Datasets:
pfilonenko
/
ML_for_TwoSampleTesting

Dataset card Data Studio Files
xet
 Community
1
iter
int64
0
7.65k
sample
stringclasses
1 value
H0_H1
stringclasses
2 values
Hi
stringclasses
27 values
n1
int64
20
1k
n2
int64
20
1k
perc
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0
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logrank_test
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BN_GPH_test
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0
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BN_MCE_test
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143
BN_SCE_test
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0
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Q_test
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MAX_Value_test
float64
0
10.2
MIN3_test
float64
0
1
WLg_logrank_test
float64
0
84.2
WLg_TaroneWare_test
float64
0
99.4
WLg_Breslow_test
float64
0
106
WLg_PetoPrentice_test
float64
0
71.9
WLg_Prentice_test
float64
0
71.6
WKM_test
float64
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train
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7,644
train
H1
H24
300
300
30
31
31.666667
-0.272726
0.511394
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4.39549
12.161594
5.673638
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0.563754
0.00685
0.3183
0.002271
0.261678
2.93464
3.090603
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7,644
train
H0
H24
500
500
30
30.8
30.4
-0.40109
0.400701
0.425588
0.425295
0.18573
0.471442
0.180939
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0.425588
0.681258
0.180876
0.205539
0.160525
0.142121
0.146724
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7,644
train
H1
H24
500
500
30
27.2
27.2
-0.551996
0.685177
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2.09221
6.36261
3.028092
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0.685177
0.095241
0.009501
0.070522
0.469702
1.007527
1.062985
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7,644
train
H0
H24
1,000
1,000
30
28
28
-0.937387
0.953916
0.856277
0.856103
0.91672
1.020201
0.880375
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0.953916
0.327157
0.732912
0.960753
0.910449
0.278468
0.264876
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7,644
train
H1
H24
1,000
1,000
30
28
26.4
0.173029
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0.134072
8.580916
0.306351
0.173029
0.357218
0.035414
0.127676
0.207502
0.013219
0.311422
0.342528
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7,644
train
H0
H24
20
20
40
65
35
-1.841864
1.836125
1.667862
1.632537
3.654727
4.30863
3.566781
1.632537
1.836125
0.04536
2.665178
3.500524
3.480793
0.663118
1.121765
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7,644
train
H1
H24
20
20
40
30
25
-0.807148
0.958159
0.203328
0.198449
2.766843
2.685453
2.810836
0.198449
0.958159
0.245265
0.039382
0.471908
0.916088
0.532709
0.389833
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7,644
train
H0
H24
30
30
40
56.666667
36.666667
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1.73385
2.107717
2.187982
5.756488
10.756328
5.64443
2.187982
2.107717
0.013119
4.787266
3.644937
3.020687
6.037585
5.830299
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7,644
train
H1
H24
30
30
40
53.333333
36.666667
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0.179014
1.177776
1.165407
4.511334
4.553573
4.550655
1.165407
1.177776
0.102763
1.358174
0.314475
0.031919
4.152204
3.920544
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7,644
train
H0
H24
50
50
40
24
44
1.888721
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5.203739
5.467622
5.269726
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2.203198
0.063874
4.910246
4.126788
3.089217
4.52932
4.628626
1.853059
7,644
train
H1
H24
