (`must_do/`):
30
+
31
+ - `must_do/subgroup_tradeoff_scatter_main__v2.tex`
32
+ - `must_do/subgroup_tradeoff_scatter_main__v2.pdf`
33
+ - `must_do/subgroup_tradeoff_scatter_main__v2.png`
34
+ - `must_do/subgroup_prefix_bars_appendix__v2.tex`
35
+ - `must_do/subgroup_prefix_bars_appendix__v2.pdf`
36
+ - `must_do/subgroup_prefix_bars_appendix__v2.png`
37
+ - `must_do/subgroup_dataset_model_heatmap_appendix__v2.tex`
38
+ - `must_do/subgroup_dataset_model_heatmap_appendix__v2.pdf`
39
+ - `must_do/subgroup_dataset_model_heatmap_appendix__v2.png`
40
+ - `must_do/subgroup_model_subitem_heatmap_appendix__v2.tex`
41
+ - `must_do/subgroup_model_subitem_heatmap_appendix__v2.pdf`
42
+ - `must_do/subgroup_model_subitem_heatmap_appendix__v2.png`
43
+ - `must_do/subgroup_family_subitem_bars_appendix__v2.tex`
44
+ - `must_do/subgroup_family_subitem_bars_appendix__v2.pdf`
45
+ - `must_do/subgroup_family_subitem_bars_appendix__v2.png`
46
+
47
+ The active SQL source for this final bundle is `v2_current` (`v2`).
48
+ The `.tex` files are standalone LaTeX sources. The `.pdf/.png` files are immediate previews for reading in the current environment.
evaluation/query_family/subgroup/final/analysis_report__v2.md ADDED
@@ -0,0 +1,36 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Subgroup Breakdown Report
2
+
3
+ ## Scope
4
+
5
+ - Source analysis run: `20260526_v2_official20_plus_c2patch_plus_subgroupconditionalrepair_merged49`
6
+ - Family analyzed: `subgroup_structure`
7
+ - Excluded models: `cdtd, codi, goggle`
8
+ - Included models: `12`
9
+ - Deduplicated dataset-model panels: `559`
10
+ - Subgroup query rows used: `12515`
11
+
12
+ ## Canonical decomposition
13
+
14
+ - `subgroup_structure = 0.5 * internal_profile_stability + 0.5 * subgroup_size_stability`
15
+ - `internal_profile_stability` captures subgroup-internal feature/distribution behavior.
16
+ - `subgroup_size_stability` captures whether subgroup support/size structure is preserved.
17
+
18
+ ## Main findings
19
+
20
+ 1. `REAL` is the expected perfect upper bound with subgroup score `1.000`. Among synthetic generators, `RealTabFormer` is strongest with mean subgroup score `0.790` across `49` datasets.
21
+ 2. `BayesNet` leans most toward internal-profile preservation (profile minus size = `0.002`), while `ForestDiffusion` is the clearest size-heavy model (profile minus size = `-0.033`).
22
+ 3. `TabDDPM` is the most balanced model between the two subgroup branches with mean absolute branch gap `0.000`.
23
+ 4. Dataset difficulty is uneven: `n9` is the hardest dataset on subgroup score (`0.091` mean across models), while `c3` is the easiest (`1.000`).
24
+
25
+ ## Files to use first
26
+
27
+ - `figures/subgroup_tradeoff_scatter_main.pdf`
28
+ - `figures/subgroup_branch_dumbbell_main.pdf`
29
+ - `figures/subgroup_prefix_bars_appendix.pdf`
30
+ - `tables/subgroup_model_summary_generated.tex`
31
+ - `data/model_summary.csv`
32
+
33
+ ## Prefix note
34
+
35
+ - Prefix coverage summary rows: `36`
36
+ - The `c / m / n` split is exported explicitly because subgroup behavior differs by dataset family, not just by overall model average.
evaluation/query_family/subgroup/final/model_summary__v2.csv ADDED
@@ -0,0 +1,13 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ model_id,model_label,dataset_count,dataset_prefixes,internal_profile_stability__mean,internal_profile_stability__std,internal_profile_stability__se,internal_profile_stability__ci95_low,internal_profile_stability__ci95_high,internal_profile_stability__ci95_radius,subgroup_size_stability__mean,subgroup_size_stability__std,subgroup_size_stability__se,subgroup_size_stability__ci95_low,subgroup_size_stability__ci95_high,subgroup_size_stability__ci95_radius,subgroup_structure_score__mean,subgroup_structure_score__std,subgroup_structure_score__se,subgroup_structure_score__ci95_low,subgroup_structure_score__ci95_high,subgroup_structure_score__ci95_radius,profile_minus_size__mean,profile_minus_size__std,profile_minus_size__se,profile_minus_size__ci95_low,profile_minus_size__ci95_high,profile_minus_size__ci95_radius
2
+ real,REAL,49,"c,m,n",1.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
3
+ arf,ARF,49,"c,m,n",0.691823,0.347951,0.049707,0.594396,0.789249,0.097426,0.711284,0.337711,0.048744,0.615744,0.806823,0.095539,0.694374,0.345097,0.0493,0.597746,0.791001,0.096627,-0.005208,0.097578,0.014084,-0.032813,0.022397,0.027605
4
+ bayesnet,BayesNet,49,"c,m,n",0.705327,0.328912,0.046987,0.613232,0.797423,0.092095,0.71791,0.32201,0.046478,0.626813,0.809007,0.091097,0.704299,0.328232,0.04689,0.612394,0.796204,0.091905,0.002099,0.098408,0.014204,-0.025741,0.029939,0.02784
5
+ ctgan,CTGAN,49,"c,m,n",0.657997,0.353802,0.050543,0.558933,0.757062,0.099065,0.684272,0.318042,0.045905,0.594298,0.774247,0.089975,0.664152,0.335732,0.047962,0.570147,0.758157,0.094005,-0.012567,0.130527,0.01884,-0.049493,0.024359,0.036926
6
+ forestdiffusion,ForestDiffusion,49,"c,m,n",0.614168,0.344612,0.04923,0.517677,0.71066,0.096491,0.660166,0.335519,0.048428,0.565247,0.755085,0.094919,0.630431,0.340664,0.048666,0.535045,0.725817,0.095386,-0.033202,0.108514,0.015663,-0.063901,-0.002503,0.030699
7
+ realtabformer,RealTabFormer,49,"c,m,n",0.789807,0.262948,0.037564,0.716182,0.863433,0.073625,0.804929,0.243997,0.035218,0.735901,0.873956,0.069027,0.79015,0.260209,0.037173,0.717291,0.863008,0.072859,-0.0007,0.067493,0.009742,-0.019794,0.018394,0.019094
8
+ tabbyflow,TabbyFlow,46,"c,m,n",0.618007,0.334339,0.049296,0.521388,0.714626,0.096619,0.635508,0.33154,0.048883,0.539698,0.731319,0.09581,0.626758,0.330113,0.048673,0.531359,0.722156,0.095398,-0.017501,0.086621,0.012772,-0.042533,0.007531,0.025032
9
+ tabddpm,TabDDPM,40,"c,m,n",0.586464,0.373769,0.059098,0.470632,0.702296,0.115832,0.601335,0.352847,0.056501,0.490594,0.712077,0.110742,0.586383,0.363952,0.057546,0.473593,0.699173,0.11279,0.000167,0.102626,0.016433,-0.032043,0.032376,0.032209
10
+ tabdiff,TabDiff,44,"c,m,n",0.649159,0.336942,0.050796,0.549599,0.748719,0.09956,0.671455,0.332929,0.050771,0.571943,0.770966,0.099511,0.652927,0.337062,0.050814,0.553331,0.752522,0.099596,-0.00771,0.092258,0.014069,-0.035286,0.019865,0.027576
11
+ tabpfgen,TabPFGen,46,"c,m,n",0.663403,0.358289,0.052827,0.559863,0.766944,0.103541,0.686325,0.361571,0.0539,0.580682,0.791969,0.105644,0.667404,0.359994,0.053078,0.563371,0.771437,0.104033,-0.00818,0.121754,0.01815,-0.043754,0.027394,0.035574
12
+ tabsyn,TabSyn,40,"c,m,n",0.693785,0.324861,0.051365,0.593109,0.79446,0.100676,0.710633,0.322337,0.051615,0.609467,0.811799,0.101166,0.693614,0.326967,0.051698,0.592286,0.794942,0.101328,0.00035,0.09902,0.015856,-0.030727,0.031428,0.031077
13
+ tvae,TVAE,49,"c,m,n",0.61906,0.327773,0.046825,0.527283,0.710836,0.091776,0.664407,0.301879,0.043572,0.579005,0.749809,0.085402,0.634954,0.314432,0.044919,0.546913,0.722995,0.088041,-0.03245,0.127273,0.01837,-0.068456,0.003555,0.036006
