diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..2074e0cd002f64f034f901614d2ad9d5eae886cf --- /dev/null +++ b/README.md @@ -0,0 +1,57 @@ +--- +license: apache-2.0 +language: en +tags: + - medical + - clinical-coding + - icd-10-cm + - snomed-ct + - entity-linking + - learning-to-rank +--- + +# TermMap-DX: trained artifacts + +Trained models for **TermMap-DX**, an engine that maps clinical terms extracted from charts to +one ICD-10-CM code and one SNOMED CT concept (HiLabs Hackathon 2026). The code lives in the team's +GitHub repository, [Shresth-Negi/TermMap-DX](https://github.com/Shresth-Negi/TermMap-DX) (private; +judges have access). There, `scripts/download_artifacts.py` pulls these files into place, and +`scripts/run_all.sh` does so automatically before mapping an input file: + +```bash +git clone https://github.com/Shresth-Negi/TermMap-DX.git && cd TermMap-DX +# set up the environment as in the README, put the challenge files in data/raw/, then +bash scripts/run_all.sh outputs/predictions.csv # downloads these artifacts first +``` + +## Contents + +| files | what | +|---|---| +| `ce_ICD10CM_d3e4/`, `ce_SNOMEDCT_US_d3e4/` | cross-encoders fine-tuned from `cambridgeltl/SapBERT-from-PubMedBERT-fulltext` (4 epochs, listwise loss over candidate shortlists) | +| `ranker__s1.txt`, `ranker__s2.txt` (+ `.json` feature lists) | LightGBM LambdaRank models, stage 1 and stage 2, per coding system | +| `calib_.json` | isotonic calibration (ranker margin -> P(correct)) | +| `config.json` | model-set configuration: encoders, cross-encoder, LLM, fallback set | +| `emb__.npy` | float16 embeddings of every unique dictionary description (row = description id rebuilt by the code from the supplied dictionaries) for SapBERT, gte-base and Qwen3-Embedding-0.6B | +| `manifest.json` | sha256 and size of every file | + +Model sets: `_d3llm14e4` (default; adds Qwen2.5-14B-Instruct scores at inference), `_d3llm7e4` +(Qwen2.5-7B-Instruct), `_d3ce4` (no LLM), `_sap4` (SapBERT only, lightest). The LLMs and encoders +are not included; they are pulled from their public Hugging Face repositories. + +## Results (5-fold cross-validation on the training file) + +| set | ICD-10-CM exact match | SNOMED CT exact match | +|---|---|---| +| `_d3llm14e4` | 0.708 | 0.582 | +| `_d3llm7e4` | 0.702 | 0.567 | +| `_d3ce4` | 0.684 | 0.543 | +| `_sap4` | 0.658 | 0.507 | + +## Training data and licences + +Trained on the HiLabs hackathon training file (proprietary; not included here). The supplied +ICD-10-CM and SNOMED CT US dictionaries define the answer space; the embedding matrices are +derived from their descriptions, so use is subject to the SNOMED CT licence terms that apply to +you. 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21616 335 4805 4675 4536 3096 1726 +cat_boundaries=0 1 2 +cat_threshold=33694695 51348384 +is_linear=0 +shrinkage=0.05 + + +end of trees + +feature_importances: +sapbert_max_gap=193 +gte_max_gap=192 +qwen3_max_gap=186 +nn_dense_max_gap=164 +chapter=162 +n_cand=143 +nn_char_max_gap=142 +prior=137 +gte_var_gap=133 +gte_max_rank=130 +sapbert_pref=129 +ctx_dense=126 +billable=120 +sapbert_var_gap=115 +word_max_gap=114 +qwen3_max_rank=111 +prior_gap=111 +sapbert_max_rank=110 +nn_cat_dense_max_gap=101 +block_prior=100 +sapbert_max=94 +char_var_gap=90 +fz_ratio=88 +qwen3_var_gap=88 +sapbert_var=87 +gte_var=87 +sapbert_var_rank=87 +fz_tset_gap=85 +char_var=84 +gte_pref=81 +nn_dense_sum=81 +char_max_gap=81 +qwen3_pref=79 +gte_var_rank=78 +gte_max=77 +nn_cat_char_max_gap=77 +fz_tset=75 +is_other=75 +nn_dense_max=73 +char_max_rank=73 +char_var_rank=70 +nn_cat_dense_max=69 +fz_tset_rank=69 +qwen3_var=68 +nn_cat_char_max_rank=68 +prior_rank=68 +fz_tsort=66 +reading_ctx=64 +word_max_rank=64 +nn_cat_dense_sum=63 +nn_dense_max_rank=62 +fz_partial=61 +nn_ctx_max=61 +qwen3_max=59 +is_unspec=59 +nn_char_sum=58 +nn_entctx_max_gap=58 +char_max=55 +nn_cat_char_sum=55 +nn_char_max=54 +nn_entctx_max=53 +nn_cat_char_max=52 +nn_ctx_max_gap=52 +nn_cat_dense_max_rank=51 +word_max=50 +q_len=50 +nn_char_max_rank=49 +reading_ctx_gap=45 +qwen3_var_rank=43 +tok_dextra=40 +nn_entctx_max_rank=39 +n_desc=38 +nn_ctx_max_rank=29 +code_len=26 +nn_cat_cnt=21 +tok_qcov=20 +ctx_overlap=19 +tok_dcov=16 +cand_neg=15 +q_nvar=15 +nn_cnt=14 +q_ntok=14 +enc7=11 +neg_match=5 +lat_match=2 +q_digit=2 +num_match=1 +hist_match=1 +lat_missing=1 +q_neg=1 +q_hist=1 + +parameters: +[boosting: gbdt] +[objective: lambdarank] +[metric: map] +[tree_learner: serial] +[device_type: cpu] +[data_sample_strategy: bagging] +[data: ] +[valid: ] +[num_iterations: 103] +[learning_rate: 0.05] +[num_leaves: 63] +[num_threads: 16] +[seed: 13] +[deterministic: 1] +[force_col_wise: 1] +[force_row_wise: 0] +[histogram_pool_size: -1] +[max_depth: -1] +[min_data_in_leaf: 20] +[min_sum_hessian_in_leaf: 0.001] +[bagging_fraction: 0.8] +[pos_bagging_fraction: 1] +[neg_bagging_fraction: 1] +[bagging_freq: 1] +[bagging_seed: 16376] +[bagging_by_query: 0] +[feature_fraction: 0.8] +[feature_fraction_bynode: 1] +[feature_fraction_seed: 20348] +[extra_trees: 0] +[extra_seed: 30076] +[early_stopping_round: 0] +[early_stopping_min_delta: 0] +[first_metric_only: 0] +[max_delta_step: 0] +[lambda_l1: 0] +[lambda_l2: 1] +[linear_lambda: 0] +[min_gain_to_split: 0] +[drop_rate: 0.1] +[max_drop: 50] +[skip_drop: 0.5] +[xgboost_dart_mode: 0] +[uniform_drop: 0] +[drop_seed: 24096] +[top_rate: 0.2] +[other_rate: 0.1] +[min_data_per_group: 100] +[max_cat_threshold: 32] +[cat_l2: 10] +[cat_smooth: 10] +[max_cat_to_onehot: 4] +[top_k: 20] +[monotone_constraints: ] +[monotone_constraints_method: basic] +[monotone_penalty: 0] +[feature_contri: ] +[forcedsplits_filename: ] +[refit_decay_rate: 0.9] +[cegb_tradeoff: 1] +[cegb_penalty_split: 0] +[cegb_penalty_feature_lazy: ] +[cegb_penalty_feature_coupled: ] +[path_smooth: 0] +[interaction_constraints: ] +[verbosity: -1] +[saved_feature_importance_type: 0] +[use_quantized_grad: 0] +[num_grad_quant_bins: 4] +[quant_train_renew_leaf: 0] +[stochastic_rounding: 1] +[linear_tree: 0] +[max_bin: 255] +[max_bin_by_feature: ] +[min_data_in_bin: 3] +[bin_construct_sample_cnt: 200000] +[data_random_seed: 81] +[is_enable_sparse: 1] +[enable_bundle: 1] +[use_missing: 1] +[zero_as_missing: 0] +[feature_pre_filter: 1] +[pre_partition: 0] +[two_round: 0] +[header: 0] +[label_column: ] +[weight_column: ] +[group_column: ] +[ignore_column: ] +[categorical_feature: 29,51,55,95,99] +[forcedbins_filename: ] +[precise_float_parser: 0] +[parser_config_file: ] +[objective_seed: 11872] +[num_class: 1] +[is_unbalance: 0] +[scale_pos_weight: 1] +[sigmoid: 1] +[boost_from_average: 1] +[reg_sqrt: 0] +[alpha: 0.9] +[fair_c: 1] +[poisson_max_delta_step: 0.7] +[tweedie_variance_power: 1.5] +[lambdarank_truncation_level: 20] +[lambdarank_norm: 1] +[label_gain: ] +[lambdarank_position_bias_regularization: 0] +[eval_at: 1] +[multi_error_top_k: 1] +[auc_mu_weights: ] +[num_machines: 1] +[local_listen_port: 12400] +[time_out: 120] +[machine_list_filename: ] +[machines: ] +[gpu_platform_id: -1] +[gpu_device_id: -1] +[gpu_device_id_list: ] +[gpu_use_dp: 0] +[num_gpu: 1] + +end of parameters + +pandas_categorical:[] diff --git a/ranker_ICD10CM_s1_d3llm14e4.json b/ranker_ICD10CM_s1_d3llm14e4.json new file mode 100644 index 0000000000000000000000000000000000000000..695c8f309a0e9ea44a068d1ea8ce25b5412151cc --- /dev/null +++ b/ranker_ICD10CM_s1_d3llm14e4.json @@ -0,0 +1 @@ +{"cols": ["char_max", "word_max", "char_var", "sapbert_max", "sapbert_pref", "sapbert_var", "reading_ctx", "reading_ctx_gap", "ctx_dense", "gte_max", "gte_pref", "gte_var", "qwen3_max", "qwen3_pref", "qwen3_var", "num_match", "num_conflict", "cand_neg", "cand_hist", "neg_match", "hist_match", "fz_ratio", 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"nn_entctx_max_gap", "nn_ctx_max_rank", "nn_ctx_max_gap", "prior_rank", "prior_gap", "q_len", "q_ntok", "q_digit", "q_abbr", "q_nvar", "q_lat", "q_neg", "q_hist", "q_fam", "subconcept", "n_cand"]} \ No newline at end of file diff --git a/ranker_ICD10CM_s1_d3llm14e4.txt b/ranker_ICD10CM_s1_d3llm14e4.txt new file mode 100644 index 0000000000000000000000000000000000000000..6f9c2dc28464de788c1b8331ba33f22fe73fee4b --- /dev/null +++ b/ranker_ICD10CM_s1_d3llm14e4.txt @@ -0,0 +1,2347 @@ +tree +version=v4 +num_class=1 +num_tree_per_iteration=1 +label_index=0 +max_feature_idx=100 +objective=lambdarank +feature_names=char_max word_max char_var sapbert_max sapbert_pref sapbert_var reading_ctx reading_ctx_gap ctx_dense gte_max gte_pref gte_var qwen3_max qwen3_pref qwen3_var num_match num_conflict cand_neg cand_hist neg_match hist_match fz_ratio fz_tset fz_partial fz_tsort tok_qcov tok_dcov tok_dextra ctx_overlap cand_lat lat_match lat_conflict lat_missing nn_cat_char_max nn_cat_char_sum 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124 571 7117 9953 4824 1197 162 17382 1722 66 2038 1061 119 258 74 53 28 118 1635 19981 269 130 139 1440 1370 1607 +internal_value=-0.000456209 -0.00347892 0.00841042 0.0143207 0.0259217 -0.0203346 -0.02788 -0.00954542 -0.000828869 -0.00275377 0.0159648 -0.00464506 -0.00218499 -0.0176816 -0.0251882 -0.0159224 -0.0476354 0.00120061 0.0311568 -0.0273039 -0.00508059 -0.00121947 -0.0239291 0.00856208 -0.0111055 -0.00851896 -0.0193443 -0.0165716 -0.0380094 0.0334285 -0.00943002 -0.0163443 -0.00641143 -0.030361 -0.00969276 0.0277341 0.0100188 0.00158248 0.00960694 0.00648253 0.0318737 -0.000358178 -0.00988535 -0.00788795 0.00876355 0.0183871 -0.000691101 0.0302573 0.00239243 -0.0119366 -0.0328672 0.00935422 -0.0447924 -0.0304581 0.00968777 0.0214875 0.00110265 0.0099565 0.0163793 0.00440248 -0.0145194 -0.0335453 +internal_weight=563.412 420.625 142.787 105.579 74.0839 56.2397 45.0011 37.2086 364.385 327.664 36.7212 301.474 254.598 46.8765 38.0344 49.6074 13.7442 204.99 66.153 30.8624 113.33 92.7081 20.6221 91.66 24.2903 31.4947 21.7839 30.5875 10.5746 63.9945 11.6921 7.9309 16.4328 18.0319 16.1185 25.0292 12.3722 55.9262 35.7356 62.1205 7.67592 5.6526 7.27207 15.5808 9.19238 26.19 10.4064 15.7837 54.4446 18.6109 9.11066 9.50027 