50
50
40
44
32
-2.49212
2.462113
2.317178
2.37829
6.462633
6.841352
6.383104
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2.462113
0.010014
5.656265
6.351381
6.172708
2.005282
2.183557
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7,644
train
H0
H24
75
75
40
36
41.333333
1.01608
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1.687746
6.618753
1.877915
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1.268736
0.085095
1.612544
1.271449
0.63787
1.715103
2.092156
0.853922
7,644
train
H1
H24
75
75
40
36
33.333333
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0.226138
0.105733
0.105172
0.012389
2.806
0.040698
0.105172
0.226138
0.422513
0.011061
0.012154
0.051006
0.005644
0.001925
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7,644
train
H0
H24
100
100
40
37
40
1.137283
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2.030926
1.997219
2.013218
1.137283
1.244468
0.196296
0.659612
1.223851
1.548008
0.000605
0.002309
1.292177
7,644
train
H1
H24
100
100
40
52
40
-1.113151
1.051728
1.124119
1.118706
1.251914
5.325751
1.266855
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1.124119
0.14944
1.251503
1.010884
1.104558
0.849145
0.717202
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7,644
train
H0
H24
150
150
40
40.666667
37.333333
0.088819
-0.046849
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0.52838
2.939034
0.356679
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0.272951
0.401121
0.074428
0.003329
0.002194
0.235198
0.187145
0.05089
7,644
train
H1
H24
150
150
40
37.333333
36.666667
0.483624
-0.403018
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0.559101
8.323663
0.768555
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0.684044
0.039775
0.471095
0.433668
0.162482
0.739105
0.92031
0.404589
7,644
train
H0
H24
200
200
40
37
40.5
0.416019
-0.459568
-0.317028
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0.190859
0.670909
0.227937
0.416019
0.459568
0.631405
0.10051
0.145992
0.211047
0.000644
0.000134
0.47975
7,644
train
H1
H24
200
200
40
34.5
41
1.428746
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6.261763
7.469035
6.682496
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2.011752
0.035393
4.095452
2.670762
1.435109
6.516086
6.388593
1.229417
7,644
train
H0
H24
300
300
40
39.333333
45
-0.015413
0.063275
-0.265761
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1.079462
3.435354
0.859101
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0.265761
0.329244
0.070678
0.000001
0.00404
0.499576
0.462821
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7,644
train
H1
H24
300
300
40
46.333333
44
-1.660816
1.899653
1.129087
1.128648
4.652058
8.155211
5.242562
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1.899653
0.042911
1.273846
2.397254
3.616881
0.033795
0.041265
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7,644
train
H0
H24
500
500
40
38
43.4
1.724546
-1.686099
-1.707632
-1.706712
2.993983
3.26756
3.017655
1.724546
1.707632
0.080108
2.912865
2.918626
2.843147
1.534509
1.482919
1.750062
7,644
train
H1
H24
500
500
40
44.2
41.4
0.230985
-0.195102
-0.146056
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0.388842
12.930072
0.113908
-0.146117
0.195102
0.00479
0.02135
0.144142
0.038085
0.000002
0.001402
0.203654
7,644
train
H0
H24
1,000
1,000
40
40.2
39.8
0.11382
-0.070313
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-0.181039
0.046363
0.631658
0.066095
0.11382
0.181098
0.889148
0.032775
0.021023
0.004937
0.053736
0.057962
0.073359
7,644
train
H1
H24
1,000
1,000
40
38.9
38.2
-0.919671
1.269877
-0.054194
-0.054203
7.903429
9.516681
8.921787
-0.054203
1.269877
0.011552
0.002938
0.469641
1.61291
2.84893
2.812036
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7,644
train
H0
H24
20
20
50
65
25
-2.188627
1.727621
2.822796