evaluation/query_family/subgroup/final/prefix_summary__v2.csv ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ model_id,model_label,dataset_prefix,dataset_count,internal_profile_stability,subgroup_size_stability,subgroup_structure_score,profile_minus_size
2
+ real,REAL,c,19,1.0,1.0,1.0,0.0
3
+ real,REAL,m,11,1.0,1.0,1.0,0.0
4
+ real,REAL,n,19,1.0,1.0,1.0,0.0
5
+ arf,ARF,c,19,0.873723,0.867941,0.870832,0.005782
6
+ arf,ARF,m,11,0.737465,0.773149,0.755307,-0.035684
7
+ arf,ARF,n,19,0.483498,0.508116,0.482638,0.001816
8
+ bayesnet,BayesNet,c,19,0.85064,0.850136,0.850388,0.000505
9
+ bayesnet,BayesNet,m,11,0.754427,0.773684,0.764055,-0.019257
10
+ bayesnet,BayesNet,n,19,0.531589,0.544254,0.523615,0.016834
11
+ ctgan,CTGAN,c,19,0.830826,0.826636,0.828731,0.004189
12
+ ctgan,CTGAN,m,11,0.627338,0.700176,0.663757,-0.072838
13
+ ctgan,CTGAN,n,19,0.502919,0.52428,0.499803,0.006578
14
+ forestdiffusion,ForestDiffusion,c,19,0.78309,0.818577,0.800834,-0.035487
15
+ forestdiffusion,ForestDiffusion,m,11,0.667279,0.72048,0.69388,-0.053201
16
+ forestdiffusion,ForestDiffusion,n,19,0.414499,0.456095,0.423294,-0.018569
17
+ realtabformer,RealTabFormer,c,19,0.905805,0.893119,0.899462,0.012687
18
+ realtabformer,RealTabFormer,m,11,0.808946,0.810894,0.80992,-0.001948
19
+ realtabformer,RealTabFormer,n,19,0.662728,0.708194,0.669392,-0.014067
20
+ tabbyflow,TabbyFlow,c,18,0.755472,0.76033,0.757901,-0.004858
21
+ tabbyflow,TabbyFlow,m,11,0.696738,0.728005,0.712372,-0.031267
22
+ tabbyflow,TabbyFlow,n,17,0.421512,0.443493,0.432503,-0.021981
23
+ tabddpm,TabDDPM,c,13,0.797139,0.780626,0.788882,0.016514
24
+ tabddpm,TabDDPM,m,10,0.675513,0.691741,0.683627,-0.016228
25
+ tabddpm,TabDDPM,n,17,0.372978,0.399158,0.374328,-0.002869
26
+ tabdiff,TabDiff,c,16,0.814657,0.807329,0.810993,0.007328
27
+ tabdiff,TabDiff,m,10,0.736522,0.766033,0.751277,-0.029511
28
+ tabdiff,TabDiff,n,18,0.453516,0.487939,0.457785,-0.00904
29
+ tabpfgen,TabPFGen,c,17,0.832439,0.812847,0.822643,0.019592
30
+ tabpfgen,TabPFGen,m,11,0.714777,0.7875,0.751138,-0.072723
31
+ tabpfgen,TabPFGen,n,18,0.472363,0.494338,0.469619,0.005812
32
+ tabsyn,TabSyn,c,17,0.833284,0.823078,0.828181,0.010206
33
+ tabsyn,TabSyn,m,11,0.712105,0.73902,0.725563,-0.026915
34
+ tabsyn,TabSyn,n,12,0.479367,0.508467,0.473691,0.012384
35
+ tvae,TVAE,c,19,0.756844,0.767009,0.761926,-0.010165
36
+ tvae,TVAE,m,11,0.554374,0.60763,0.581002,-0.053255
37
+ tvae,TVAE,n,19,0.518725,0.590803,0.539217,-0.043259
evaluation/query_family/subgroup/final/subgroup_branch_dumbbell_main__v2.tex ADDED
@@ -0,0 +1,90 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \documentclass[tikz,border=4pt]{standalone}
2
+ \usepackage{pgfplots}
3
+ \usepackage{xcolor}
4
+ \usetikzlibrary{patterns}
5
+ \pgfplotsset{compat=1.18}
6
+
7
+ \definecolor{modelreal}{HTML}{000000}
8
+ \definecolor{modelarf}{HTML}{777777}
9
+ \definecolor{modelbayesnet}{HTML}{CCBB44}
10
+ \definecolor{modelctgan}{HTML}{EE6677}
11
+ \definecolor{modelforestdiffusion}{HTML}{228833}
12
+ \definecolor{modelrealtabformer}{HTML}{332288}
13
+ \definecolor{modeltabbyflow}{HTML}{882255}
14
+ \definecolor{modeltabddpm}{HTML}{EE7733}
15
+ \definecolor{modeltabdiff}{HTML}{AA3377}
16
+ \definecolor{modeltabpfgen}{HTML}{009988}
17
+ \definecolor{modeltabsyn}{HTML}{66CCEE}
18
+ \definecolor{modeltvae}{HTML}{4477AA}
19
+ \begin{document}
20
+ \begin{tikzpicture}
21
+ \begin{axis}[
22
+ width=13.2cm,
23
+ height=9.8cm,
24
+ xmin=0.15, xmax=1.03,
25
+ ytick={12,11,10,9,8,7,6,5,4,3,2,1},
26
+ yticklabels={REAL,ARF,BayesNet,CTGAN,ForestDiffusion,RealTabFormer,TabbyFlow,TabDDPM,TabDiff,TabPFGen,TabSyn,TVAE},
27
+ y dir=reverse,
28
+ xlabel={Score},
29
+ grid=both,
30
+ grid style={draw=gray!18},
31
+ tick style={draw=black!70},
32
+ legend style={draw=none, fill=none, font=\scriptsize, at={(0.03,0.03)}, anchor=south west},
33
+ ]
34
+ \draw[line width=0.9pt, color=modelreal!70] (axis cs:1.0000,12) -- (axis cs:1.0000,12);
35
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modelreal, fill=modelreal] coordinates { (1.0000,12) };
36
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modelreal, fill=modelreal] coordinates { (1.0000,12) };
37
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (1.0000,12) };
38
+ \draw[line width=0.9pt, color=modelarf!70] (axis cs:0.7113,11) -- (axis cs:0.6918,11);
39
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modelarf, fill=modelarf] coordinates { (0.7113,11) };
40
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modelarf, fill=modelarf] coordinates { (0.6918,11) };
41
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.6944,11) };
42
+ \draw[line width=0.9pt, color=modelbayesnet!70] (axis cs:0.7179,10) -- (axis cs:0.7053,10);
43
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modelbayesnet, fill=modelbayesnet] coordinates { (0.7179,10) };
44
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modelbayesnet, fill=modelbayesnet] coordinates { (0.7053,10) };
45
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.7043,10) };
46
+ \draw[line width=0.9pt, color=modelctgan!70] (axis cs:0.6843,9) -- (axis cs:0.6580,9);
47
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modelctgan, fill=modelctgan] coordinates { (0.6843,9) };
48
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modelctgan, fill=modelctgan] coordinates { (0.6580,9) };
49
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.6642,9) };
50
+ \draw[line width=0.9pt, color=modelforestdiffusion!70] (axis cs:0.6602,8) -- (axis cs:0.6142,8);
51
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modelforestdiffusion, fill=modelforestdiffusion] coordinates { (0.6602,8) };
52
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modelforestdiffusion, fill=modelforestdiffusion] coordinates { (0.6142,8) };
53
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.6304,8) };
54
+ \draw[line width=0.9pt, color=modelrealtabformer!70] (axis cs:0.8049,7) -- (axis cs:0.7898,7);
55
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modelrealtabformer, fill=modelrealtabformer] coordinates { (0.8049,7) };
56
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modelrealtabformer, fill=modelrealtabformer] coordinates { (0.7898,7) };
57
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.7902,7) };
58
+ \draw[line width=0.9pt, color=modeltabbyflow!70] (axis cs:0.6355,6) -- (axis cs:0.6180,6);
59
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modeltabbyflow, fill=modeltabbyflow] coordinates { (0.6355,6) };
60
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modeltabbyflow, fill=modeltabbyflow] coordinates { (0.6180,6) };
61
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.6268,6) };
62
+ \draw[line width=0.9pt, color=modeltabddpm!70] (axis cs:0.6013,5) -- (axis cs:0.5865,5);
63
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modeltabddpm, fill=modeltabddpm] coordinates { (0.6013,5) };