7.84085 6.57338 11.2386 8.79528 5.19927 35.8337 28.3847 17.7517 9.59979 6.45823 +internal_count=396261 318263 77998 32123 30788 188952 166061 45875 129311 127486 1825 119379 112856 6523 6289 22011 4016 90845 30119 6574 52803 23246 29557 38042 2273 1335 1147 2112 286 25213 1254 669 345 33313 981 571 305 35421 34850 21134 5963 2175 181 26221 8839 8107 6711 1396 15171 10366 10055 311 9981 172 22891 21616 335 4805 4675 4536 3096 1726 +cat_boundaries=0 1 2 +cat_threshold=33694695 51348384 +is_linear=0 +shrinkage=0.05 + + +end of trees + +feature_importances: +sapbert_max_gap=193 +gte_max_gap=192 +qwen3_max_gap=186 +nn_dense_max_gap=164 +chapter=162 +n_cand=143 +nn_char_max_gap=142 +prior=137 +gte_var_gap=133 +gte_max_rank=130 +sapbert_pref=129 +ctx_dense=126 +billable=120 +sapbert_var_gap=115 +word_max_gap=114 +qwen3_max_rank=111 +prior_gap=111 +sapbert_max_rank=110 +nn_cat_dense_max_gap=101 +block_prior=100 +sapbert_max=94 +char_var_gap=90 +fz_ratio=88 +qwen3_var_gap=88 +sapbert_var=87 +gte_var=87 +sapbert_var_rank=87 +fz_tset_gap=85 +char_var=84 +gte_pref=81 +nn_dense_sum=81 +char_max_gap=81 +qwen3_pref=79 +gte_var_rank=78 +gte_max=77 +nn_cat_char_max_gap=77 +fz_tset=75 +is_other=75 +nn_dense_max=73 +char_max_rank=73 +char_var_rank=70 +nn_cat_dense_max=69 +fz_tset_rank=69 +qwen3_var=68 +nn_cat_char_max_rank=68 +prior_rank=68 +fz_tsort=66 +reading_ctx=64 +word_max_rank=64 +nn_cat_dense_sum=63 +nn_dense_max_rank=62 +fz_partial=61 +nn_ctx_max=61 +qwen3_max=59 +is_unspec=59 +nn_char_sum=58 +nn_entctx_max_gap=58 +char_max=55 +nn_cat_char_sum=55 +nn_char_max=54 +nn_entctx_max=53 +nn_cat_char_max=52 +nn_ctx_max_gap=52 +nn_cat_dense_max_rank=51 +word_max=50 +q_len=50 +nn_char_max_rank=49 +reading_ctx_gap=45 +qwen3_var_rank=43 +tok_dextra=40 +nn_entctx_max_rank=39 +n_desc=38 +nn_ctx_max_rank=29 +code_len=26 +nn_cat_cnt=21 +tok_qcov=20 +ctx_overlap=19 +tok_dcov=16 +cand_neg=15 +q_nvar=15 +nn_cnt=14 +q_ntok=14 +enc7=11 +neg_match=5 +lat_match=2 +q_digit=2 +num_match=1 +hist_match=1 +lat_missing=1 +q_neg=1 +q_hist=1 + +parameters: +[boosting: gbdt] +[objective: lambdarank] +[metric: map] +[tree_learner: serial] +[device_type: cpu] +[data_sample_strategy: bagging] +[data: ] +[valid: ] +[num_iterations: 103] +[learning_rate: 0.05] +[num_leaves: 63] +[num_threads: 16] +[seed: 13] +[deterministic: 1] +[force_col_wise: 1] +[force_row_wise: 0] +[histogram_pool_size: -1] +[max_depth: -1] +[min_data_in_leaf: 20] +[min_sum_hessian_in_leaf: 0.001] +[bagging_fraction: 0.8] +[pos_bagging_fraction: 1] +[neg_bagging_fraction: 1] +[bagging_freq: 1] +[bagging_seed: 16376] +[bagging_by_query: 0] +[feature_fraction: 0.8] +[feature_fraction_bynode: 1] +[feature_fraction_seed: 20348] +[extra_trees: 0] +[extra_seed: 30076] +[early_stopping_round: 0] +[early_stopping_min_delta: 0] +[first_metric_only: 0] +[max_delta_step: 0] +[lambda_l1: 0] +[lambda_l2: 1] +[linear_lambda: 0] +[min_gain_to_split: 0] +[drop_rate: 0.1] +[max_drop: 50] +[skip_drop: 0.5] +[xgboost_dart_mode: 0] +[uniform_drop: 0] +[drop_seed: 24096] +[top_rate: 0.2] +[other_rate: 0.1] +[min_data_per_group: 100] +[max_cat_threshold: 32] +[cat_l2: 10] +[cat_smooth: 10] +[max_cat_to_onehot: 4] +[top_k: 20] +[monotone_constraints: ] +[monotone_constraints_method: basic] +[monotone_penalty: 0] +[feature_contri: ] +[forcedsplits_filename: ] +[refit_decay_rate: 0.9] +[cegb_tradeoff: 1] +[cegb_penalty_split: 0] +[cegb_penalty_feature_lazy: ] +[cegb_penalty_feature_coupled: ] +[path_smooth: 0] +[interaction_constraints: ] +[verbosity: -1] +[saved_feature_importance_type: 0] +[use_quantized_grad: 0] +[num_grad_quant_bins: 4] +[quant_train_renew_leaf: 0] +[stochastic_rounding: 1] +[linear_tree: 0] +[max_bin: 255] +[max_bin_by_feature: ] +[min_data_in_bin: 3] +[bin_construct_sample_cnt: 200000] +[data_random_seed: 81] +[is_enable_sparse: 1] +[enable_bundle: 1] +[use_missing: 1] +[zero_as_missing: 0] +[feature_pre_filter: 1] +[pre_partition: 0] +[two_round: 0] +[header: 0] +[label_column: ] +[weight_column: ] +[group_column: ] +[ignore_column: ] +[categorical_feature: 29,51,55,95,99] +[forcedbins_filename: ] +[precise_float_parser: 0] +[parser_config_file: ] +[objective_seed: 11872] +[num_class: 1] +[is_unbalance: 0] +[scale_pos_weight: 1] +[sigmoid: 1] +[boost_from_average: 1] +[reg_sqrt: 0] +[alpha: 0.9] +[fair_c: 1] +[poisson_max_delta_step: 0.7] +[tweedie_variance_power: 1.5] +[lambdarank_truncation_level: 20] +[lambdarank_norm: 1] +[label_gain: ] +[lambdarank_position_bias_regularization: 0] +[eval_at: 1] +[multi_error_top_k: 1] +[auc_mu_weights: ] +[num_machines: 1] +[local_listen_port: 12400] +[time_out: 120] +[machine_list_filename: ] +[machines: ] +[gpu_platform_id: -1] +[gpu_device_id: -1] +[gpu_device_id_list: ] +[gpu_use_dp: 0] +[num_gpu: 1] + +end of parameters + +pandas_categorical:[] diff --git a/ranker_ICD10CM_s1_d3llm7e4.json b/ranker_ICD10CM_s1_d3llm7e4.json new file mode 100644 index 0000000000000000000000000000000000000000..695c8f309a0e9ea44a068d1ea8ce25b5412151cc --- /dev/null +++ b/ranker_ICD10CM_s1_d3llm7e4.json @@ -0,0 +1 @@ +{"cols": ["char_max", "word_max", "char_var", "sapbert_max", "sapbert_pref", "sapbert_var", "reading_ctx", "reading_ctx_gap", "ctx_dense", "gte_max", "gte_pref", "gte_var", "qwen3_max", "qwen3_pref", "qwen3_var", "num_match", "num_conflict", "cand_neg", "cand_hist", "neg_match", "hist_match", "fz_ratio", "fz_tset", "fz_partial", "fz_tsort", "tok_qcov", "tok_dcov", "tok_dextra", "ctx_overlap", "cand_lat", "lat_match", "lat_conflict", "lat_missing", "nn_cat_char_max", "nn_cat_char_sum", "nn_cat_dense_max", "nn_cat_dense_sum", "nn_cat_cnt", "nn_char_max", "nn_char_sum", "nn_dense_max", "nn_dense_sum", "nn_cnt", "nn_entctx_max", "nn_ctx_max", "prior", "exact", "mention", "n_desc", "billable", "code_len", "chapter", "block_prior", "is_unspec", "is_other", "enc7", "char_max_rank", "char_max_gap", "word_max_rank", "word_max_gap", "char_var_rank", "char_var_gap", "sapbert_max_rank", "sapbert_max_gap", "sapbert_var_rank", "sapbert_var_gap", "gte_max_rank", "gte_max_gap", "gte_var_rank", "gte_var_gap", "qwen3_max_rank", "qwen3_max_gap", "qwen3_var_rank", "qwen3_var_gap", "fz_tset_rank", "fz_tset_gap", "nn_cat_char_max_rank", "nn_cat_char_max_gap", "nn_cat_dense_max_rank", "nn_cat_dense_max_gap", "nn_char_max_rank", "nn_char_max_gap", "nn_dense_max_rank", "nn_dense_max_gap", "nn_entctx_max_rank", "nn_entctx_max_gap", "nn_ctx_max_rank", "nn_ctx_max_gap", "prior_rank", "prior_gap", "q_len", "q_ntok", "q_digit", "q_abbr", "q_nvar", "q_lat", "q_neg", "q_hist", "q_fam", "subconcept", "n_cand"]} \ No newline at end of file diff --git a/ranker_ICD10CM_s1_d3llm7e4.txt b/ranker_ICD10CM_s1_d3llm7e4.txt new file mode 100644 index 0000000000000000000000000000000000000000..6f9c2dc28464de788c1b8331ba33f22fe73fee4b --- /dev/null +++ b/ranker_ICD10CM_s1_d3llm7e4.txt @@ -0,0 +1,2347 @@ +tree +version=v4 +num_class=1 +num_tree_per_iteration=1 +label_index=0 +max_feature_idx=100 +objective=lambdarank +feature_names=char_max word_max char_var sapbert_max sapbert_pref sapbert_var reading_ctx reading_ctx_gap ctx_dense gte_max gte_pref gte_var qwen3_max qwen3_pref qwen3_var num_match num_conflict cand_neg cand_hist neg_match hist_match fz_ratio fz_tset fz_partial fz_tsort tok_qcov tok_dcov tok_dextra ctx_overlap cand_lat lat_match lat_conflict lat_missing nn_cat_char_max nn_cat_char_sum nn_cat_dense_max nn_cat_dense_sum nn_cat_cnt nn_char_max nn_char_sum nn_dense_max nn_dense_sum nn_cnt nn_entctx_max nn_ctx_max prior exact mention n_desc billable code_len chapter block_prior is_unspec is_other enc7 char_max_rank char_max_gap word_max_rank word_max_gap char_var_rank char_var_gap sapbert_max_rank sapbert_max_gap 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7.4490281959297127 10.632919992320238 8.1519486605620823 3.1415628590129927 4.4032788922340842 +leaf_count=4673 54 164453 12562 252 4906 1275 1608 978 19 1826 124 234 5593 3834 2228 15437 182 8629 20584 167 24256 1139 5301 2621 45 188 802 154 132 4629 1130 417 173 31138 814 266 124 571 7117 9953 4824 1197 162 17382 1722 66 2038 1061 119 258 74 53 28 118 1635 19981 269 130 139 1440 1370 1607 +internal_value=-0.000456209 -0.00347892 0.00841042 0.0143207 0.0259217 -0.0203346 -0.02788 -0.00954542 -0.000828869 -0.00275377 0.0159648 -0.00464506 -0.00218499 -0.0176816 -0.0251882 -0.0159224 -0.0476354 0.00120061 0.0311568 -0.0273039 -0.00508059 -0.00121947 -0.0239291 0.00856208 -0.0111055 -0.00851896 -0.0193443 -0.0165716 -0.0380094 0.0334285 -0.00943002 -0.0163443 -0.00641143 -0.030361 -0.00969276 0.0277341 0.0100188 0.00158248 0.00960694 0.00648253 0.0318737 -0.000358178 -0.00988535 -0.00788795 0.00876355 0.0183871 -0.000691101 0.0302573 0.00239243 -0.0119366 -0.0328672 0.00935422 -0.0447924 -0.0304581 0.00968777 0.0214875 0.00110265 0.0099565 0.0163793 0.00440248 -0.0145194 -0.0335453 +internal_weight=563.412 420.625 142.787 105.579 74.0839 56.2397 45.0011 37.2086 364.385 327.664 36.7212 301.474 254.598 46.8765 38.0344 49.6074 13.7442 204.99 66.153 30.8624 113.33 92.7081 20.6221 91.66 24.2903 31.4947 21.7839 30.5875 10.5746 63.9945 11.6921 7.9309 16.4328 18.0319 16.1185 25.0292 12.3722 55.9262 35.7356 62.1205 7.67592 5.6526 7.27207 15.5808 9.19238 26.19 10.4064 15.7837 54.4446 18.6109 9.11066 9.50027 7.84085 6.57338 11.2386 8.79528 5.19927 35.8337 28.3847 17.7517 9.59979 6.45823 +internal_count=396261 318263 77998 32123 30788 188952 166061 45875 129311 127486 1825 119379 112856 6523 6289 22011 4016 90845 30119 6574 52803 23246 29557 38042 2273 1335 1147 2112 286 25213 1254 669 345 33313 981 571 305 35421 34850 21134 5963 2175 181 26221 8839 8107 6711 1396 15171 10366 10055 311 9981 172 22891 21616 335 4805 4675 4536 3096 1726 +cat_boundaries=0 1 2 +cat_threshold=33694695 51348384 +is_linear=0 +shrinkage=0.05 + + +end of trees + +feature_importances: +sapbert_max_gap=193 +gte_max_gap=192 +qwen3_max_gap=186 +nn_dense_max_gap=164 +chapter=162 +n_cand=143 +nn_char_max_gap=142 +prior=137 +gte_var_gap=133 +gte_max_rank=130 +sapbert_pref=129 +ctx_dense=126 +billable=120 +sapbert_var_gap=115 +word_max_gap=114 +qwen3_max_rank=111 +prior_gap=111 +sapbert_max_rank=110 +nn_cat_dense_max_gap=101 +block_prior=100 +sapbert_max=94 +char_var_gap=90 +fz_ratio=88 +qwen3_var_gap=88 +sapbert_var=87 +gte_var=87 +sapbert_var_rank=87 +fz_tset_gap=85 +char_var=84 +gte_pref=81 +nn_dense_sum=81 +char_max_gap=81 +qwen3_pref=79 +gte_var_rank=78 +gte_max=77 +nn_cat_char_max_gap=77 +fz_tset=75 +is_other=75 +nn_dense_max=73 +char_max_rank=73 +char_var_rank=70 +nn_cat_dense_max=69 +fz_tset_rank=69 +qwen3_var=68 +nn_cat_char_max_rank=68 +prior_rank=68 +fz_tsort=66 +reading_ctx=64 +word_max_rank=64 +nn_cat_dense_sum=63 +nn_dense_max_rank=62 +fz_partial=61 +nn_ctx_max=61 +qwen3_max=59 +is_unspec=59 +nn_char_sum=58 +nn_entctx_max_gap=58 +char_max=55 +nn_cat_char_sum=55 +nn_char_max=54 +nn_entctx_max=53 +nn_cat_char_max=52 +nn_ctx_max_gap=52 +nn_cat_dense_max_rank=51 +word_max=50 +q_len=50 +nn_char_max_rank=49 +reading_ctx_gap=45 +qwen3_var_rank=43 +tok_dextra=40 +nn_entctx_max_rank=39 +n_desc=38 +nn_ctx_max_rank=29 +code_len=26 +nn_cat_cnt=21 +tok_qcov=20 +ctx_overlap=19 +tok_dcov=16 +cand_neg=15 +q_nvar=15 +nn_cnt=14 +q_ntok=14 +enc7=11 +neg_match=5 +lat_match=2 +q_digit=2 +num_match=1 +hist_match=1 +lat_missing=1 +q_neg=1 +q_hist=1 + +parameters: +[boosting: gbdt] +[objective: lambdarank] +[metric: map] +[tree_learner: serial] +[device_type: cpu] +[data_sample_strategy: bagging] +[data: ] +[valid: ] +[num_iterations: 103] +[learning_rate: 0.05] +[num_leaves: 63] +[num_threads: 16] +[seed: 13] +[deterministic: 1] +[force_col_wise: 1] +[force_row_wise: 0] +[histogram_pool_size: -1] +[max_depth: -1] +[min_data_in_leaf: 20] +[min_sum_hessian_in_leaf: 0.001] +[bagging_fraction: 0.8] +[pos_bagging_fraction: 1] +[neg_bagging_fraction: 1] +[bagging_freq: 1] +[bagging_seed: 16376] +[bagging_by_query: 0] +[feature_fraction: 0.8] +[feature_fraction_bynode: 1] +[feature_fraction_seed: 20348] +[extra_trees: 0] +[extra_seed: 30076] +[early_stopping_round: 0] +[early_stopping_min_delta: 0] +[first_metric_only: 0] +[max_delta_step: 0] +[lambda_l1: 0] +[lambda_l2: 1] +[linear_lambda: 0] +[min_gain_to_split: 0] +[drop_rate: 0.1] +[max_drop: 50] +[skip_drop: 0.5] +[xgboost_dart_mode: 0] +[uniform_drop: 0] +[drop_seed: 24096] +[top_rate: 0.2] +[other_rate: 0.1] +[min_data_per_group: 100] +[max_cat_threshold: 32] +[cat_l2: 10] +[cat_smooth: 10] +[max_cat_to_onehot: 4] +[top_k: 20] +[monotone_constraints: ] +[monotone_constraints_method: basic] +[monotone_penalty: 0] +[feature_contri: ] +[forcedsplits_filename: ] +[refit_decay_rate: 0.9] +[cegb_tradeoff: 1] +[cegb_penalty_split: 0] +[cegb_penalty_feature_lazy: ] +[cegb_penalty_feature_coupled: ] +[path_smooth: 0] +[interaction_constraints: ] +[verbosity: -1] +[saved_feature_importance_type: 0] +[use_quantized_grad: 0] +[num_grad_quant_bins: 4] +[quant_train_renew_leaf: 0] +[stochastic_rounding: 1] +[linear_tree: 0] +[max_bin: 255] +[max_bin_by_feature: ] +[min_data_in_bin: 3] +[bin_construct_sample_cnt: 200000] +[data_random_seed: 81] +[is_enable_sparse: 1] +[enable_bundle: 1] +[use_missing: 1] +[zero_as_missing: 0] +[feature_pre_filter: 1] +[pre_partition: 0] +[two_round: 0] +[header: 0] +[label_column: ] +[weight_column: ] +[group_column: ] +[ignore_column: ] +[categorical_feature: 29,51,55,95,99] +[forcedbins_filename: ] +[precise_float_parser: 0] +[parser_config_file: ] +[objective_seed: 11872] +[num_class: 1] +[is_unbalance: 0] +[scale_pos_weight: 1] +[sigmoid: 1] +[boost_from_average: 1] +[reg_sqrt: 0] +[alpha: 0.9] +[fair_c: 1] +[poisson_max_delta_step: 0.7] +[tweedie_variance_power: 1.5] +[lambdarank_truncation_level: 20] +[lambdarank_norm: 1] +[label_gain: ] +[lambdarank_position_bias_regularization: 0] +[eval_at: 1] +[multi_error_top_k: 1] +[auc_mu_weights: ] +[num_machines: 1] +[local_listen_port: 12400] +[time_out: 120] +[machine_list_filename: ] +[machines: ] +[gpu_platform_id: -1] +[gpu_device_id: -1] +[gpu_device_id_list: ] +[gpu_use_dp: 0] +[num_gpu: 1] + +end of parameters + +pandas_categorical:[] diff --git a/ranker_ICD10CM_s1_sap4.json b/ranker_ICD10CM_s1_sap4.json new file mode 100644 index 0000000000000000000000000000000000000000..9d3473f03ea04d39c705b60891257271acff4ca6 --- /dev/null +++ b/ranker_ICD10CM_s1_sap4.json @@ -0,0 +1 @@ +{"cols": ["char_max", "word_max", "char_var", "sapbert_max", "sapbert_pref", "sapbert_var", "reading_ctx", "reading_ctx_gap", "ctx_dense", "num_match", "num_conflict", "cand_neg", "cand_hist", "neg_match", "hist_match", "fz_ratio", "fz_tset", "fz_partial", "fz_tsort", "tok_qcov", "tok_dcov", "tok_dextra", "ctx_overlap", "cand_lat", "lat_match", "lat_conflict", "lat_missing", "nn_cat_char_max", "nn_cat_char_sum", "nn_cat_dense_max", "nn_cat_dense_sum", "nn_cat_cnt", "nn_char_max", "nn_char_sum", "nn_dense_max", "nn_dense_sum", "nn_cnt", "nn_entctx_max", "nn_ctx_max", "prior", "exact", "mention", "n_desc", "billable", "code_len", "chapter", "block_prior", "is_unspec", "is_other", "enc7", "char_max_rank", "char_max_gap", "word_max_rank", "word_max_gap", "char_var_rank", "char_var_gap", "sapbert_max_rank", "sapbert_max_gap", "sapbert_var_rank", "sapbert_var_gap", "fz_tset_rank", "fz_tset_gap", "nn_cat_char_max_rank", "nn_cat_char_max_gap", "nn_cat_dense_max_rank", "nn_cat_dense_max_gap", "nn_char_max_rank", "nn_char_max_gap", "nn_dense_max_rank", "nn_dense_max_gap", "nn_entctx_max_rank", "nn_entctx_max_gap", "nn_ctx_max_rank", "nn_ctx_max_gap", "prior_rank", "prior_gap", "q_len", "q_ntok", "q_digit", "q_abbr", "q_nvar", "q_lat", "q_neg", "q_hist", "q_fam", "subconcept", "n_cand"]} \ No newline at end of file diff --git a/ranker_ICD10CM_s1_sap4.txt b/ranker_ICD10CM_s1_sap4.txt new file mode 100644 index 0000000000000000000000000000000000000000..61be3aceb73760a9eb20293bcc3b934990e3b384 --- /dev/null +++ b/ranker_ICD10CM_s1_sap4.txt @@ -0,0 +1,2158 @@ +tree +version=v4 +num_class=1 +num_tree_per_iteration=1 +label_index=0 +max_feature_idx=86 +objective=lambdarank +feature_names=char_max word_max char_var sapbert_max sapbert_pref sapbert_var reading_ctx reading_ctx_gap ctx_dense num_match num_conflict cand_neg cand_hist neg_match hist_match fz_ratio fz_tset fz_partial fz_tsort tok_qcov tok_dcov tok_dextra ctx_overlap cand_lat lat_match lat_conflict lat_missing nn_cat_char_max nn_cat_char_sum nn_cat_dense_max nn_cat_dense_sum nn_cat_cnt nn_char_max nn_char_sum nn_dense_max nn_dense_sum nn_cnt nn_entctx_max nn_ctx_max prior exact mention n_desc billable code_len chapter block_prior is_unspec is_other enc7 char_max_rank char_max_gap word_max_rank word_max_gap char_var_rank char_var_gap sapbert_max_rank sapbert_max_gap sapbert_var_rank sapbert_var_gap fz_tset_rank fz_tset_gap nn_cat_char_max_rank nn_cat_char_max_gap nn_cat_dense_max_rank nn_cat_dense_max_gap nn_char_max_rank nn_char_max_gap nn_dense_max_rank nn_dense_max_gap nn_entctx_max_rank nn_entctx_max_gap nn_ctx_max_rank nn_ctx_max_gap prior_rank prior_gap q_len q_ntok q_digit q_abbr q_nvar q_lat q_neg q_hist q_fam subconcept n_cand +feature_infos=[0:1.0000002384185791] [0:1.0000001192092896] [0:1.0000002384185791] [-0.36729863286018372:1.0000722408294678] [-0.38990747928619385:1.0000544786453247] [-0.20657619833946228:1.0000724792480469] [-0.16073939204216003:0.82179844379425049] [0:0.4222283661365509] [-0.26089823246002197:0.88825666904449463] [0:2] [0:1] [0:1] [0:1] [0:1] [0:1] [0:100] [0:100] [0:100] [0:100] [0:1] [0:1] [0:27] [0:5] -1:0:1:2:3 [0:1] [0:1] [0:1] [0:1.0000001192092896] [0:14.182402610778809] [0:1.0000008344650269] [0:10.127299308776855] [0:20] [0:1.0000001192092896] [0:10.082548141479492] [0:1.0000008344650269] [0:8.9456338882446289] [0:15] [0:0.98123562335968018] 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4.3898068892594875 7.0821864096342324 6.5829774476005678 6.5888609048743092 3.9655684115059548 3.7392440650728531 4.0822992478497317 2.5489581741276188 2.6556484848988466 9.4943005798631912 1.5638258193466743 3.4875210369355045 22.551895644533946 3.7031110625248393 5.6337797628402759 5.3551403658639156 4.1474996158358408 12.971721450951007 25.332631973873504 10.420379722745563 57.243034108223583 7.5782754774700143 2.0891316195957179 +leaf_count=389 1813 931 4556 6557 2239 572 2548 51 9020 46380 1816 1662 613 7875 335 627 573 56 1006 1471 4497 616 1009 1815 79 2030 1790 2522 196 41 40 394 398 4838 75 68 23 531 4279 445 6325 634 894 2074 40 91 583 44 1187 97 311 7337 100 838 608 1612 3721 92857 1340 9299 216 977 +internal_value=-0.00040625 -0.014024 0.00157415 0.0095454 0.0199008 0.00146796 0.00957632 -0.0005658 -0.00570693 -0.0232783 -0.00193617 -0.00303361 -0.0134958 0.00486724 -0.00823276 0.00876184 0.0195275 0.00270846 0.0231017 0.0167388 0.0219556 -0.000810515 -0.0082765 -0.00125574 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26849 11295 9633 26034 586 25448 2770 22678 2197 12445 10974 5113 7446 6437 251 25033 5861 5289 23003 160 119 2916 1404 9490 793 143 650 20983 11580 11049 6770 9403 1528 3889 91 22807 2373 1695 1651 1284 367 22716 7437 15279 14441 2220 8559 94670 12221 11616 605 2317 +is_linear=0 +shrinkage=0.05 + + +end of trees + +feature_importances: +sapbert_max_gap=270 +ctx_dense=206 +nn_dense_max_gap=175 +char_var_gap=162 +char_max_gap=152 +sapbert_pref=150 +chapter=145 +nn_char_max_gap=145 +word_max_gap=134 +sapbert_max_rank=133 +prior=132 +sapbert_var_gap=125 +sapbert_var=124 +char_var_rank=124 +block_prior=121 +n_cand=121 +nn_cat_dense_max_gap=120 +billable=119 +sapbert_var_rank=119 +nn_cat_dense_sum=107 +char_var=106 +fz_tset_gap=106 +sapbert_max=104 +fz_partial=103 +nn_dense_sum=103 +word_max_rank=97 +prior_gap=96 +char_max_rank=94 +fz_tsort=91 +nn_cat_char_max_gap=91 +nn_entctx_max_gap=91 +nn_char_sum=88 +nn_entctx_max=88 +char_max=87 +nn_cat_dense_max=87 +fz_ratio=85 +fz_tset_rank=80 +nn_dense_max_rank=75 +nn_ctx_max_gap=75 +prior_rank=74 +is_other=70 +nn_cat_char_max_rank=69 +reading_ctx=66 +fz_tset=62 +nn_char_max=61 +word_max=60 +nn_cat_dense_max_rank=59 +q_len=59 +reading_ctx_gap=55 +is_unspec=53 +nn_ctx_max=52 +nn_dense_max=51 +tok_dextra=46 +nn_cat_char_sum=44 +nn_char_max_rank=43 +nn_cat_char_max=42 +n_desc=33 +nn_ctx_max_rank=33 +tok_dcov=31 +ctx_overlap=30 +nn_entctx_max_rank=26 +code_len=22 +tok_qcov=21 +q_nvar=21 +nn_cat_cnt=16 +q_ntok=15 +cand_neg=12 +nn_cnt=12 +neg_match=7 +lat_match=4 +enc7=4 +exact=2 +num_match=1 +cand_hist=1 +hist_match=1 +q_neg=1 + +parameters: +[boosting: gbdt] +[objective: lambdarank] +[metric: map] +[tree_learner: serial] +[device_type: cpu] +[data_sample_strategy: bagging] +[data: ] +[valid: ] +[num_iterations: 95] +[learning_rate: 0.05] +[num_leaves: 63] +[num_threads: 16] +[seed: 13] +[deterministic: 1] +[force_col_wise: 1] +[force_row_wise: 0] +[histogram_pool_size: -1] +[max_depth: -1] +[min_data_in_leaf: 20] +[min_sum_hessian_in_leaf: 0.001] +[bagging_fraction: 0.8] +[pos_bagging_fraction: 1] +[neg_bagging_fraction: 1] +[bagging_freq: 1] +[bagging_seed: 16376] +[bagging_by_query: 0] +[feature_fraction: 0.8] +[feature_fraction_bynode: 1] +[feature_fraction_seed: 20348] +[extra_trees: 0] +[extra_seed: 30076] +[early_stopping_round: 0] +[early_stopping_min_delta: 0] +[first_metric_only: 0] +[max_delta_step: 0] +[lambda_l1: 0] +[lambda_l2: 1] +[linear_lambda: 0] +[min_gain_to_split: 0] +[drop_rate: 0.1] +[max_drop: 50] +[skip_drop: 0.5] +[xgboost_dart_mode: 0] +[uniform_drop: 0] +[drop_seed: 24096] +[top_rate: 0.2] +[other_rate: 0.1] +[min_data_per_group: 100] +[max_cat_threshold: 32] +[cat_l2: 10] +[cat_smooth: 10] +[max_cat_to_onehot: 4] +[top_k: 20] +[monotone_constraints: ] +[monotone_constraints_method: basic] +[monotone_penalty: 0] +[feature_contri: ] +[forcedsplits_filename: ] +[refit_decay_rate: 0.9] +[cegb_tradeoff: 1] +[cegb_penalty_split: 0] +[cegb_penalty_feature_lazy: ] +[cegb_penalty_feature_coupled: ] +[path_smooth: 0] +[interaction_constraints: ] +[verbosity: -1] +[saved_feature_importance_type: 0] +[use_quantized_grad: 0] +[num_grad_quant_bins: 4] +[quant_train_renew_leaf: 0] +[stochastic_rounding: 1] +[linear_tree: 0] +[max_bin: 255] +[max_bin_by_feature: ] +[min_data_in_bin: 3] +[bin_construct_sample_cnt: 200000] +[data_random_seed: 81] +[is_enable_sparse: 1] +[enable_bundle: 1] +[use_missing: 1] +[zero_as_missing: 0] +[feature_pre_filter: 1] +[pre_partition: 0] +[two_round: 0] +[header: 0] +[label_column: ] +[weight_column: ] +[group_column: ] +[ignore_column: ] +[categorical_feature: 23,45,49,81,85] +[forcedbins_filename: ] +[precise_float_parser: 0] +[parser_config_file: ] +[objective_seed: 11872] +[num_class: 1] +[is_unbalance: 0] +[scale_pos_weight: 1] +[sigmoid: 1] +[boost_from_average: 1] +[reg_sqrt: 0] +[alpha: 0.9] +[fair_c: 1] +[poisson_max_delta_step: 0.7] +[tweedie_variance_power: 1.5] +[lambdarank_truncation_level: 20] +[lambdarank_norm: 1] +[label_gain: ] +[lambdarank_position_bias_regularization: 0] +[eval_at: 1] +[multi_error_top_k: 1] +[auc_mu_weights: ] +[num_machines: 1] +[local_listen_port: 12400] +[time_out: 120] +[machine_list_filename: ] +[machines: ] +[gpu_platform_id: -1] +[gpu_device_id: -1] +[gpu_device_id_list: ] +[gpu_use_dp: 0] +[num_gpu: 1] + +end of parameters + +pandas_categorical:[] diff --git a/ranker_ICD10CM_s2_d3ce4.json b/ranker_ICD10CM_s2_d3ce4.json new file mode 100644 index 0000000000000000000000000000000000000000..cf6ea892235f7dfb464a826662555114eebf9636 --- /dev/null +++ b/ranker_ICD10CM_s2_d3ce4.json @@ -0,0 +1 @@ +{"cols": ["char_max", "word_max", "char_var", "sapbert_max", "sapbert_pref", "sapbert_var", "reading_ctx", "reading_ctx_gap", "ctx_dense", "gte_max", "gte_pref", "gte_var", "qwen3_max", "qwen3_pref", "qwen3_var", "num_match", "num_conflict", "cand_neg", "cand_hist", "neg_match", "hist_match", "fz_ratio", "fz_tset", "fz_partial", "fz_tsort", "tok_qcov", "tok_dcov", "tok_dextra", "ctx_overlap", "cand_lat", "lat_match", "lat_conflict", "lat_missing", "nn_cat_char_max", "nn_cat_char_sum", "nn_cat_dense_max", "nn_cat_dense_sum", "nn_cat_cnt", "nn_char_max", "nn_char_sum", "nn_dense_max", "nn_dense_sum", "nn_cnt", "nn_entctx_max", "nn_ctx_max", "prior", "exact", "mention", "n_desc", "billable", "code_len", "chapter", "block_prior", "is_unspec", "is_other", "enc7", "char_max_rank", "char_max_gap", "word_max_rank", "word_max_gap", "char_var_rank", "char_var_gap", "sapbert_max_rank", "sapbert_max_gap", "sapbert_var_rank", "sapbert_var_gap", "gte_max_rank", "gte_max_gap", "gte_var_rank", "gte_var_gap", "qwen3_max_rank", "qwen3_max_gap", "qwen3_var_rank", "qwen3_var_gap", "fz_tset_rank", "fz_tset_gap", "nn_cat_char_max_rank", "nn_cat_char_max_gap", "nn_cat_dense_max_rank", "nn_cat_dense_max_gap", "nn_char_max_rank", "nn_char_max_gap", "nn_dense_max_rank", "nn_dense_max_gap", "nn_entctx_max_rank", "nn_entctx_max_gap", "nn_ctx_max_rank", "nn_ctx_max_gap", "prior_rank", "prior_gap", "q_len", "q_ntok", "q_digit", "q_abbr", "q_nvar", "q_lat", "q_neg", "q_hist", "q_fam", "subconcept", "n_cand", "s1", "s1_rank", "s1_p", "s1_gap", "xs_cooc", "xs_cooc_top1", "xs_sim", "xs_sim_top1", "ce", "ce_lp", "ce_rank", "ce_gap", "ce_lp_rank", "ce_lp_gap"]} \ No newline at end of file diff --git a/ranker_ICD10CM_s2_d3ce4.txt b/ranker_ICD10CM_s2_d3ce4.txt new file mode 100644 index 0000000000000000000000000000000000000000..6c68d420b341636e8033bfd94957e12f1798e6bb --- /dev/null +++ b/ranker_ICD10CM_s2_d3ce4.txt @@ -0,0 +1,1601 @@ +tree +version=v4 +num_class=1 +num_tree_per_iteration=1 +label_index=0 +max_feature_idx=114 +objective=lambdarank +feature_names=char_max word_max char_var sapbert_max sapbert_pref sapbert_var reading_ctx reading_ctx_gap ctx_dense gte_max gte_pref gte_var qwen3_max qwen3_pref qwen3_var num_match num_conflict cand_neg cand_hist neg_match hist_match fz_ratio fz_tset fz_partial fz_tsort tok_qcov tok_dcov tok_dextra ctx_overlap cand_lat lat_match lat_conflict lat_missing nn_cat_char_max nn_cat_char_sum nn_cat_dense_max nn_cat_dense_sum nn_cat_cnt nn_char_max nn_char_sum nn_dense_max nn_dense_sum nn_cnt nn_entctx_max nn_ctx_max prior exact mention n_desc billable code_len chapter block_prior is_unspec is_other enc7 char_max_rank char_max_gap word_max_rank word_max_gap char_var_rank char_var_gap sapbert_max_rank sapbert_max_gap sapbert_var_rank sapbert_var_gap gte_max_rank gte_max_gap gte_var_rank gte_var_gap qwen3_max_rank qwen3_max_gap qwen3_var_rank qwen3_var_gap fz_tset_rank fz_tset_gap nn_cat_char_max_rank nn_cat_char_max_gap nn_cat_dense_max_rank nn_cat_dense_max_gap nn_char_max_rank nn_char_max_gap nn_dense_max_rank nn_dense_max_gap nn_entctx_max_rank nn_entctx_max_gap nn_ctx_max_rank nn_ctx_max_gap prior_rank prior_gap q_len q_ntok q_digit q_abbr q_nvar q_lat q_neg q_hist q_fam subconcept n_cand s1 s1_rank s1_p s1_gap xs_cooc xs_cooc_top1 xs_sim xs_sim_top1 ce ce_lp ce_rank ce_gap ce_lp_rank 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1.540312801429536 1.2985445353551766 6.1444331135135144 9.5863678613241046 1.1245262594893555 1.1394909418886507 7.036262915993575 2.7630060805531675 4.9311501934134867 15.750660409394188 5.7970078992948384 3.3316448213590766 1.7496312531875435 5.3772051138512325 2.5073829718166962 2.0836793176131323 2.8123420374759007 7.4193857132049725 4.2117832693329547 3.7807835242419952 5.3161125241313121 9.859887012105899 3.2421679484250481 1.3604141125106242 2.2683392392355008 12.53993498458294 4.2448845579638146 1.6509041024837632 7.3910954886814579 7.7790935615776133 17.579051469569094 +leaf_count=3272 1136 160 110 969 636 275 197 340 141 74 371 970 765 343 367 104 1088 462 78 1153 1135 264 262 222 59 287 43 75 891 315 93 40 150 179 9426 24 33 127 88 144 478 184 294 37 328 171 128 181 260 347 87 520 689 206 95 177 1140 82 53 147 156 924 +internal_value=0.000428204 0.00178417 0.000977181 -0.0019758 -0.00833352 -0.0151723 -0.0263406 0.00640368 0.00426657 -0.0122424 -0.0173855 -0.0044619 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14.8083 8.02567 13.9995 8.51562 47.3847 25.3581 +internal_count=33552 18566 18406 13699 8252 5364 2945 2888 5447 673 2309 2419 4774 4009 1960 4707 3812 895 1388 14986 4407 1778 1359 300 1436 599 1069 2424 2548 1657 1097 133 433 283 10579 312 531 160 898 232 1625 1052 649 1060 403 355 171 524 666 607 964 689 799 1342 573 1514 1317 169 1023 171 2049 1080 +is_linear=0 +shrinkage=0.05 + + +end of trees + +feature_importances: +s1_p=196 +ce_lp=151 +ce=142 +ctx_dense=83 +xs_cooc=82 +xs_sim_top1=81 +s1_gap=80 +ce_gap=75 +ce_rank=71 +sapbert_max_gap=69 +sapbert_var_gap=69 +gte_var_gap=66 +s1=66 +qwen3_max_gap=65 +qwen3_var_gap=65 +reading_ctx_gap=63 +xs_sim=62 +fz_partial=60 +fz_tset_gap=60 +nn_char_max_gap=60 +sapbert_max=59 +reading_ctx=58 +sapbert_pref=57 +qwen3_var=57 +char_var_gap=56 +fz_tset_rank=55 +prior_gap=55 +gte_var_rank=54 +char_max=53 +gte_var=52 +word_max_gap=51 +fz_tsort=50 +gte_max_gap=50 +n_cand=50 +char_max_gap=48 +fz_ratio=47 +nn_cat_dense_max_rank=46 +nn_dense_max_gap=46 +nn_entctx_max_gap=46 +gte_pref=45 +block_prior=45 +char_var_rank=45 +nn_cat_dense_max=43 +char_max_rank=43 +nn_cat_char_max_rank=43 +q_len=43 +qwen3_pref=42 +gte_max=41 +qwen3_var_rank=40 +prior_rank=40 +prior=39 +qwen3_max=38 +sapbert_var_rank=38 +qwen3_max_rank=38 +ce_lp_gap=38 +sapbert_var=37 +nn_entctx_max=37 +word_max_rank=37 +nn_cat_char_sum=36 +sapbert_max_rank=36 +word_max=35 +nn_ctx_max=35 +nn_cat_dense_sum=34 +nn_dense_max=34 +gte_max_rank=34 +nn_ctx_max_gap=34 +nn_char_max=33 +nn_dense_sum=33 +nn_cat_char_max_gap=31 +char_var=30 +chapter=29 +nn_dense_max_rank=28 +nn_cat_char_max=27 +fz_tset=26 +nn_cat_dense_max_gap=25 +nn_char_sum=23 +billable=23 +nn_char_max_rank=23 +xs_cooc_top1=22 +tok_dextra=21 +nn_entctx_max_rank=21 +s1_rank=19 +nn_cat_cnt=18 +n_desc=18 +tok_dcov=17 +nn_ctx_max_rank=16 +is_other=15 +ce_lp_rank=12 +code_len=11 +q_nvar=11 +q_ntok=9 +neg_match=8 +tok_qcov=8 +is_unspec=8 +nn_cnt=5 +cand_neg=1 +ctx_overlap=1 + +parameters: +[boosting: gbdt] +[objective: lambdarank] +[metric: map] +[tree_learner: serial] +[device_type: cpu] +[data_sample_strategy: bagging] +[data: ] +[valid: ] +[num_iterations: 69] +[learning_rate: 0.05] +[num_leaves: 63] +[num_threads: 16] +[seed: 13] +[deterministic: 1] +[force_col_wise: 1] +[force_row_wise: 0] +[histogram_pool_size: -1] +[max_depth: -1] +[min_data_in_leaf: 20] +[min_sum_hessian_in_leaf: 0.001] +[bagging_fraction: 0.8] +[pos_bagging_fraction: 1] +[neg_bagging_fraction: 1] +[bagging_freq: 1] +[bagging_seed: 16376] +[bagging_by_query: 0] +[feature_fraction: 0.8] +[feature_fraction_bynode: 1] +[feature_fraction_seed: 20348] +[extra_trees: 0] +[extra_seed: 30076] +[early_stopping_round: 0] +[early_stopping_min_delta: 0] +[first_metric_only: 0] +[max_delta_step: 0] +[lambda_l1: 0] +[lambda_l2: 1] +[linear_lambda: 0] +[min_gain_to_split: 0] +[drop_rate: 0.1] +[max_drop: 50] +[skip_drop: 0.5] +[xgboost_dart_mode: 0] +[uniform_drop: 0] +[drop_seed: 24096] +[top_rate: 0.2] +[other_rate: 0.1] +[min_data_per_group: 100] +[max_cat_threshold: 32] +[cat_l2: 10] +[cat_smooth: 10] +[max_cat_to_onehot: 4] +[top_k: 20] +[monotone_constraints: ] +[monotone_constraints_method: basic] +[monotone_penalty: 0] +[feature_contri: ] +[forcedsplits_filename: ] +[refit_decay_rate: 0.9] +[cegb_tradeoff: 1] +[cegb_penalty_split: 0] +[cegb_penalty_feature_lazy: ] +[cegb_penalty_feature_coupled: ] +[path_smooth: 0] +[interaction_constraints: ] +[verbosity: -1] +[saved_feature_importance_type: 0] +[use_quantized_grad: 0] +[num_grad_quant_bins: 4] +[quant_train_renew_leaf: 0] +[stochastic_rounding: 1] +[linear_tree: 0] +[max_bin: 255] +[max_bin_by_feature: ] +[min_data_in_bin: 3] +[bin_construct_sample_cnt: 200000] +[data_random_seed: 81] +[is_enable_sparse: 1] +[enable_bundle: 1] +[use_missing: 1] +[zero_as_missing: 0] +[feature_pre_filter: 1] +[pre_partition: 0] +[two_round: 0] +[header: 0] +[label_column: ] +[weight_column: ] +[group_column: ] +[ignore_column: ] +[categorical_feature: 29,51,55,95,99] +[forcedbins_filename: ] +[precise_float_parser: 0] +[parser_config_file: ] +[objective_seed: 11872] +[num_class: 1] +[is_unbalance: 0] +[scale_pos_weight: 1] +[sigmoid: 1] +[boost_from_average: 1] +[reg_sqrt: 0] +[alpha: 0.9] +[fair_c: 1] +[poisson_max_delta_step: 0.7] +[tweedie_variance_power: 1.5] +[lambdarank_truncation_level: 20] +[lambdarank_norm: 1] +[label_gain: ] +[lambdarank_position_bias_regularization: 0] +[eval_at: 1] +[multi_error_top_k: 1] +[auc_mu_weights: ] +[num_machines: 1] +[local_listen_port: 12400] +[time_out: 120] +[machine_list_filename: ] +[machines: ] +[gpu_platform_id: -1] +[gpu_device_id: -1] +[gpu_device_id_list: ] +[gpu_use_dp: 0] +[num_gpu: 1] + +end of parameters + +pandas_categorical:[] diff --git a/ranker_ICD10CM_s2_d3llm14e4.json b/ranker_ICD10CM_s2_d3llm14e4.json new file mode 100644 index 0000000000000000000000000000000000000000..f8a7926968ac64dfdaa9e4b20af62a99bfbef0f1 --- /dev/null +++ b/ranker_ICD10CM_s2_d3llm14e4.json @@ -0,0 +1 @@ +{"cols": ["char_max", "word_max", "char_var", "sapbert_max", "sapbert_pref", "sapbert_var", "reading_ctx", "reading_ctx_gap", "ctx_dense", "gte_max", "gte_pref", "gte_var", "qwen3_max", "qwen3_pref", "qwen3_var", "num_match", "num_conflict", "cand_neg", "cand_hist", "neg_match", "hist_match", "fz_ratio", "fz_tset", "fz_partial", "fz_tsort", "tok_qcov", "tok_dcov", "tok_dextra", "ctx_overlap", "cand_lat", "lat_match", "lat_conflict", "lat_missing", "nn_cat_char_max", "nn_cat_char_sum", "nn_cat_dense_max", "nn_cat_dense_sum", "nn_cat_cnt", "nn_char_max", "nn_char_sum", "nn_dense_max", "nn_dense_sum", "nn_cnt", "nn_entctx_max", "nn_ctx_max", "prior", "exact", "mention", "n_desc", "billable", "code_len", "chapter", "block_prior", "is_unspec", "is_other", "enc7", "char_max_rank", "char_max_gap", "word_max_rank", "word_max_gap", "char_var_rank", "char_var_gap", "sapbert_max_rank", "sapbert_max_gap", "sapbert_var_rank", "sapbert_var_gap", "gte_max_rank", "gte_max_gap", "gte_var_rank", "gte_var_gap", "qwen3_max_rank", "qwen3_max_gap", "qwen3_var_rank", "qwen3_var_gap", "fz_tset_rank", "fz_tset_gap", "nn_cat_char_max_rank", "nn_cat_char_max_gap", "nn_cat_dense_max_rank", "nn_cat_dense_max_gap", "nn_char_max_rank", "nn_char_max_gap", "nn_dense_max_rank", "nn_dense_max_gap", "nn_entctx_max_rank", "nn_entctx_max_gap", "nn_ctx_max_rank", "nn_ctx_max_gap", "prior_rank", "prior_gap", "q_len", "q_ntok", "q_digit", "q_abbr", "q_nvar", "q_lat", "q_neg", "q_hist", "q_fam", "subconcept", "n_cand", "s1", "s1_rank", "s1_p", "s1_gap", "xs_cooc", "xs_cooc_top1", "xs_sim", "xs_sim_top1", "llm_lp", "llm_lp_rank", "llm_lp_gap", "ce", "ce_lp", "ce_rank", "ce_gap", "ce_lp_rank", "ce_lp_gap"]} \ No newline at end of file diff --git a/ranker_ICD10CM_s2_d3llm14e4.txt b/ranker_ICD10CM_s2_d3llm14e4.txt new file mode 100644 index 0000000000000000000000000000000000000000..297089098cc0db2b7f4158cdddad68d9e74412bc --- /dev/null +++ b/ranker_ICD10CM_s2_d3llm14e4.txt @@ -0,0 +1,972 @@ +tree +version=v4 +num_class=1 +num_tree_per_iteration=1 +label_index=0 +max_feature_idx=117 +objective=lambdarank +feature_names=char_max word_max char_var sapbert_max sapbert_pref sapbert_var reading_ctx reading_ctx_gap ctx_dense gte_max gte_pref gte_var qwen3_max qwen3_pref qwen3_var num_match num_conflict cand_neg cand_hist neg_match hist_match fz_ratio fz_tset fz_partial fz_tsort tok_qcov tok_dcov tok_dextra ctx_overlap cand_lat lat_match lat_conflict lat_missing nn_cat_char_max nn_cat_char_sum nn_cat_dense_max nn_cat_dense_sum nn_cat_cnt nn_char_max nn_char_sum nn_dense_max nn_dense_sum nn_cnt nn_entctx_max nn_ctx_max prior exact mention n_desc billable code_len chapter block_prior is_unspec is_other enc7 char_max_rank char_max_gap word_max_rank word_max_gap char_var_rank char_var_gap sapbert_max_rank sapbert_max_gap sapbert_var_rank sapbert_var_gap gte_max_rank gte_max_gap gte_var_rank gte_var_gap qwen3_max_rank qwen3_max_gap qwen3_var_rank qwen3_var_gap fz_tset_rank fz_tset_gap nn_cat_char_max_rank nn_cat_char_max_gap nn_cat_dense_max_rank nn_cat_dense_max_gap nn_char_max_rank nn_char_max_gap nn_dense_max_rank nn_dense_max_gap nn_entctx_max_rank nn_entctx_max_gap nn_ctx_max_rank nn_ctx_max_gap prior_rank prior_gap q_len q_ntok q_digit q_abbr q_nvar q_lat q_neg q_hist q_fam subconcept n_cand s1 s1_rank s1_p s1_gap xs_cooc xs_cooc_top1 xs_sim xs_sim_top1 llm_lp llm_lp_rank llm_lp_gap ce ce_lp ce_rank ce_gap ce_lp_rank ce_lp_gap +feature_infos=[0:1.0000002384185791] [0:1.0000001192092896] [0:1.0000002384185791] [-0.078878216445446014:1.0000715255737305] [-0.10396952927112579:1.00006103515625] [-0.18628421425819397:1.0000715255737305] [-0.16074290871620178:0.82175421714782715] [0:0.40820926427841187] [-0.12654291093349457:0.93806958198547363] [0.67732530832290649:1.0000559091567993] [0.67671990394592285:1.0000412464141846] [0.67732530832290649:1.0002433061599731] [0.1988551914691925:0.84735560417175293] [0.16513721644878387:0.84735560417175293] 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[0:0.98131084442138672] [1:21] [0:1.0000001192092896] [1:74] [0:3.2958368660043291] [2:110] [1:15] [0:1] [0:1] [0:6] -1:0:1:2:3 [0:1] [0:1] [0:1] none [66:644] [-4.9941094830467794:4.392090570308592] [0:19] [9.5665172382360258e-05:0.9941365733767108] [0:9.2390463310796243] [0:0.99393557450742864] [0:1] [-0.17931083820428986:0.99128901638374345] [-0.18872827291488647:1.0001242160797119] [-39.4375:0] [1:10] [0:39.4375] [-5.375:5.1875] [-11.324056625366211:-0.0010972023010253906] [1:16] [0:10.25] [1:16] [0:10.25] +tree_sizes=6861 6854 6879 6886 6831 6864 6843 6839 6846 6850 6853 6857 6847 6857 6837 6858 6874 6845 6866 6846 6872 6877 6859 6863 6867 6858 6877 6886 6866 6866 6907 6854 6883 6891 6886 6877 6874 6913 + +Tree=0 +num_leaves=63 +num_cat=0 +split_feature=103 109 109 103 103 104 103 113 114 57 40 103 111 111 27 109 38 14 115 89 103 71 33 0 113 24 77 61 67 3 113 66 109 108 103 105 56 113 103 110 104 109 89 38 69 113 115 105 104 27 113 62 4 113 114 105 57 81 103 109 80 62 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1.0853759031742809 10.877703481353821 11.136481119785454 27.24741486390122 6.099322607740759 4.482230882626026 11.008274018764501 7.1042761951684943 5.4915612570475778 3.6905251964926737 1.4703534781001506 35.47750441590324 4.6401361336465916 17.587097834330059 3.1170754285994917 2.7553858719766131 12.206196494400499 31.95548742718529 1.8587145311757982 14.108755948953329 3.4645617771893731 5.0465961983427396 5.9874308686703435 3.9506805068813255 3.8476773686707011 2.8508404828608036 2.1895176805555812 160.26587512111291 3.0546606592833987 1.312693491578101 0.79366759536787768 0.86755280732178164 2.2282907887129113 2.626064797397702 3.7990100313909343 1.0604497452732164 2.4372267629951239 1.623127735685556 1.2640800836961705 3.1630871356464914 2.7168654296547174 23.182942897314206 1.0373939180281002 2.7656633402220896 1.2823806928936381 10.392202700721102 0.94325394043698985 24.007579198572785 3.0807823538780212 3.2627325430512411 5.6908517396077514 5.9717463784618303 3.6231150839012107 1.7029874296858896 3.4099260347429663 17.422069760039456 11.752635885844937 34.029435124713928 +leaf_count=264 381 109 658 13013 44 267 1520 2574 529 52 254 81 332 194 234 739 139 383 149 156 402 212 20 83 27 59 62 38 24 24 11 937 44 5 13 47 384 205 192 43 34 126 92 216 56 4079 27 26 148 653 20 146 16 17 61 587 284 141 120 508 1078 297 +internal_value=0.000758297 -0.0214557 0.0167918 -0.0333731 0.013186 -0.0184394 -0.00327057 -0.0284682 -0.00805511 0.0150967 0.00779771 0.01587 0.00253417 -0.00962292 0.00314505 0.0129377 0.0179408 -0.00512062 -0.0153337 0.0246901 -0.0216651 0.0176382 0.0156378 0.0166095 0.01487 0.0157282 0.000494909 0.00751425 0.0117146 -0.0293287 -0.0169379 0.0185371 0.00671314 0.0108397 -0.0430009 -0.0433259 -0.0281883 -0.0363133 0.00904881 -0.042902 0.0197768 0.0220728 0.0315223 -0.0460878 -0.0334398 -0.0475004 0.017198 0.015785 0.0292796 -0.0276099 -0.0441901 0.0252562 -0.000719692 -0.0245895 0.0271115 -0.0247356 0.00946921 0.0236311 -0.0156517 0.022934 -0.0325379 0.0197854 +internal_weight=723.098 302.983 420.114 182.53 366.663 74.1397 120.454 54.5259 23.3218 348.144 17.2224 343.661 97.9817 45.2177 29.5921 52.764 47.2725 26.5528 7.75721 39.5153 18.5198 317.109 285.153 278.049 263.94 260.475 51.2837 45.2962 43.4375 6.69852 19.7766 209.192 48.9259 45.8713 31.2042 108.39 33.7643 27.737 6.0273 25.1109 