2.877912
14.531109
14.895866
14.433433
-2.188627
2.822796
0.000734
8.282377
4.934541
3.008623
12.909525
12.412243
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7,644
train
H1
H24
20
20
50
55
70
0.586732
-0.474531
-0.756467
-0.743789
1.074123
2.518021
1.028836
-0.743789
0.756467
0.472043
0.553222
0.326412
0.223395
0.701025
0.608497
0.54547
7,644
train
H0
H24
30
30
50
56.666667
53.333333
0.954708
-1.268373
-0.548665
-0.549298
3.621206
3.59091
3.618212
0.954708
1.268373
0.163801
0.301728
0.936584
1.538263
0.271458
0.230013
1.360955
7,644
train
H1
H24
30
30
50
63.333333
53.333333
-0.670435
1.021942
0.422365
0.420498
1.312917
4.428507
1.477764
0.420498
1.021942
0.218757
0.176819
0.576891
1.043321
0.037157
0.059306
-1.058028
7,644
train
H0
H24
50
50
50
54
54
0.24487
-0.33545
-0.149957
-0.149243
0.227756
0.391934
0.238735
-0.149243
0.33545
0.728851
0.022273
0.058275
0.109293
0.066957
0.071691
0.346654
7,644
train
H1
H24
50
50
50
48
34
-2.264808
2.369778
1.87512
1.884528
6.107942
7.737459
6.320586
-2.264808
2.369778
0.01365
3.551447
4.741121
5.643953
0.393376
0.39303
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7,644
train
H0
H24
75
75
50
46.666667
50.666667
1.130852
-1.233209
-0.921324
-0.928059
1.885193
1.867944
1.882685
-0.928059
1.233209
0.199894
0.861293
1.239229
1.525045
0.042866
0.045162
1.281852
7,644
train
H1
H24
75
75
50
57.333333
41.333333
-1.211039
1.320059
0.997547
1.004457
1.800357
4.543044
1.949595
1.004457
1.320059
0.169349
1.008934
1.361661
1.743369
0.134507
0.124303
-1.374299
7,644
train
H0
H24
100
100
50
48
52
0.744408
-0.847941
-0.473328
-0.470663
1.304497
1.234972
1.308658
-0.470663
0.847941
0.378824
0.221523
0.504185
0.718335
0.069841
0.046634
0.880064
7,644
train
H1
H24
100
100
50
47
43
-0.473203
0.890207
-0.300173
-0.301367
6.70416
8.662069
7.268012
-0.301367
0.890207
0.02641
0.090822
0.161582
0.792576
3.023635
3.098953
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7,644
train
H0
H24
150
150
50
44.666667
52.666667
2.112233
-2.326381
-1.611181
-1.609493
6.894052
6.83483
6.944319
-1.609493
2.326381
0.014837
2.590469
4.408357
5.42446
0.055864
0.079528
2.43633
7,644
train
H1
H24
150
150
50
52
52.666667
0.279829
-0.1234
-0.409088
-0.40814
0.287291
2.092852
0.35586
-0.40814
0.409088
0.55336
0.166578
0.093879
0.015221
0.265638
0.321822
0.131819
7,644
train
H0
H24
200
200
50
47.5
45
-1.011306
1.24933
0.479489
0.478533
3.901067
4.37694
3.710594
0.478533
1.24933
0.156406
0.228994
1.012926
1.561385
0.468718
0.319366
-1.325973
7,644
train
H1
H24
200
200
50
47
56
1.229728
-1.271737
-1.011618
-1.011313
2.140412
4.054607
1.983152
1.229728
1.271737
0.179403
1.022754
1.590402
1.615993
0.08948
0.111381
1.342596
7,644
train
H0
H24
300
300
50
52.333333
44.666667
-1.057284
0.921588
1.222608
1.223172
1.662662
1.676451
1.661905
1.223172
1.222608
0.328803
1.496149
1.144443
0.849391
1.687113
1.737868
-0.976528
7,644
train
H1
H24
300
300
50
49
55.666667
1.341367
-1.092693
-1.665389
-1.671695
4.024762
4.36486
3.930485
-1.671695
1.665389
0.140122
2.794565
1.714874
1.193408
3.758425
3.694161
1.15409
7,644
train
H0
H24
500
500
50
52
48.2
0.076779
-0.388126
0.359195
0.358822
2.188445
2.650369
2.372187
0.358822
0.388126
0.305412
0.128753
0.002678
0.150588
1.340838
1.280218
0.411075
7,644
train
H1
H24
500
500
50
52.8
50.6
-0.832837
1.106307
0.492684
0.492592
1.754992
5.862068
2.098369
0.492592
1.106307
0.118517
0.242647
0.613362
1.22445
0.12223
0.127693
-1.163287
7,644
train
H0
H24
1,000
1,000
50
52
47.2
-0.969215
0.7263
1.281517
1.280966
2.481313
2.841932
2.540721
1.280966
1.281517
0.28073
1.640874
0.930815
0.527592
2.57648
2.578222
-0.769073
7,644
train
H1
H24
1,000
1,000
50
49.3
48.7
-0.056421
0.616002
-0.836108
-0.838197
10.480701
19.147714
11.666243
-0.838197
0.836108
0.000255
0.702574
0.006234
0.379718
6.405605
6.464267
-0.648846