64
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modeltabddpm, fill=modeltabddpm] coordinates { (0.5865,5) };
65
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.5864,5) };
66
+ \draw[line width=0.9pt, color=modeltabdiff!70] (axis cs:0.6715,4) -- (axis cs:0.6492,4);
67
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modeltabdiff, fill=modeltabdiff] coordinates { (0.6715,4) };
68
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modeltabdiff, fill=modeltabdiff] coordinates { (0.6492,4) };
69
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.6529,4) };
70
+ \draw[line width=0.9pt, color=modeltabpfgen!70] (axis cs:0.6863,3) -- (axis cs:0.6634,3);
71
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modeltabpfgen, fill=modeltabpfgen] coordinates { (0.6863,3) };
72
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modeltabpfgen, fill=modeltabpfgen] coordinates { (0.6634,3) };
73
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.6674,3) };
74
+ \draw[line width=0.9pt, color=modeltabsyn!70] (axis cs:0.7106,2) -- (axis cs:0.6938,2);
75
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modeltabsyn, fill=modeltabsyn] coordinates { (0.7106,2) };
76
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modeltabsyn, fill=modeltabsyn] coordinates { (0.6938,2) };
77
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.6936,2) };
78
+ \draw[line width=0.9pt, color=modeltvae!70] (axis cs:0.6644,1) -- (axis cs:0.6191,1);
79
+ \addplot+[only marks, mark=square*, mark size=2.4pt, draw=modeltvae, fill=modeltvae] coordinates { (0.6644,1) };
80
+ \addplot+[only marks, mark=*, mark size=2.6pt, draw=modeltvae, fill=modeltvae] coordinates { (0.6191,1) };
81
+ \addplot+[only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black] coordinates { (0.6350,1) };
82
+ \addlegendimage{only marks, mark=square*, mark size=2.4pt, draw=black, fill=black}
83
+ \addlegendentry{Subgroup size stability}
84
+ \addlegendimage{only marks, mark=*, mark size=2.6pt, draw=black, fill=black}
85
+ \addlegendentry{Internal profile stability}
86
+ \addlegendimage{only marks, mark=diamond*, mark size=2.6pt, draw=black, fill=black}
87
+ \addlegendentry{Canonical subgroup score}
88
+ \end{axis}
89
+ \end{tikzpicture}
90
+ \end{document}
evaluation/query_family/subgroup/final/subgroup_dataset_model_heatmap_appendix__v2.tex ADDED
@@ -0,0 +1,62 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \documentclass{standalone}
2
+ \usepackage[table]{xcolor}
3
+ \usepackage{booktabs}
4
+ \begin{document}
5
+ \scriptsize
6
+ \setlength{\tabcolsep}{4pt}
7
+ \begin{tabular}{lcccccccccccc}
8
+ \toprule
9
+ Dataset & REAL & ARF & BayesNet & CTGAN & ForestDiffusion & RealTabFormer & TabbyFlow & TabDDPM & TabDiff & TabPFGen & TabSyn & TVAE \\
10
+ \midrule
11
+ C2 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{0A1E5C} & \cellcolor[HTML]{091E5A} & \cellcolor[HTML]{0D2161} & \cellcolor[HTML]{0A1E5C} & \cellcolor[HTML]{091E5A} & \cellcolor[HTML]{24409A} & \cellcolor[HTML]{0C2060} & \cellcolor[HTML]{24409A} & \cellcolor[HTML]{243D98} & \cellcolor[HTML]{243392} & \cellcolor[HTML]{0A1E5C} \\
12
+ C3 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} \\
13
+ C4 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{091E5A} & \cellcolor[HTML]{091E5A} & \cellcolor[HTML]{091E5A} & \cellcolor[HTML]{0B1F5E} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{091E5A} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{0C2060} & \cellcolor[HTML]{081D58} \\
14
+ C5 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{243C98} & \cellcolor[HTML]{243F99} & \cellcolor[HTML]{243C98} & \cellcolor[HTML]{24439B} & \cellcolor[HTML]{243C98} & \cellcolor[HTML]{243D98} & \cellcolor[HTML]{24439B} & \cellcolor[HTML]{243C98} & \cellcolor[HTML]{1E2E85} & \cellcolor[HTML]{24409A} & \cellcolor[HTML]{24439B} \\
15
+ C6 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{32A6C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{34A9C3} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{32A6C2} & \cellcolor[HTML]{34A9C3} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{32A6C2} \\
16
+ C7 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{0D2161} & \cellcolor[HTML]{142670} & \cellcolor[HTML]{0D2163} & \cellcolor[HTML]{0C2060} & \cellcolor[HTML]{13266F} & \cellcolor[HTML]{1B2C80} & \cellcolor[HTML]{0D2161} & \cellcolor[HTML]{142670} & \cellcolor[HTML]{13266F} & \cellcolor[HTML]{1B2C80} & \cellcolor[HTML]{142670} \\
17
+ C8 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{0E2265} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{12256D} & \cellcolor[HTML]{12256D} & \cellcolor[HTML]{0E2265} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{11246B} \\
18
+ C9 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{CBEBB4} & \cellcolor[HTML]{C2E7B4} & \cellcolor[HTML]{C2E7B4} & \cellcolor[HTML]{CBEBB4} & \cellcolor[HTML]{0D2163} & \cellcolor[HTML]{CBEBB4} & \cellcolor[HTML]{CBEBB4} & \cellcolor[HTML]{CBEBB4} & \cellcolor[HTML]{CBEBB4} & \cellcolor[HTML]{CBEBB4} & \cellcolor[HTML]{C2E7B4} \\
19
+ C10 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & & \cellcolor[HTML]{102369} \\
20
+ C11 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{102369} & \cellcolor[HTML]{11246B} & \cellcolor[HTML]{152772} & \cellcolor[HTML]{12256D} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{0D2163} & \cellcolor[HTML]{0D2163} & \cellcolor[HTML]{0D2161} & \cellcolor[HTML]{0B1F5E} & \cellcolor[HTML]{0D2163} & \cellcolor[HTML]{0D2161} \\
21
+ C12 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2350A1} & \cellcolor[HTML]{081D58} & & & & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{299DC1} \\
22
+ C13 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{5FC1C0} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2094C0} & \cellcolor[HTML]{102369} & \cellcolor[HTML]{F8FCCA} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{5FC1C0} \\
23
+ C14 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{21318D} & \cellcolor[HTML]{2354A3} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{091E5A} & \cellcolor[HTML]{80CEBB} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{225DA8} \\
24
+ C15 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{253595} & \cellcolor[HTML]{2354A3} & \cellcolor[HTML]{1F78B4} & \cellcolor[HTML]{2070B0} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2165AB} & & \cellcolor[HTML]{2260A9} & \cellcolor[HTML]{2354A3} & \cellcolor[HTML]{2260A9} & \cellcolor[HTML]{32A6C2} \\
25
+ C16 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{243392} & \cellcolor[HTML]{1E8ABD} & \cellcolor[HTML]{243392} & \cellcolor[HTML]{1E8BBD} & \cellcolor[HTML]{243C98} & \cellcolor[HTML]{A7DCB7} & & \cellcolor[HTML]{2DA2C2} & & \cellcolor[HTML]{31A5C2} & \cellcolor[HTML]{5FC1C0} \\
26
+ C17 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2076B3} & \cellcolor[HTML]{2076B3} & \cellcolor[HTML]{142670} & \cellcolor[HTML]{3CB1C3} & \cellcolor[HTML]{32A6C2} & \cellcolor[HTML]{A9DDB7} & & \cellcolor[HTML]{36ABC3} & \cellcolor[HTML]{1F7AB5} & \cellcolor[HTML]{3BB0C3} & \cellcolor[HTML]{243D98} \\
27
+ C18 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{32A6C2} & \cellcolor[HTML]{42B6C4} & \cellcolor[HTML]{269BC1} & \cellcolor[HTML]{4AB9C3} & \cellcolor[HTML]{24419A} & \cellcolor[HTML]{9CD8B8} & & & & & \cellcolor[HTML]{259AC1} \\
28
+ C19 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2258A5} & \cellcolor[HTML]{234DA0} & \cellcolor[HTML]{37ACC3} & \cellcolor[HTML]{1F80B8} & & \cellcolor[HTML]{234DA0} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{22328F} & \cellcolor[HTML]{2352A3} \\
29
+ C20 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2258A5} & & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} \\
30
+ M1 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{21318D} & \cellcolor[HTML]{21308B} & \cellcolor[HTML]{182A7A} & \cellcolor[HTML]{24409A} & \cellcolor[HTML]{162874} & \cellcolor[HTML]{11246B} & \cellcolor[HTML]{162874} & \cellcolor[HTML]{1F7BB6} \\
31
+ M2 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{4EBBC2} & \cellcolor[HTML]{4EBBC2} & \cellcolor[HTML]{4EBBC2} & \cellcolor[HTML]{4EBBC2} & \cellcolor[HTML]{3CB1C3} & \cellcolor[HTML]{55BEC1} & \cellcolor[HTML]{4CBAC2} & & \cellcolor[HTML]{4EBBC2} & \cellcolor[HTML]{4EBBC2} & \cellcolor[HTML]{4EBBC2} \\
32
+ M4 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2259A6} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{13266F} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2259A6} \\
33
+ M5 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{32A6C2} & \cellcolor[HTML]{32A6C2} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{53BDC1} & \cellcolor[HTML]{35AAC3} & \cellcolor[HTML]{37ACC3} & \cellcolor[HTML]{75C9BD} & \cellcolor[HTML]{46B8C3} & \cellcolor[HTML]{2354A3} & \cellcolor[HTML]{37ACC3} & \cellcolor[HTML]{B7E3B6} \\
34
+ M6 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{0B1F5E} & \cellcolor[HTML]{0C2060} & \cellcolor[HTML]{A5DCB7} & \cellcolor[HTML]{24439B} & \cellcolor[HTML]{13266F} & \cellcolor[HTML]{1E2E85} & \cellcolor[HTML]{23499E} & \cellcolor[HTML]{152772} & \cellcolor[HTML]{1D2E83} & \cellcolor[HTML]{172976} & \cellcolor[HTML]{C0E6B5} \\
35
+ M7 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{162874} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{13266F} \\
36
+ M8 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{40B5C4} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{34A9C3} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{6BC6BE} \\
37
+ M9 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{243392} & \cellcolor[HTML]{243392} & \cellcolor[HTML]{243392} & \cellcolor[HTML]{1F7DB6} & \cellcolor[HTML]{12256D} & \cellcolor[HTML]{2DA2C2} & \cellcolor[HTML]{1F7DB6} & \cellcolor[HTML]{1F7EB7} & \cellcolor[HTML]{225CA7} & \cellcolor[HTML]{1F7EB7} & \cellcolor[HTML]{1E85BA} \\
38
+ M10 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{24449C} & \cellcolor[HTML]{233390} & \cellcolor[HTML]{253595} & \cellcolor[HTML]{24459C} & \cellcolor[HTML]{091E5A} & \cellcolor[HTML]{24439B} & \cellcolor[HTML]{2352A3} & \cellcolor[HTML]{24439B} & \cellcolor[HTML]{24449C} & \cellcolor[HTML]{24439B} & \cellcolor[HTML]{253997} \\
39
+ M11 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{61C2BF} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{6FC7BD} & \cellcolor[HTML]{67C4BE} \\
40
+ M12 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2076B3} & \cellcolor[HTML]{2165AB} & \cellcolor[HTML]{1F80B8} & \cellcolor[HTML]{299DC1} & \cellcolor[HTML]{102369} & \cellcolor[HTML]{206EB0} & & \cellcolor[HTML]{2163AA} & \cellcolor[HTML]{216BAE} & \cellcolor[HTML]{2075B3} & \cellcolor[HTML]{1D8EBF} \\
41
+ N1 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{40B5C4} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} \\
42
+ N2 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{C6E9B4} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{C6E9B4} & \cellcolor[HTML]{C6E9B4} & \cellcolor[HTML]{C6E9B4} & \cellcolor[HTML]{081D58} & & \cellcolor[HTML]{081D58} \\
43
+ N3 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{D0EDB3} & \cellcolor[HTML]{D0EDB3} & \cellcolor[HTML]{EEF8B3} & \cellcolor[HTML]{E0F3B2} & \cellcolor[HTML]{40B5C4} & \cellcolor[HTML]{DDF2B2} & \cellcolor[HTML]{DFF2B2} & \cellcolor[HTML]{DDF2B2} & \cellcolor[HTML]{E5F5B2} & \cellcolor[HTML]{CEECB3} & \cellcolor[HTML]{EEF8B3} \\
44
+ N4 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{76CABC} & \cellcolor[HTML]{76CABC} & \cellcolor[HTML]{D5EFB3} & \cellcolor[HTML]{76CABC} & \cellcolor[HTML]{44B7C4} & \cellcolor[HTML]{73C8BD} & \cellcolor[HTML]{CFECB3} & \cellcolor[HTML]{73C8BD} & \cellcolor[HTML]{73C8BD} & & \cellcolor[HTML]{C6E9B4} \\
45
+ N5 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{89D1BA} & \cellcolor[HTML]{46B8C3} & \cellcolor[HTML]{61C2BF} & \cellcolor[HTML]{8CD2BA} & \cellcolor[HTML]{39ADC3} & \cellcolor[HTML]{97D6B9} & \cellcolor[HTML]{EAF7B1} & \cellcolor[HTML]{89D1BA} & \cellcolor[HTML]{8CD2BA} & & \cellcolor[HTML]{67C4BE} \\
46
+ N6 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{D3EEB3} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{D3EEB3} \\
47
+ N7 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{37ACC3} & \cellcolor[HTML]{33A7C2} & \cellcolor[HTML]{33A7C2} & & \cellcolor[HTML]{33A7C2} \\
48
+ N8 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{2296C1} & \cellcolor[HTML]{2498C1} & \cellcolor[HTML]{87D0BA} & \cellcolor[HTML]{35AAC3} & \cellcolor[HTML]{1F7AB5} & \cellcolor[HTML]{2296C1} & & \cellcolor[HTML]{31A5C2} & & \cellcolor[HTML]{31A5C2} & \cellcolor[HTML]{35AAC3} \\
49
+ N9 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & & \cellcolor[HTML]{FFFFD9} \\
50
+ N10 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & & \cellcolor[HTML]{081D58} \\
51
+ N11 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} \\
52
+ N12 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{E8F6B1} & \cellcolor[HTML]{E8F6B1} & \cellcolor[HTML]{1C2D81} & \cellcolor[HTML]{F5FBC2} & \cellcolor[HTML]{0F2367} & \cellcolor[HTML]{F5FBC2} & \cellcolor[HTML]{F5FBC2} & \cellcolor[HTML]{F5FBC2} & \cellcolor[HTML]{F5FBC2} & & \cellcolor[HTML]{182A7A} \\
53
+ N14 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{FEFFD8} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{F1FABB} & & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FCFED3} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FCFED3} & \cellcolor[HTML]{FFFFD9} \\
54
+ N15 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{152772} & \cellcolor[HTML]{0B1F5E} & \cellcolor[HTML]{EDF8B2} & \cellcolor[HTML]{192B7C} & \cellcolor[HTML]{142670} & \cellcolor[HTML]{216AAD} & \cellcolor[HTML]{9ED9B8} & \cellcolor[HTML]{152772} & \cellcolor[HTML]{1B2C80} & \cellcolor[HTML]{152772} & \cellcolor[HTML]{24479D} \\
55
+ N16 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{081D58} \\
56
+ N17 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{F3FABF} & \cellcolor[HTML]{1D90C0} & \cellcolor[HTML]{259AC1} & \cellcolor[HTML]{F8FCCA} & \cellcolor[HTML]{2075B3} & & \cellcolor[HTML]{F4FBC1} & \cellcolor[HTML]{F4FBC1} & \cellcolor[HTML]{F4FBC0} & \cellcolor[HTML]{F8FCCA} & \cellcolor[HTML]{2DA2C2} \\
57
+ N18 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{EAF7B1} & \cellcolor[HTML]{E2F4B2} & \cellcolor[HTML]{E1F3B2} & \cellcolor[HTML]{E7F6B1} & \cellcolor[HTML]{BDE5B5} & \cellcolor[HTML]{E1F3B2} & & \cellcolor[HTML]{E3F4B2} & \cellcolor[HTML]{E8F6B1} & \cellcolor[HTML]{E3F4B2} & \cellcolor[HTML]{E5F5B2} \\
58
+ N19 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{E0F3B2} & \cellcolor[HTML]{CEECB3} & \cellcolor[HTML]{24489D} & \cellcolor[HTML]{F9FDCC} & \cellcolor[HTML]{216DAF} & \cellcolor[HTML]{FBFDD0} & \cellcolor[HTML]{FBFDD0} & \cellcolor[HTML]{EDF8B1} & \cellcolor[HTML]{CBEBB4} & \cellcolor[HTML]{E0F3B2} & \cellcolor[HTML]{1F7AB5} \\
59
+ N20 & \cellcolor[HTML]{081D58} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{2166AC} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} & \cellcolor[HTML]{FFFFD9} \\
60
+ \bottomrule
61
+ \end{tabular}
62
+ \end{document}
evaluation/query_family/subgroup/final/subgroup_family_subitem_bars_appendix__v2.tex ADDED
@@ -0,0 +1,66 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \documentclass[tikz,border=4pt]{standalone}
2
+ \usepackage{pgfplots}
3
+ \usepackage{xcolor}
4
+ \pgfplotsset{compat=1.18}
5
+
6
+ \definecolor{barreal}{HTML}{000000}
7
+ \definecolor{bararf}{HTML}{777777}
8
+ \definecolor{barbayesnet}{HTML}{CCBB44}
9
+ \definecolor{barctgan}{HTML}{EE6677}
10
+ \definecolor{barforestdiffusion}{HTML}{228833}
11
+ \definecolor{barrealtabformer}{HTML}{332288}
12
+ \definecolor{bartabbyflow}{HTML}{882255}
13
+ \definecolor{bartabddpm}{HTML}{EE7733}
14
+ \definecolor{bartabdiff}{HTML}{AA3377}
15
+ \definecolor{bartabpfgen}{HTML}{009988}
16
+ \definecolor{bartabsyn}{HTML}{66CCEE}
17
+ \definecolor{bartvae}{HTML}{4477AA}
18
+ \begin{document}
19
+ \begin{tikzpicture}
20
+ \begin{axis}[
21
+ width=13.50cm,
22
+ height=8.8cm,
23
+ ymin=0.0, ymax=1.08,
24
+ ylabel={Score},
25
+ title={Subgroup family and subitem bars},
26
+ ymajorgrids,
27
+ grid style={draw=gray!22},
28
+ major grid style={draw=gray!30},
29
+ axis line style={draw=black!70},
30
+ tick style={draw=black!70},
31
+ xtick={0.0000,1.1000,2.2000,3.3000,4.4000,5.5000,6.6000,7.7000,8.8000,9.9000,11.0000,12.1000,14.5500,15.6500,16.7500,17.8500,18.9500,20.0500,21.1500,22.2500,23.3500,24.4500,25.5500,26.6500},
32
+ xticklabels={REAL,ARF,BayesNet,CTGAN,ForestDiffusion,RealTabFormer,TabbyFlow,TabDDPM,TabDiff,TabPFGen,TabSyn,TVAE,REAL,ARF,BayesNet,CTGAN,ForestDiffusion,RealTabFormer,TabbyFlow,TabDDPM,TabDiff,TabPFGen,TabSyn,TVAE},
33
+ x tick label style={rotate=90, anchor=east, font=\scriptsize},
34
+ enlarge x limits=0.01,
35
+ clip=false,
36
+ ]
37
+ \addplot+[ybar, bar width=5.8pt, draw=barreal, fill=barreal] coordinates {(0.0000,1.000000)};
38
+ \addplot+[ybar, bar width=5.8pt, draw=bararf, fill=bararf] coordinates {(1.1000,0.691823)};
39
+ \addplot+[ybar, bar width=5.8pt, draw=barbayesnet, fill=barbayesnet] coordinates {(2.2000,0.705327)};
40
+ \addplot+[ybar, bar width=5.8pt, draw=barctgan, fill=barctgan] coordinates {(3.3000,0.657997)};
41
+ \addplot+[ybar, bar width=5.8pt, draw=barforestdiffusion, fill=barforestdiffusion] coordinates {(4.4000,0.614168)};
42
+ \addplot+[ybar, bar width=5.8pt, draw=barrealtabformer, fill=barrealtabformer] coordinates {(5.5000,0.789807)};
43
+ \addplot+[ybar, bar width=5.8pt, draw=bartabbyflow, fill=bartabbyflow] coordinates {(6.6000,0.618007)};
44
+ \addplot+[ybar, bar width=5.8pt, draw=bartabddpm, fill=bartabddpm] coordinates {(7.7000,0.586464)};
45
+ \addplot+[ybar, bar width=5.8pt, draw=bartabdiff, fill=bartabdiff] coordinates {(8.8000,0.649159)};
46
+ \addplot+[ybar, bar width=5.8pt, draw=bartabpfgen, fill=bartabpfgen] coordinates {(9.9000,0.663403)};
47
+ \addplot+[ybar, bar width=5.8pt, draw=bartabsyn, fill=bartabsyn] coordinates {(11.0000,0.693785)};
48
+ \addplot+[ybar, bar width=5.8pt, draw=bartvae, fill=bartvae] coordinates {(12.1000,0.619060)};
49
+ \addplot+[ybar, bar width=5.8pt, draw=barreal, fill=barreal] coordinates {(14.5500,1.000000)};
50
+ \addplot+[ybar, bar width=5.8pt, draw=bararf, fill=bararf] coordinates {(15.6500,0.711284)};
51
+ \addplot+[ybar, bar width=5.8pt, draw=barbayesnet, fill=barbayesnet] coordinates {(16.7500,0.717910)};
52
+ \addplot+[ybar, bar width=5.8pt, draw=barctgan, fill=barctgan] coordinates {(17.8500,0.684272)};
53
+ \addplot+[ybar, bar width=5.8pt, draw=barforestdiffusion, fill=barforestdiffusion] coordinates {(18.9500,0.660166)};
54
+ \addplot+[ybar, bar width=5.8pt, draw=barrealtabformer, fill=barrealtabformer] coordinates {(20.0500,0.804929)};
55
+ \addplot+[ybar, bar width=5.8pt, draw=bartabbyflow, fill=bartabbyflow] coordinates {(21.1500,0.635508)};
56
+ \addplot+[ybar, bar width=5.8pt, draw=bartabddpm, fill=bartabddpm] coordinates {(22.2500,0.601335)};
57
+ \addplot+[ybar, bar width=5.8pt, draw=bartabdiff, fill=bartabdiff] coordinates {(23.3500,0.671455)};
58
+ \addplot+[ybar, bar width=5.8pt, draw=bartabpfgen, fill=bartabpfgen] coordinates {(24.4500,0.686325)};
59
+ \addplot+[ybar, bar width=5.8pt, draw=bartabsyn, fill=bartabsyn] coordinates {(25.5500,0.710633)};
60
+ \addplot+[ybar, bar width=5.8pt, draw=bartvae, fill=bartvae] coordinates {(26.6500,0.664407)};
61
+ \draw[dashed, gray!70, line width=0.6pt] (axis cs:13.8250,0) -- (axis cs:13.8250,1.08);
62
+ \node[anchor=south, font=\bfseries\small] at (axis cs:6.0500,1.035) {Internal profile stability};
63
+ \node[anchor=south, font=\bfseries\small] at (axis cs:20.6000,1.035) {Subgroup size stability};
64
+ \end{axis}
65
+ \end{tikzpicture}
66
+ \end{document}
evaluation/query_family/subgroup/final/subgroup_model_subitem_heatmap_appendix__v2.tex ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \documentclass{standalone}
2
+ \usepackage[table]{xcolor}
3
+ \usepackage{xcolor}
4
+ \usepackage{booktabs}
5
+
6
+ \begin{document}
7
+ \scriptsize
8
+ \textbf{Subgroup model-subitem heatmap}\\[0.4em]
9
+ \emph{Mean score, 0--1; missing cells stay white.}\\[0.5em]
10
+ \setlength{\tabcolsep}{4pt}
11
+ \begin{tabular}{lccccccccccc}
12
+ \toprule
13
+ Subitem & ARF & BayesNet & CTGAN & ForestDiffusion & RealTabFormer & TabbyFlow & TabDDPM & TabDiff & TabPFGen & TabSyn & TVAE \\
14
+ \midrule
15
+ Internal profile stability & \cellcolor[HTML]{2075B3} & \cellcolor[HTML]{2070B0} & \cellcolor[HTML]{1E83BA} & \cellcolor[HTML]{2094C0} & \cellcolor[HTML]{2350A1} & \cellcolor[HTML]{1F93C0} & \cellcolor[HTML]{289CC1} & \cellcolor[HTML]{1E86BB} & \cellcolor[HTML]{1F82B9} & \cellcolor[HTML]{2075B3} & \cellcolor[HTML]{1F93C0} \\
16
+ Subgroup size stability & \cellcolor[HTML]{216DAF} & \cellcolor[HTML]{216BAE} & \cellcolor[HTML]{1F78B4} & \cellcolor[HTML]{1F82B9} & \cellcolor[HTML]{234B9F} & \cellcolor[HTML]{1D8DBE} & \cellcolor[HTML]{2498C1} & \cellcolor[HTML]{1F7EB7} & \cellcolor[HTML]{1F78B4} & \cellcolor[HTML]{206EB0} & \cellcolor[HTML]{1F80B8} \\
17
+ Family mean & \cellcolor[HTML]{2075B3} & \cellcolor[HTML]{2070B0} & \cellcolor[HTML]{1F80B8} & \cellcolor[HTML]{1D8EBF} & \cellcolor[HTML]{2350A1} & \cellcolor[HTML]{1D90C0} & \cellcolor[HTML]{289CC1} & \cellcolor[HTML]{1E85BA} & \cellcolor[HTML]{1F80B8} & \cellcolor[HTML]{2075B3} & \cellcolor[HTML]{1D8DBE} \\
18
+ \bottomrule
19
+ \end{tabular}
20
+ \end{document}
evaluation/query_family/subgroup/final/subgroup_model_summary_generated__v2.tex ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \begin{tabular}{lrrrr}
2
+ \toprule
3
+ Model & Subgroup score & Internal profile & Subgroup size & Datasets \\
4
+ \midrule
5
+ REAL & 1.000 & 1.000 & 1.000 & 49 \\
6
+ ARF & 0.694 & 0.692 & 0.711 & 49 \\
7
+ BayesNet & 0.704 & 0.705 & 0.718 & 49 \\
8
+ CTGAN & 0.664 & 0.658 & 0.684 & 49 \\
9
+ ForestDiffusion & 0.630 & 0.614 & 0.660 & 49 \\
10
+ RealTabFormer & 0.790 & 0.790 & 0.805 & 49 \\
11
+ TabbyFlow & 0.627 & 0.618 & 0.636 & 46 \\
12
+ TabDDPM & 0.586 & 0.586 & 0.601 & 40 \\
13
+ TabDiff & 0.653 & 0.649 & 0.671 & 44 \\
14
+ TabPFGen & 0.667 & 0.663 & 0.686 & 46 \\
15
+ TabSyn & 0.694 & 0.694 & 0.711 & 40 \\
16
+ TVAE & 0.635 & 0.619 & 0.664 & 49 \\
17
+ \bottomrule
18
+ \end{tabular}
evaluation/query_family/subgroup/final/subgroup_prefix_bars_appendix__v2.tex ADDED
@@ -0,0 +1,77 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \documentclass[tikz,border=4pt]{standalone}
2
+ \usepackage{pgfplots}
3
+ \usepackage{xcolor}
4
+ \usetikzlibrary{patterns}
5
+ \pgfplotsset{compat=1.18}
6
+
7
+ \usepgfplotslibrary{groupplots}
8
+ \definecolor{modelreal}{HTML}{000000}
9
+ \definecolor{modelarf}{HTML}{777777}
10
+ \definecolor{modelbayesnet}{HTML}{CCBB44}
11
+ \definecolor{modelctgan}{HTML}{EE6677}
12
+ \definecolor{modelforestdiffusion}{HTML}{228833}
13
+ \definecolor{modelrealtabformer}{HTML}{332288}
14
+ \definecolor{modeltabbyflow}{HTML}{882255}
15
+ \definecolor{modeltabddpm}{HTML}{EE7733}
16
+ \definecolor{modeltabdiff}{HTML}{AA3377}
17
+ \definecolor{modeltabpfgen}{HTML}{009988}
18
+ \definecolor{modeltabsyn}{HTML}{66CCEE}
19
+ \definecolor{modeltvae}{HTML}{4477AA}
20
+ \begin{document}
21
+ \begin{tikzpicture}
22
+ \begin{groupplot}[
23
+ group style={group size=3 by 1, horizontal sep=1.15cm},
24
+ width=5.0cm,
25
+ height=7.0cm,
26
+ ymin=0.0, ymax=1.0,
27
+ ymajorgrids,
28
+ grid style={draw=gray!20},
29
+ major grid style={draw=gray!30},
30
+ symbolic x coords={REAL,ARF,BayesNet,CTGAN,ForestDiffusion,RealTabFormer,TabbyFlow,TabDDPM,TabDiff,TabPFGen,TabSyn,TVAE},
31
+ xtick=data,
32
+ x tick label style={rotate=45, anchor=east, font=\scriptsize},
33
+ tick style={draw=black!70},
34
+ axis line style={draw=black!70},
35
+ ]
36
+ \nextgroupplot[title={Categorical}, ylabel={Subgroup structure score}]
37
+ \addplot+[ybar, bar width=7.0pt, draw=modelreal, fill=modelreal] coordinates { (REAL,1.0000) };
38
+ \addplot+[ybar, bar width=7.0pt, draw=modelarf, fill=modelarf] coordinates { (ARF,0.8708) };
39
+ \addplot+[ybar, bar width=7.0pt, draw=modelbayesnet, fill=modelbayesnet] coordinates { (BayesNet,0.8504) };
40
+ \addplot+[ybar, bar width=7.0pt, draw=modelctgan, fill=modelctgan] coordinates { (CTGAN,0.8287) };
41
+ \addplot+[ybar, bar width=7.0pt, draw=modelforestdiffusion, fill=modelforestdiffusion] coordinates { (ForestDiffusion,0.8008) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modelrealtabformer, fill=modelrealtabformer] coordinates { (RealTabFormer,0.8995) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modeltabbyflow, fill=modeltabbyflow] coordinates { (TabbyFlow,0.7579) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modeltabddpm, fill=modeltabddpm] coordinates { (TabDDPM,0.7889) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modeltabdiff, fill=modeltabdiff] coordinates { (TabDiff,0.8110) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modeltabpfgen, fill=modeltabpfgen] coordinates { (TabPFGen,0.8226) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modeltabsyn, fill=modeltabsyn] coordinates { (TabSyn,0.8282) };
48
+ \addplot+[ybar, bar width=7.0pt, draw=modeltvae, fill=modeltvae] coordinates { (TVAE,0.7619) };
49
+ \nextgroupplot[title={Mixed}, ylabel={}]
50
+ \addplot+[ybar, bar width=7.0pt, draw=modelreal, fill=modelreal] coordinates { (REAL,1.0000) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modelarf, fill=modelarf] coordinates { (ARF,0.7553) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modelbayesnet, fill=modelbayesnet] coordinates { (BayesNet,0.7641) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modelctgan, fill=modelctgan] coordinates { (CTGAN,0.6638) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modelforestdiffusion, fill=modelforestdiffusion] coordinates { (ForestDiffusion,0.6939) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modelrealtabformer, fill=modelrealtabformer] coordinates { (RealTabFormer,0.8099) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modeltabbyflow, fill=modeltabbyflow] coordinates { (TabbyFlow,0.7124) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modeltabddpm, fill=modeltabddpm] coordinates { (TabDDPM,0.6836) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modeltabdiff, fill=modeltabdiff] coordinates { (TabDiff,0.7513) };
59
+ \addplot+[ybar, bar width=7.0pt, draw=modeltabpfgen, fill=modeltabpfgen] coordinates { (TabPFGen,0.7511) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modeltabsyn, fill=modeltabsyn] coordinates { (TabSyn,0.7256) };
61
+ \addplot+[ybar, bar width=7.0pt, draw=modeltvae, fill=modeltvae] coordinates { (TVAE,0.5810) };
62
+ \nextgroupplot[title={Numerical}, ylabel={}]
63
+ \addplot+[ybar, bar width=7.0pt, draw=modelreal, fill=modelreal] coordinates { (REAL,1.0000) };
64
+ \addplot+[ybar, bar width=7.0pt, draw=modelarf, fill=modelarf] coordinates { (ARF,0.4826) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modelbayesnet, fill=modelbayesnet] coordinates { (BayesNet,0.5236) };
66
+ \addplot+[ybar, bar width=7.0pt, draw=modelctgan, fill=modelctgan] coordinates { (CTGAN,0.4998) };
67
+ \addplot+[ybar, bar width=7.0pt, draw=modelforestdiffusion, fill=modelforestdiffusion] coordinates { (ForestDiffusion,0.4233) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modelrealtabformer, fill=modelrealtabformer] coordinates { (RealTabFormer,0.6694) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modeltabbyflow, fill=modeltabbyflow] coordinates { (TabbyFlow,0.4325) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modeltabddpm, fill=modeltabddpm] coordinates { (TabDDPM,0.3743) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modeltabdiff, fill=modeltabdiff] coordinates { (TabDiff,0.4578) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modeltabpfgen, fill=modeltabpfgen] coordinates { (TabPFGen,0.4696) };
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+ \addplot+[ybar, bar width=7.0pt, draw=modeltabsyn, fill=modeltabsyn] coordinates { (TabSyn,0.4737) };
74
+ \addplot+[ybar, bar width=7.0pt, draw=modeltvae, fill=modeltvae] coordinates { (TVAE,0.5392) };
75
+ \end{groupplot}
76
+ \end{tikzpicture}
77
+ \end{document}
evaluation/query_family/subgroup/final/subgroup_tradeoff_scatter_main__v2.tex ADDED
@@ -0,0 +1,116 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \documentclass[tikz,border=4pt]{standalone}
2
+ \usepackage{pgfplots}
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+ \usepackage{xcolor}
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+ \usetikzlibrary{patterns}
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+ \pgfplotsset{compat=1.18}
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+
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+ \definecolor{modelreal}{HTML}{000000}
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+ \definecolor{modelarf}{HTML}{777777}
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+ \definecolor{modelbayesnet}{HTML}{CCBB44}
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+ \definecolor{modelctgan}{HTML}{EE6677}
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+ \definecolor{modelforestdiffusion}{HTML}{228833}
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+ \definecolor{modelrealtabformer}{HTML}{332288}
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+ \definecolor{modeltabbyflow}{HTML}{882255}
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+ \definecolor{modeltabdiff}{HTML}{AA3377}
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+ \definecolor{modeltabpfgen}{HTML}{009988}
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+ \definecolor{modeltabsyn}{HTML}{66CCEE}
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+ \definecolor{modeltvae}{HTML}{4477AA}
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+ \begin{document}
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+ \begin{tikzpicture}
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+ \begin{axis}[
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+ width=14.6cm,
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+ height=8.4cm,
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+ ymin=0.0, ymax=1.03,
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+ xlabel={Model},
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+ ylabel={Score},
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+ ymajorgrids,
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+ grid style={draw=gray!20},
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+ major grid style={draw=gray!30},
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+ axis line style={draw=black!70},
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+ tick style={draw=black!70},
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+ symbolic x coords={REAL,ARF,BayesNet,CTGAN,ForestDiffusion,RealTabFormer,TabbyFlow,TabDDPM,TabDiff,TabPFGen,TabSyn,TVAE},
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+ xtick=data,
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+ xticklabel style={rotate=45, anchor=east, font=\scriptsize},
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+ legend style={draw=none, fill=none, font=\scriptsize, at={(0.98,0.98)}, anchor=north east},
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+ ]
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (REAL,1.0000) +- (0,0.0000) };
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+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modelreal, fill=white, pattern=north east lines, pattern color=modelreal,
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (REAL,1.0000) +- (0,0.0000) };
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+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modelarf, fill=modelarf,
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (ARF,0.6918) +- (0,0.0974) };
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (ARF,0.7113) +- (0,0.0955) };
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+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modelbayesnet, fill=modelbayesnet,
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (BayesNet,0.7053) +- (0,0.0921) };
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+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modelbayesnet, fill=white, pattern=north east lines, pattern color=modelbayesnet,
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (BayesNet,0.7179) +- (0,0.0911) };
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+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modelctgan, fill=modelctgan,
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (CTGAN,0.6580) +- (0,0.0991) };
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+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modelctgan, fill=white, pattern=north east lines, pattern color=modelctgan,
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (CTGAN,0.6843) +- (0,0.0900) };
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (ForestDiffusion,0.6142) +- (0,0.0965) };
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (RealTabFormer,0.7898) +- (0,0.0736) };
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+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modelrealtabformer, fill=white, pattern=north east lines, pattern color=modelrealtabformer,
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (RealTabFormer,0.8049) +- (0,0.0690) };
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+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modeltabbyflow, fill=modeltabbyflow,
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (TabbyFlow,0.6180) +- (0,0.0966) };
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+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modeltabbyflow, fill=white, pattern=north east lines, pattern color=modeltabbyflow,
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (TabbyFlow,0.6355) +- (0,0.0958) };
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+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modeltabddpm, fill=modeltabddpm,
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (TabDDPM,0.5865) +- (0,0.1158) };
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+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modeltabddpm, fill=white, pattern=north east lines, pattern color=modeltabddpm,
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (TabDDPM,0.6013) +- (0,0.1107) };
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (TabDiff,0.6492) +- (0,0.0996) };
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+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modeltabdiff, fill=white, pattern=north east lines, pattern color=modeltabdiff,
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (TabDiff,0.6715) +- (0,0.0995) };
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+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modeltabpfgen, fill=modeltabpfgen,
92
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (TabPFGen,0.6634) +- (0,0.1035) };
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+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modeltabpfgen, fill=white, pattern=north east lines, pattern color=modeltabpfgen,
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+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
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+ coordinates { (TabPFGen,0.6863) +- (0,0.1056) };
97
+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modeltabsyn, fill=modeltabsyn,
98
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
99
+ coordinates { (TabSyn,0.6938) +- (0,0.1007) };
100
+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modeltabsyn, fill=white, pattern=north east lines, pattern color=modeltabsyn,
101
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
102
+ coordinates { (TabSyn,0.7106) +- (0,0.1012) };
103
+ \addplot+[ybar, bar width=6.5pt, bar shift=-3.8pt, draw=modeltvae, fill=modeltvae,
104
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
105
+ coordinates { (TVAE,0.6191) +- (0,0.0918) };
106
+ \addplot+[ybar, bar width=6.5pt, bar shift=3.8pt, draw=modeltvae, fill=white, pattern=north east lines, pattern color=modeltvae,
107
+ error bars/.cd, y dir=both, y explicit, error bar style={line width=0.8pt}]
108
+ coordinates { (TVAE,0.6644) +- (0,0.0854) };
109
+ \addlegendimage{area legend, draw=black, fill=black}
110
+ \addlegendentry{Internal profile stability}
111
+ \addlegendimage{area legend, draw=black, fill=white, pattern=north east lines, pattern color=black}
112
+ \addlegendentry{Subgroup size stability}
113
+ \node[anchor=west, font=\scriptsize] at (rel axis cs:0.02,0.90) {$\uparrow$ better};
114
+ \end{axis}
115
+ \end{tikzpicture}
116
+ \end{document}
evaluation/query_family/subgroup/final/v2/subgroup_model_summary_generated__v2.tex ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \begin{tabular}{lrrrr}
2
+ \toprule
3
+ Model & Subgroup score & Internal profile & Subgroup size & Datasets \\
4
+ \midrule
5
+ REAL & 1.000 & 1.000 & 1.000 & 49 \\
6
+ ARF & 0.694 & 0.692 & 0.711 & 49 \\
7
+ BayesNet & 0.704 & 0.705 & 0.718 & 49 \\
8
+ CTGAN & 0.664 & 0.658 & 0.684 & 49 \\
9
+ ForestDiffusion & 0.630 & 0.614 & 0.660 & 49 \\
10
+ RealTabFormer & 0.790 & 0.790 & 0.805 & 49 \\
11
+ TabbyFlow & 0.627 & 0.618 & 0.636 & 46 \\
12
+ TabDDPM & 0.586 & 0.586 & 0.601 & 40 \\
13
+ TabDiff & 0.653 & 0.649 & 0.671 & 44 \\
14
+ TabPFGen & 0.667 & 0.663 & 0.686 & 46 \\
15
+ TabSyn & 0.694 & 0.694 & 0.711 & 40 \\
16
+ TVAE & 0.635 & 0.619 & 0.664 & 49 \\
17
+ \bottomrule
18
+ \end{tabular}
evaluation/query_family/subgroup/manifest.json ADDED
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1
+ {
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+ "task": "subgroup_breakdown",
3
+ "sql_source_version": "v2",
4
+ "sql_source_label": "v2_current",
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+ "source_analysis_run": "20260526_v2_official20_plus_c2patch_plus_subgroupconditionalrepair_merged49",
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+ "excluded_models": [
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+ "cdtd",
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+ "codi",
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+ "goggle"
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+ ],
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+ "included_models": [
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+ "real",
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+ "arf",
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+ "bayesnet",
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+ "ctgan",
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+ "forestdiffusion",
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+ "realtabformer",
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+ "tabbyflow",
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+ "tabddpm",
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+ "tabdiff",
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+ "tabpfgen",
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+ "tabsyn",
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+ "tvae"
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+ ],
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+ "dataset_panel_count": 559,
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+ "query_row_count": 12515,
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+ "compile_notes": {
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+ "tradeoff": {
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+ "success": false,
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+ "note": "latexmk not available"
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+ "note": "latexmk not available"
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+ "heatmap": {
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+ "note": "latexmk not available"
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+ "note": "latexmk not available"
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+ "family_subitem_bars": {
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+ "success": false,
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+ "note": "latexmk not available"
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+ }
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+ },
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+ "publish_final": true
54
+ }
evaluation/query_family/subgroup/tables/subgroup_model_summary_generated.tex ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ \begin{tabular}{lrrrr}
2
+ \toprule
3
+ Model & Subgroup score & Internal profile & Subgroup size & Datasets \\
4
+ \midrule
5
+ REAL & 1.000 & 1.000 & 1.000 & 49 \\
6
+ ARF & 0.694 & 0.692 & 0.711 & 49 \\
7
+ BayesNet & 0.704 & 0.705 & 0.718 & 49 \\
8
+ CTGAN & 0.664 & 0.658 & 0.684 & 49 \\
9
+ ForestDiffusion & 0.630 & 0.614 & 0.660 & 49 \\
10
+ RealTabFormer & 0.790 & 0.790 & 0.805 & 49 \\
11
+ TabbyFlow & 0.627 & 0.618 & 0.636 & 46 \\
12
+ TabDDPM & 0.586 & 0.586 & 0.601 & 40 \\
13
+ TabDiff & 0.653 & 0.649 & 0.671 & 44 \\
14
+ TabPFGen & 0.667 & 0.663 & 0.686 & 46 \\
15
+ TabSyn & 0.694 & 0.694 & 0.711 & 40 \\
16
+ TVAE & 0.635 & 0.619 & 0.664 & 49 \\
17
+ \bottomrule
18
+ \end{tabular}