36.739 13.8955 12.2724 30.4105 4.02956 24.0505 19.9298 41.8417 36.7599 22.4719 12.0797 32.7883 8.78074 5.69996 6.77623 9.66227 19.6137 12.5807 7.03304 18.8924 15.6256 39.076 +internal_count=33636 29553 4083 22960 3425 4997 6593 4185 1382 2759 853 2707 4400 2737 1550 1663 1331 499 288 1043 666 2208 1996 1915 1832 1805 381 319 299 48 394 1424 487 443 2803 17963 4950 4374 576 4169 251 472 346 2790 61 4126 769 382 887 2193 1540 213 67 51 105 781 812 408 404 742 1187 356 +cat_boundaries=0 1 +cat_threshold=37758537 +is_linear=0 +shrinkage=0.05 + + +end of trees + +feature_importances: +llm_lp=139 +s1_p=135 +ce_lp=94 +s1_gap=80 +ce=68 +xs_cooc=63 +ce_gap=47 +llm_lp_gap=45 +ctx_dense=39 +s1=39 +llm_lp_rank=38 +char_var_gap=34 +char_max_gap=33 +gte_max_gap=32 +sapbert_max_gap=31 +reading_ctx_gap=30 +fz_tset_rank=30 +xs_sim=30 +ce_rank=30 +fz_tset_gap=29 +sapbert_pref=28 +gte_var=28 +nn_cat_dense_max=28 +qwen3_max_gap=28 +reading_ctx=27 +qwen3_var_gap=27 +nn_cat_char_max_gap=27 +nn_char_max_gap=27 +fz_ratio=26 +nn_entctx_max=26 +n_cand=26 +sapbert_max=25 +fz_tsort=25 +gte_var_gap=25 +nn_ctx_max_gap=24 +fz_partial=23 +sapbert_var_gap=23 +prior_gap=23 +nn_dense_max=22 +nn_entctx_max_gap=22 +xs_sim_top1=22 +gte_pref=21 +qwen3_max=21 +qwen3_pref=21 +word_max_rank=21 +char_var=20 +sapbert_var=20 +qwen3_var=20 +nn_cat_dense_sum=20 +word_max_gap=20 +qwen3_max_rank=20 +nn_cat_dense_max_rank=20 +ce_lp_gap=20 +tok_dextra=19 +nn_ctx_max=19 +char_max_rank=19 +sapbert_max_rank=19 +gte_var_rank=19 +nn_cat_char_max_rank=19 +sapbert_var_rank=18 +qwen3_var_rank=18 +nn_dense_max_gap=18 +char_var_rank=17 +nn_char_max_rank=17 +gte_max=16 +tok_dcov=16 +nn_cat_char_max=16 +char_max=15 +billable=15 +nn_cat_dense_max_gap=15 +xs_cooc_top1=15 +nn_cat_char_sum=14 +block_prior=13 +q_len=13 +nn_char_max=12 +gte_max_rank=12 +fz_tset=11 +nn_dense_sum=11 +prior_rank=11 +word_max=10 +n_desc=10 +s1_rank=10 +prior=9 +nn_dense_max_rank=9 +nn_cat_cnt=8 +nn_char_sum=8 +nn_entctx_max_rank=7 +tok_qcov=5 +chapter=5 +nn_ctx_max_rank=5 +ce_lp_rank=5 +code_len=3 +q_ntok=3 +cand_neg=2 +nn_cnt=2 +is_other=2 +q_nvar=2 +ctx_overlap=1 +is_unspec=1 + +parameters: +[boosting: gbdt] +[objective: lambdarank] +[metric: map] +[tree_learner: serial] +[device_type: cpu] +[data_sample_strategy: bagging] +[data: ] +[valid: ] +[num_iterations: 38] +[learning_rate: 0.05] +[num_leaves: 63] +[num_threads: 16] +[seed: 13] +[deterministic: 1] +[force_col_wise: 1] +[force_row_wise: 0] +[histogram_pool_size: -1] +[max_depth: -1] +[min_data_in_leaf: 20] +[min_sum_hessian_in_leaf: 0.001] +[bagging_fraction: 0.8] +[pos_bagging_fraction: 1] +[neg_bagging_fraction: 1] +[bagging_freq: 1] +[bagging_seed: 16376] +[bagging_by_query: 0] +[feature_fraction: 0.8] +[feature_fraction_bynode: 1] +[feature_fraction_seed: 20348] +[extra_trees: 0] +[extra_seed: 30076] +[early_stopping_round: 0] +[early_stopping_min_delta: 0] +[first_metric_only: 0] +[max_delta_step: 0] +[lambda_l1: 0] +[lambda_l2: 1] +[linear_lambda: 0] +[min_gain_to_split: 0] +[drop_rate: 0.1] +[max_drop: 50] +[skip_drop: 0.5] +[xgboost_dart_mode: 0] +[uniform_drop: 0] +[drop_seed: 24096] +[top_rate: 0.2] +[other_rate: 0.1] +[min_data_per_group: 100] +[max_cat_threshold: 32] +[cat_l2: 10] +[cat_smooth: 10] +[max_cat_to_onehot: 4] +[top_k: 20] +[monotone_constraints: ] +[monotone_constraints_method: basic] +[monotone_penalty: 0] +[feature_contri: ] +[forcedsplits_filename: ] +[refit_decay_rate: 0.9] +[cegb_tradeoff: 1] +[cegb_penalty_split: 0] +[cegb_penalty_feature_lazy: ] +[cegb_penalty_feature_coupled: ] +[path_smooth: 0] +[interaction_constraints: ] +[verbosity: -1] +[saved_feature_importance_type: 0] +[use_quantized_grad: 0] +[num_grad_quant_bins: 4] +[quant_train_renew_leaf: 0] +[stochastic_rounding: 1] +[linear_tree: 0] +[max_bin: 255] +[max_bin_by_feature: ] +[min_data_in_bin: 3] +[bin_construct_sample_cnt: 200000] +[data_random_seed: 81] +[is_enable_sparse: 1] +[enable_bundle: 1] +[use_missing: 1] +[zero_as_missing: 0] +[feature_pre_filter: 1] +[pre_partition: 0] +[two_round: 0] +[header: 0] +[label_column: ] +[weight_column: ] +[group_column: ] +[ignore_column: ] +[categorical_feature: 29,51,55,95,99] +[forcedbins_filename: ] +[precise_float_parser: 0] +[parser_config_file: ] +[objective_seed: 11872] +[num_class: 1] +[is_unbalance: 0] +[scale_pos_weight: 1] +[sigmoid: 1] +[boost_from_average: 1] +[reg_sqrt: 0] +[alpha: 0.9] +[fair_c: 1] +[poisson_max_delta_step: 0.7] +[tweedie_variance_power: 1.5] +[lambdarank_truncation_level: 20] +[lambdarank_norm: 1] +[label_gain: ] +[lambdarank_position_bias_regularization: 0] +[eval_at: 1] +[multi_error_top_k: 1] +[auc_mu_weights: ] +[num_machines: 1] +[local_listen_port: 12400] +[time_out: 120] +[machine_list_filename: ] +[machines: ] +[gpu_platform_id: -1] +[gpu_device_id: -1] +[gpu_device_id_list: ] +[gpu_use_dp: 0] +[num_gpu: 1] + +end of parameters + +pandas_categorical:[] diff --git a/ranker_ICD10CM_s2_d3llm7e4.json b/ranker_ICD10CM_s2_d3llm7e4.json new file mode 100644 index 0000000000000000000000000000000000000000..f8a7926968ac64dfdaa9e4b20af62a99bfbef0f1 --- /dev/null +++ b/ranker_ICD10CM_s2_d3llm7e4.json @@ -0,0 +1 @@ +{"cols": ["char_max", "word_max", "char_var", "sapbert_max", "sapbert_pref", "sapbert_var", "reading_ctx", "reading_ctx_gap", "ctx_dense", "gte_max", "gte_pref", "gte_var", "qwen3_max", "qwen3_pref", "qwen3_var", "num_match", "num_conflict", "cand_neg", "cand_hist", "neg_match", "hist_match", "fz_ratio", "fz_tset", "fz_partial", "fz_tsort", "tok_qcov", "tok_dcov", "tok_dextra", "ctx_overlap", "cand_lat", "lat_match", "lat_conflict", "lat_missing", "nn_cat_char_max", "nn_cat_char_sum", "nn_cat_dense_max", "nn_cat_dense_sum", "nn_cat_cnt", "nn_char_max", "nn_char_sum", "nn_dense_max", "nn_dense_sum", "nn_cnt", "nn_entctx_max", "nn_ctx_max", "prior", "exact", "mention", "n_desc", "billable", "code_len", "chapter", "block_prior", "is_unspec", "is_other", "enc7", "char_max_rank", "char_max_gap", "word_max_rank", "word_max_gap", "char_var_rank", "char_var_gap", "sapbert_max_rank", "sapbert_max_gap", "sapbert_var_rank", "sapbert_var_gap", "gte_max_rank", "gte_max_gap", "gte_var_rank", "gte_var_gap", "qwen3_max_rank", "qwen3_max_gap", "qwen3_var_rank", "qwen3_var_gap", "fz_tset_rank", "fz_tset_gap", "nn_cat_char_max_rank", "nn_cat_char_max_gap", "nn_cat_dense_max_rank", "nn_cat_dense_max_gap", "nn_char_max_rank", "nn_char_max_gap", "nn_dense_max_rank", "nn_dense_max_gap", "nn_entctx_max_rank", "nn_entctx_max_gap", "nn_ctx_max_rank", "nn_ctx_max_gap", "prior_rank", "prior_gap", "q_len", "q_ntok", "q_digit", "q_abbr", "q_nvar", "q_lat", "q_neg", "q_hist", "q_fam", "subconcept", "n_cand", "s1", "s1_rank", "s1_p", "s1_gap", "xs_cooc", "xs_cooc_top1", "xs_sim", "xs_sim_top1", "llm_lp", "llm_lp_rank", "llm_lp_gap", "ce", "ce_lp", "ce_rank", "ce_gap", "ce_lp_rank", "ce_lp_gap"]} \ No newline at end of file diff --git a/ranker_ICD10CM_s2_d3llm7e4.txt b/ranker_ICD10CM_s2_d3llm7e4.txt new file mode 100644 index 0000000000000000000000000000000000000000..55b8bc43298a4748668aaf0f4ed72be2ba8adcab --- /dev/null +++ b/ranker_ICD10CM_s2_d3llm7e4.txt @@ -0,0 +1,1786 @@ +tree +version=v4 +num_class=1 +num_tree_per_iteration=1 +label_index=0 +max_feature_idx=117 +objective=lambdarank +feature_names=char_max word_max char_var sapbert_max sapbert_pref sapbert_var reading_ctx reading_ctx_gap ctx_dense gte_max gte_pref gte_var qwen3_max qwen3_pref qwen3_var num_match num_conflict cand_neg cand_hist neg_match hist_match fz_ratio fz_tset fz_partial fz_tsort tok_qcov tok_dcov tok_dextra ctx_overlap cand_lat lat_match lat_conflict lat_missing nn_cat_char_max nn_cat_char_sum nn_cat_dense_max nn_cat_dense_sum nn_cat_cnt nn_char_max nn_char_sum nn_dense_max nn_dense_sum nn_cnt nn_entctx_max nn_ctx_max prior exact mention n_desc billable code_len chapter block_prior is_unspec is_other enc7 char_max_rank char_max_gap word_max_rank word_max_gap char_var_rank char_var_gap sapbert_max_rank sapbert_max_gap sapbert_var_rank sapbert_var_gap gte_max_rank gte_max_gap gte_var_rank gte_var_gap qwen3_max_rank qwen3_max_gap qwen3_var_rank qwen3_var_gap fz_tset_rank fz_tset_gap nn_cat_char_max_rank nn_cat_char_max_gap nn_cat_dense_max_rank nn_cat_dense_max_gap nn_char_max_rank nn_char_max_gap nn_dense_max_rank nn_dense_max_gap nn_entctx_max_rank nn_entctx_max_gap nn_ctx_max_rank nn_ctx_max_gap prior_rank prior_gap q_len q_ntok q_digit q_abbr q_nvar q_lat q_neg q_hist q_fam subconcept n_cand s1 s1_rank s1_p s1_gap xs_cooc xs_cooc_top1 xs_sim xs_sim_top1 llm_lp llm_lp_rank llm_lp_gap ce ce_lp ce_rank ce_gap ce_lp_rank 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+ce_lp=154 +ce=144 +ctx_dense=103 +s1_gap=97 +xs_cooc=96 +llm_lp_gap=95 +ce_rank=74 +qwen3_var_gap=73 +xs_sim_top1=72 +ce_gap=71 +reading_ctx=70 +xs_sim=70 +fz_tset_gap=65 +sapbert_var_gap=64 +char_var_gap=63 +sapbert_max_gap=63 +fz_tset_rank=63 +reading_ctx_gap=62 +gte_var_gap=62 +s1=61 +sapbert_var=60 +gte_pref=60 +nn_char_max_gap=59 +prior_gap=59 +gte_var=58 +qwen3_var=58 +fz_ratio=58 +qwen3_var_rank=56 +qwen3_max=55 +gte_max_gap=55 +word_max_gap=54 +fz_partial=53 +qwen3_max_gap=53 +nn_dense_max_gap=53 +sapbert_max=51 +qwen3_pref=51 +nn_cat_dense_max_rank=51 +char_max=50 +llm_lp_rank=50 +fz_tsort=49 +nn_cat_dense_sum=49 +gte_max_rank=48 +nn_cat_char_max_gap=48 +nn_ctx_max_gap=48 +nn_cat_char_max_rank=46 +char_var=45 +word_max_rank=44 +prior_rank=44 +nn_cat_dense_max=43 +nn_dense_sum=43 +tok_dextra=42 +prior=42 +gte_max=41 +nn_cat_char_sum=41 +char_var_rank=41 +gte_var_rank=40 +nn_dense_max=39 +nn_entctx_max_gap=39 +sapbert_pref=38 +char_max_rank=38 +n_cand=38 +nn_ctx_max=37 +char_max_gap=37 +sapbert_var_rank=36 +ce_lp_gap=36 +q_len=35 +nn_entctx_max=33 +chapter=33 +fz_tset=32 +nn_char_sum=32 +nn_char_max_rank=32 +billable=31 +nn_cat_dense_max_gap=31 +sapbert_max_rank=30 +qwen3_max_rank=30 +nn_char_max=29 +block_prior=29 +nn_cat_char_max=27 +word_max=25 +nn_dense_max_rank=25 +n_desc=23 +nn_entctx_max_rank=22 +nn_ctx_max_rank=21 +tok_dcov=20 +q_nvar=18 +s1_rank=16 +is_other=15 +xs_cooc_top1=15 +ce_lp_rank=12 +code_len=10 +nn_cat_cnt=9 +nn_cnt=9 +tok_qcov=7 +q_ntok=7 +is_unspec=6 +ctx_overlap=5 +cand_neg=4 +neg_match=3 +lat_missing=2 +exact=1 +q_digit=1 + +parameters: +[boosting: gbdt] +[objective: lambdarank] +[metric: map] +[tree_learner: serial] +[device_type: cpu] +[data_sample_strategy: bagging] +[data: ] +[valid: ] +[num_iterations: 78] +[learning_rate: 0.05] +[num_leaves: 63] +[num_threads: 16] +[seed: 13] +[deterministic: 1] +[force_col_wise: 1] +[force_row_wise: 0] +[histogram_pool_size: -1] +[max_depth: -1] +[min_data_in_leaf: 20] +[min_sum_hessian_in_leaf: 0.001] +[bagging_fraction: 0.8] +[pos_bagging_fraction: 1] +[neg_bagging_fraction: 1] +[bagging_freq: 1] +[bagging_seed: 16376] +[bagging_by_query: 0] +[feature_fraction: 0.8] +[feature_fraction_bynode: 1] +[feature_fraction_seed: 20348] +[extra_trees: 0] +[extra_seed: 30076] +[early_stopping_round: 0] +[early_stopping_min_delta: 0] +[first_metric_only: 0] +[max_delta_step: 0] +[lambda_l1: 0] +[lambda_l2: 1] +[linear_lambda: 0] +[min_gain_to_split: 0] +[drop_rate: 0.1] +[max_drop: 50] +[skip_drop: 0.5] +[xgboost_dart_mode: 0] +[uniform_drop: 0] +[drop_seed: 24096] +[top_rate: 0.2] +[other_rate: 0.1] +[min_data_per_group: 100] +[max_cat_threshold: 32] +[cat_l2: 10] +[cat_smooth: 10] +[max_cat_to_onehot: 4] +[top_k: 20] +[monotone_constraints: ] +[monotone_constraints_method: basic] +[monotone_penalty: 0] +[feature_contri: ] +[forcedsplits_filename: ] +[refit_decay_rate: 0.9] +[cegb_tradeoff: 1] +[cegb_penalty_split: 0] +[cegb_penalty_feature_lazy: ] +[cegb_penalty_feature_coupled: ] +[path_smooth: 0] +[interaction_constraints: ] +[verbosity: -1] +[saved_feature_importance_type: 0] +[use_quantized_grad: 0] +[num_grad_quant_bins: 4] +[quant_train_renew_leaf: 0] +[stochastic_rounding: 1] +[linear_tree: 0] +[max_bin: 255] +[max_bin_by_feature: ] +[min_data_in_bin: 3] +[bin_construct_sample_cnt: 200000] +[data_random_seed: 81] +[is_enable_sparse: 1] +[enable_bundle: 1] +[use_missing: 1] +[zero_as_missing: 0] +[feature_pre_filter: 1] +[pre_partition: 0] +[two_round: 0] +[header: 0] +[label_column: ] +[weight_column: ] +[group_column: ] +[ignore_column: ] +[categorical_feature: 29,51,55,95,99] +[forcedbins_filename: ] +[precise_float_parser: 0] +[parser_config_file: ] +[objective_seed: 11872] +[num_class: 1] +[is_unbalance: 0] +[scale_pos_weight: 1] +[sigmoid: 1] +[boost_from_average: 1] +[reg_sqrt: 0] +[alpha: 0.9] +[fair_c: 1] +[poisson_max_delta_step: 0.7] +[tweedie_variance_power: 1.5] +[lambdarank_truncation_level: 20] +[lambdarank_norm: 1] +[label_gain: ] +[lambdarank_position_bias_regularization: 0] +[eval_at: 1] +[multi_error_top_k: 1] +[auc_mu_weights: ] +[num_machines: 1] +[local_listen_port: 12400] +[time_out: 120] +[machine_list_filename: ] +[machines: ] +[gpu_platform_id: -1] +[gpu_device_id: -1] +[gpu_device_id_list: ] +[gpu_use_dp: 0] +[num_gpu: 1] + +end of parameters + +pandas_categorical:[] diff --git a/ranker_ICD10CM_s2_sap4.json b/ranker_ICD10CM_s2_sap4.json new file mode 100644 index 0000000000000000000000000000000000000000..0162ed5afc2cdad6bbcba427dfdf2012633a6be9 --- /dev/null +++ b/ranker_ICD10CM_s2_sap4.json @@ -0,0 +1 @@ +{"cols": ["char_max", "word_max", "char_var", "sapbert_max", "sapbert_pref", "sapbert_var", "reading_ctx", "reading_ctx_gap", "ctx_dense", "num_match", "num_conflict", "cand_neg", "cand_hist", "neg_match", "hist_match", "fz_ratio", "fz_tset", "fz_partial", "fz_tsort", "tok_qcov", "tok_dcov", "tok_dextra", "ctx_overlap", "cand_lat", "lat_match", "lat_conflict", "lat_missing", "nn_cat_char_max", "nn_cat_char_sum", "nn_cat_dense_max", "nn_cat_dense_sum", "nn_cat_cnt", "nn_char_max", "nn_char_sum", "nn_dense_max", "nn_dense_sum", "nn_cnt", "nn_entctx_max", "nn_ctx_max", "prior", "exact", "mention", "n_desc", "billable", "code_len", "chapter", "block_prior", "is_unspec", "is_other", "enc7", "char_max_rank", "char_max_gap", "word_max_rank", "word_max_gap", "char_var_rank", "char_var_gap", "sapbert_max_rank", "sapbert_max_gap", "sapbert_var_rank", "sapbert_var_gap", "fz_tset_rank", "fz_tset_gap", "nn_cat_char_max_rank", "nn_cat_char_max_gap", "nn_cat_dense_max_rank", "nn_cat_dense_max_gap", "nn_char_max_rank", "nn_char_max_gap", "nn_dense_max_rank", "nn_dense_max_gap", "nn_entctx_max_rank", "nn_entctx_max_gap", "nn_ctx_max_rank", "nn_ctx_max_gap", "prior_rank", "prior_gap", "q_len", "q_ntok", "q_digit", "q_abbr", "q_nvar", "q_lat", "q_neg", "q_hist", "q_fam", "subconcept", "n_cand", "s1", "s1_rank", "s1_p", "s1_gap", "xs_cooc", "xs_cooc_top1", "xs_sim", "xs_sim_top1"]} \ No newline at end of file diff --git a/ranker_ICD10CM_s2_sap4.txt b/ranker_ICD10CM_s2_sap4.txt new file mode 100644 index 0000000000000000000000000000000000000000..728de2fb5a33714ea8b63380c04e191109deaa4d --- /dev/null +++ b/ranker_ICD10CM_s2_sap4.txt @@ -0,0 +1,1288 @@ +tree +version=v4 +num_class=1 +num_tree_per_iteration=1 +label_index=0 +max_feature_idx=94 +objective=lambdarank +feature_names=char_max word_max char_var sapbert_max sapbert_pref sapbert_var reading_ctx reading_ctx_gap ctx_dense num_match num_conflict cand_neg cand_hist neg_match hist_match fz_ratio fz_tset fz_partial fz_tsort tok_qcov tok_dcov tok_dextra ctx_overlap cand_lat lat_match lat_conflict lat_missing nn_cat_char_max nn_cat_char_sum nn_cat_dense_max nn_cat_dense_sum nn_cat_cnt nn_char_max nn_char_sum nn_dense_max nn_dense_sum nn_cnt nn_entctx_max nn_ctx_max prior exact mention n_desc billable code_len chapter block_prior is_unspec is_other enc7 char_max_rank char_max_gap word_max_rank word_max_gap char_var_rank char_var_gap sapbert_max_rank sapbert_max_gap sapbert_var_rank sapbert_var_gap fz_tset_rank fz_tset_gap nn_cat_char_max_rank nn_cat_char_max_gap nn_cat_dense_max_rank nn_cat_dense_max_gap nn_char_max_rank nn_char_max_gap nn_dense_max_rank nn_dense_max_gap nn_entctx_max_rank nn_entctx_max_gap nn_ctx_max_rank nn_ctx_max_gap prior_rank prior_gap q_len q_ntok q_digit q_abbr q_nvar q_lat q_neg q_hist q_fam subconcept n_cand s1 s1_rank s1_p s1_gap xs_cooc xs_cooc_top1 xs_sim xs_sim_top1 +feature_infos=[0:1.0000002384185791] [0:1.0000001192092896] [0:1.0000002384185791] [-0.18305797874927521:1.0000722408294678] [-0.18305797874927521:1.000062108039856] [-0.18638628721237183:1.0000724792480469] [-0.16073939204216003:0.82179844379425049] [0:0.4084649384021759] [-0.12636484205722809:0.9380265474319458] [0:2] [0:1] [0:1] [0:1] [0:1] [0:1] [0:100] [0:100] [0:100] [0:100] [0:1] [0:1] [0:17] [0:5] -1:0:2:1:3 [0:1] [0:1] [0:1] [0:1.0000001192092896] [0:14.182402610778809] [0:1.0000008344650269] [0:10.127299308776855] [0:20] [0:1.0000001192092896] [0:10.082548141479492] [0:1.0000008344650269] [0:8.9456911087036133] [0:15] [0:0.98123562335968018] [0:1.0000001192092896] [0:3.2958368660043291] [0:1] none [1:22] [0:1] [3:7] -1:17:8:12:9:4:10:6:7:11:13:25:5:18:2:19:3:1:22:0:16:14:15:20:23:24 [0:3.9889840465642745] [0:1] [0:1] -1:0:1:2 [1:227] [0:1.0000001192092896] [1:204] [0:1.0000001192092896] [1:333] [0:1.0000002384185791] [1:296] [0:1.1384812593460083] [1:300] [0:1.1718997955322266] [1:302] [0:100] [1:133] [0:1.0000001192092896] [1:111] [0:1.0000008344650269] [1:21] [0:1.0000001192092896] [1:21] [0:1.0000008344650269] [1:21] [0:0.98123562335968018] [1:21] [0:1.0000001192092896] [1:60] [0:3.2958368660043291] [2:110] [1:15] [0:1] [0:1] [0:6] -1:0:1:2:3 [0:1] [0:1] [0:1] none [48:345] [-4.919539080797132:4.3864777820875398] [0:19] [0.00012037347373178901:0.99388349761654227] [0:9.0187760823935399] [0:0.99578850261102947] [0:1] 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3.74907 3.33766 3.28987 3.24741 3.21638 5.78811 3.10137 3.08417 3.00346 2.91309 2.59956 +threshold=0.069939928734242152 0.026087224719316703 0.21630476815233657 0.009943072214952357 0.053124432070898127 0.030504794640031196 1.3931573800188792 0.44433999622726023 0.29470152349845674 1.4787642947195083 0.15555207431316379 0.46458776295185095 20.500000000000004 3.5000000000000004 0.80088415741920482 0.018096625804901127 4.5000000000000009 2.1547098159790044 1.0000000180025095e-35 0.79535716772079479 1.5000000000000002 0.32179310917854315 0.50275853276252758 2.8947751844355394 8.3333333333333339 0.43532677543137238 2.5000000000000004 0.11804786324501039 0.34236443042755133 14.500000000000002 0.013160312548279764 0.52661287784576427 77.015755329008343 0.59589016437530529 0.030099793337285522 0.22518929094076159 0.077479928731918349 0.12146218866109849 0.33106449246406561 0.45599608123302465 0.40911426020392544 0.44886441528797155 117.50000000000001 0.20951197296380999 0.70779776573181163 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871 518 +cat_boundaries=0 1 +cat_threshold=4205953 +is_linear=0 +shrinkage=0.05 + + +end of trees + +feature_importances: +s1_p=192 +s1_gap=108 +s1=107 +xs_cooc=106 +xs_sim=84 +char_var_gap=82 +ctx_dense=79 +sapbert_max_gap=75 +nn_ctx_max_gap=73 +xs_sim_top1=73 +sapbert_var_gap=71 +char_max_gap=66 +reading_ctx=61 +char_var_rank=60 +sapbert_var=59 +reading_ctx_gap=57 +prior_gap=57 +sapbert_max_rank=56 +fz_ratio=55 +fz_partial=55 +fz_tset_gap=55 +sapbert_max=53 +sapbert_pref=53 +nn_entctx_max_gap=52 +char_var=51 +word_max_gap=49 +nn_cat_dense_max=46 +n_cand=46 +s1_rank=45 +nn_char_max_gap=42 +word_max_rank=41 +prior_rank=41 +nn_dense_sum=40 +fz_tset_rank=40 +nn_char_sum=39 +block_prior=38 +nn_dense_max_gap=38 +fz_tsort=37 +sapbert_var_rank=37 +q_len=37 +nn_cat_dense_max_rank=36 +nn_dense_max=35 +nn_entctx_max=35 +nn_ctx_max=35 +nn_char_max=34 +char_max_rank=34 +nn_cat_char_max_gap=34 +nn_cat_dense_sum=33 +nn_cat_char_sum=32 +chapter=32 +nn_char_max_rank=31 +tok_dextra=30 +nn_cat_char_max_rank=30 +prior=29 +nn_cat_dense_max_gap=29 +char_max=26 +nn_cat_char_max=24 +is_other=24 +fz_tset=23 +word_max=22 +nn_dense_max_rank=22 +nn_ctx_max_rank=22 +n_desc=20 +nn_entctx_max_rank=18 +tok_dcov=14 +nn_cat_cnt=13 +is_unspec=13 +billable=12 +cand_neg=11 +ctx_overlap=11 +q_ntok=11 +xs_cooc_top1=11 +enc7=9 +q_nvar=9 +nn_cnt=8 +code_len=8 +tok_qcov=7 +neg_match=1 +lat_match=1 +q_neg=1 + +parameters: +[boosting: gbdt] +[objective: lambdarank] +[metric: map] +[tree_learner: serial] +[device_type: cpu] +[data_sample_strategy: bagging] +[data: ] +[valid: ] +[num_iterations: 53] +[learning_rate: 0.05] +[num_leaves: 63] +[num_threads: 16] +[seed: 13] +[deterministic: 1] +[force_col_wise: 1] +[force_row_wise: 0] +[histogram_pool_size: -1] +[max_depth: -1] +[min_data_in_leaf: 20] +[min_sum_hessian_in_leaf: 0.001] +[bagging_fraction: 0.8] +[pos_bagging_fraction: 1] +[neg_bagging_fraction: 1] +[bagging_freq: 1] +[bagging_seed: 16376] +[bagging_by_query: 0] +[feature_fraction: 0.8] +[feature_fraction_bynode: 1] +[feature_fraction_seed: 20348] +[extra_trees: 0] +[extra_seed: 30076] +[early_stopping_round: 0] +[early_stopping_min_delta: 0] +[first_metric_only: 0] +[max_delta_step: 0] +[lambda_l1: 0] +[lambda_l2: 1] +[linear_lambda: 0] +[min_gain_to_split: 0] +[drop_rate: 0.1] +[max_drop: 50] +[skip_drop: 0.5] +[xgboost_dart_mode: 0] +[uniform_drop: 0] +[drop_seed: 24096] +[top_rate: 0.2] +[other_rate: 0.1] +[min_data_per_group: 100] +[max_cat_threshold: 32] +[cat_l2: 10] +[cat_smooth: 10] +[max_cat_to_onehot: 4] +[top_k: 20] +[monotone_constraints: ] +[monotone_constraints_method: basic] +[monotone_penalty: 0] +[feature_contri: ] +[forcedsplits_filename: ] +[refit_decay_rate: 0.9] +[cegb_tradeoff: 1] +[cegb_penalty_split: 0] +[cegb_penalty_feature_lazy: ] +[cegb_penalty_feature_coupled: ] +[path_smooth: 0] +[interaction_constraints: ] +[verbosity: -1] +[saved_feature_importance_type: 0] +[use_quantized_grad: 0] +[num_grad_quant_bins: 4] +[quant_train_renew_leaf: 0] +[stochastic_rounding: 1] +[linear_tree: 0] +[max_bin: 255] +[max_bin_by_feature: ] +[min_data_in_bin: 3] +[bin_construct_sample_cnt: 200000] +[data_random_seed: 81] +[is_enable_sparse: 1] +[enable_bundle: 1] +[use_missing: 1] +[zero_as_missing: 0] +[feature_pre_filter: 1] +[pre_partition: 0] +[two_round: 0] +[header: 0] +[label_column: ] +[weight_column: ] +[group_column: ] +[ignore_column: ] +[categorical_feature: 23,45,49,81,85] +[forcedbins_filename: ] +[precise_float_parser: 0] +[parser_config_file: ] +[objective_seed: 11872] +[num_class: 1] +[is_unbalance: 0] +[scale_pos_weight: 1] +[sigmoid: 1] +[boost_from_average: 1] +[reg_sqrt: 0] +[alpha: 0.9] +[fair_c: 1] +[poisson_max_delta_step: 0.7] +[tweedie_variance_power: 1.5] +[lambdarank_truncation_level: 20] +[lambdarank_norm: 1] +[label_gain: ] +[lambdarank_position_bias_regularization: 0] +[eval_at: 1] +[multi_error_top_k: 1] +[auc_mu_weights: ] +[num_machines: 1] +[local_listen_port: 12400] +[time_out: 120] +[machine_list_filename: ] +[machines: ] +[gpu_platform_id: -1] +[gpu_device_id: -1] +[gpu_device_id_list: ] +[gpu_use_dp: 0] +[num_gpu: 1] + +end of parameters + +pandas_categorical:[] diff --git a/ranker_SNOMEDCT_US_s1_d3ce4.json b/ranker_SNOMEDCT_US_s1_d3ce4.json new file mode 100644 index 0000000000000000000000000000000000000000..ac170f53071c62c2e73e34e4e26077956f41a40c --- /dev/null +++ b/ranker_SNOMEDCT_US_s1_d3ce4.json @@ -0,0 +1 @@ +{"cols": ["char_max", "word_max", "char_var", "sapbert_max", "sapbert_pref", "sapbert_var", "reading_ctx", "reading_ctx_gap", "ctx_dense", "gte_max", "gte_pref", "gte_var", "qwen3_max", "qwen3_pref", "qwen3_var", "num_match", "num_conflict", "cand_neg", "cand_hist", "neg_match", "hist_match", "fz_ratio", "fz_tset", "fz_partial", "fz_tsort", "tok_qcov", "tok_dcov", "tok_dextra", "ctx_overlap", "cand_lat", "lat_match", "lat_conflict", "lat_missing", "nn_char_max", "nn_char_sum", "nn_dense_max", "nn_dense_sum", "nn_cnt", "nn_entctx_max", "nn_ctx_max", "prior", "exact", "mention", "n_desc", "semtag", "best_order", "best_is_pref", "char_max_rank", "char_max_gap", "word_max_rank", "word_max_gap", "char_var_rank", "char_var_gap", "sapbert_max_rank", "sapbert_max_gap", "sapbert_var_rank", "sapbert_var_gap", "gte_max_rank", "gte_max_gap", "gte_var_rank", "gte_var_gap", "qwen3_max_rank", "qwen3_max_gap", "qwen3_var_rank", "qwen3_var_gap", "fz_tset_rank", "fz_tset_gap", "nn_char_max_rank", "nn_char_max_gap", "nn_dense_max_rank", "nn_dense_max_gap", "nn_entctx_max_rank", "nn_entctx_max_gap", "nn_ctx_max_rank", "nn_ctx_max_gap", "prior_rank", "prior_gap", "q_len", "q_ntok", "q_digit", "q_abbr", "q_nvar", "q_lat", "q_neg", "q_hist", "q_fam", "subconcept", "n_cand"]} \ No newline at end of file diff --git a/ranker_SNOMEDCT_US_s1_d3ce4.txt b/ranker_SNOMEDCT_US_s1_d3ce4.txt new file mode 100644 index 0000000000000000000000000000000000000000..def03e3762fb5ea520e076e392361507507e1a52 --- /dev/null +++ b/ranker_SNOMEDCT_US_s1_d3ce4.txt @@ -0,0 +1,3718 @@ +tree +version=v4 +num_class=1 +num_tree_per_iteration=1 +label_index=0 +max_feature_idx=87 +objective=lambdarank +feature_names=char_max word_max char_var sapbert_max sapbert_pref sapbert_var reading_ctx reading_ctx_gap ctx_dense gte_max gte_pref gte_var qwen3_max qwen3_pref qwen3_var num_match num_conflict cand_neg cand_hist neg_match hist_match fz_ratio fz_tset fz_partial fz_tsort tok_qcov tok_dcov tok_dextra ctx_overlap cand_lat lat_match lat_conflict lat_missing nn_char_max nn_char_sum nn_dense_max nn_dense_sum nn_cnt nn_entctx_max nn_ctx_max prior exact mention n_desc semtag best_order best_is_pref char_max_rank char_max_gap word_max_rank word_max_gap char_var_rank char_var_gap sapbert_max_rank sapbert_max_gap sapbert_var_rank sapbert_var_gap gte_max_rank gte_max_gap gte_var_rank gte_var_gap qwen3_max_rank qwen3_max_gap qwen3_var_rank qwen3_var_gap fz_tset_rank fz_tset_gap nn_char_max_rank nn_char_max_gap nn_dense_max_rank 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9830 429844 700 45300 40647 798 18625 3508 68283 3149 2441 1463 1087 376 1022 252 +cat_boundaries=0 1 2 +cat_threshold=15038 875792 +is_linear=0 +shrinkage=0.05 + + +end of trees + +feature_importances: +semtag=469 +ctx_dense=382 +sapbert_max_gap=363 +qwen3_max_gap=303 +nn_dense_max_gap=291 +n_cand=283 +gte_max_rank=259 +nn_char_max_gap=238 +qwen3_max_rank=231 +prior=225 +char_var_gap=223 +gte_max_gap=222 +word_max_rank=209 +ctx_overlap=193 +gte_var_gap=183 +char_var_rank=182 +q_len=182 +sapbert_pref=181 +word_max_gap=177 +char_max_gap=175 +char_max_rank=172 +reading_ctx=168 +nn_entctx_max_gap=167 +qwen3_pref=165 +qwen3_var=165 +gte_var=162 +sapbert_var_gap=160 +qwen3_var_rank=159 +prior_rank=159 +fz_partial=158 +prior_gap=158 +sapbert_max_rank=154 +fz_ratio=153 +sapbert_var=150 +sapbert_max=147 +gte_pref=144 +char_var=139 +fz_tsort=136 +nn_dense_sum=135 +char_max=134 +nn_char_sum=134 +qwen3_max=128 +gte_max=123 +sapbert_var_rank=122 +qwen3_var_gap=122 +gte_var_rank=119 +nn_ctx_max_gap=116 +nn_char_max_rank=112 +fz_tset_rank=109 +fz_tset=106 +word_max=105 +nn_ctx_max=95 +nn_dense_max=91 +fz_tset_gap=89 +nn_char_max=87 +nn_entctx_max=78 +nn_entctx_max_rank=75 +nn_dense_max_rank=69 +reading_ctx_gap=59 +tok_dcov=55 +tok_dextra=53 +subconcept=53 +q_ntok=50 +n_desc=48 +nn_ctx_max_rank=48 +tok_qcov=37 +cand_neg=31 +best_order=26 +nn_cnt=21 +exact=13 +neg_match=7 +q_neg=6 +q_nvar=5 +num_conflict=4 +lat_conflict=4 +lat_missing=4 +q_digit=4 +num_match=3 +cand_hist=2 +hist_match=2 +lat_match=2 +q_abbr=2 +q_lat=2 +best_is_pref=1 + +parameters: +[boosting: gbdt] +[objective: lambdarank] +[metric: map] +[tree_learner: serial] +[device_type: cpu] +[data_sample_strategy: bagging] +[data: ] +[valid: ] +[num_iterations: 169] +[learning_rate: 0.05] +[num_leaves: 63] +[num_threads: 16] +[seed: 13] +[deterministic: 1] +[force_col_wise: 1] +[force_row_wise: 0] +[histogram_pool_size: -1] +[max_depth: -1] +[min_data_in_leaf: 20] +[min_sum_hessian_in_leaf: 0.001] +[bagging_fraction: 0.8] +[pos_bagging_fraction: 1] +[neg_bagging_fraction: 1] +[bagging_freq: 1] +[bagging_seed: 16376] +[bagging_by_query: 0] +[feature_fraction: 0.8] +[feature_fraction_bynode: 1] +[feature_fraction_seed: 20348] +[extra_trees: 0] +[extra_seed: 30076] +[early_stopping_round: 0] +[early_stopping_min_delta: 0] +[first_metric_only: 0] +[max_delta_step: 0] +[lambda_l1: 0] +[lambda_l2: 1] +[linear_lambda: 0] +[min_gain_to_split: 0] +[drop_rate: 0.1] +[max_drop: 50] +[skip_drop: 0.5] +[xgboost_dart_mode: 0] +[uniform_drop: 0] +[drop_seed: 24096] +[top_rate: 0.2] +[other_rate: 0.1] +[min_data_per_group: 100] +[max_cat_threshold: 32] +[cat_l2: 10] +[cat_smooth: 10] +[max_cat_to_onehot: 4] +[top_k: 20] +[monotone_constraints: ] +[monotone_constraints_method: basic] +[monotone_penalty: 0] +[feature_contri: ] +[forcedsplits_filename: ] +[refit_decay_rate: 0.9] +[cegb_tradeoff: 1] +[cegb_penalty_split: 0] +[cegb_penalty_feature_lazy: ] +[cegb_penalty_feature_coupled: ] +[path_smooth: 0] +[interaction_constraints: ] +[verbosity: -1] +[saved_feature_importance_type: 0] +[use_quantized_grad: 0] +[num_grad_quant_bins: 4] +[quant_train_renew_leaf: 0] +[stochastic_rounding: 1] +[linear_tree: 0] +[max_bin: 255] +[max_bin_by_feature: ] +[min_data_in_bin: 3] +[bin_construct_sample_cnt: 200000] +[data_random_seed: 81] +[is_enable_sparse: 1] +[enable_bundle: 1] +[use_missing: 1] +[zero_as_missing: 0] +[feature_pre_filter: 1] +[pre_partition: 0] +[two_round: 0] +[header: 0] +[label_column: ] +[weight_column: ] +[group_column: ] +[ignore_column: ] +[categorical_feature: 29,44,82,86] +[forcedbins_filename: ] +[precise_float_parser: 0] +[parser_config_file: ] +[objective_seed: 11872] +[num_class: 1] +[is_unbalance: 0] +[scale_pos_weight: 1] +[sigmoid: 1] +[boost_from_average: 1] +[reg_sqrt: 0] +[alpha: 0.9] +[fair_c: 1] +[poisson_max_delta_step: 0.7] +[tweedie_variance_power: 1.5] +[lambdarank_truncation_level: 20] +[lambdarank_norm: 1] +[label_gain: ] +[lambdarank_position_bias_regularization: 0] +[eval_at: 1] +[multi_error_top_k: 1] +[auc_mu_weights: ] +[num_machines: 1] +[local_listen_port: 12400] +[time_out: 120] +[machine_list_filename: ] +[machines: ] +[gpu_platform_id: -1] +[gpu_device_id: -1] +[gpu_device_id_list: ] +[gpu_use_dp: 0] +[num_gpu: 1] + +end of parameters + +pandas_categorical:[] diff --git a/ranker_SNOMEDCT_US_s1_d3llm14e4.json b/ranker_SNOMEDCT_US_s1_d3llm14e4.json new file mode 100644 index 0000000000000000000000000000000000000000..ac170f53071c62c2e73e34e4e26077956f41a40c --- /dev/null +++ b/ranker_SNOMEDCT_US_s1_d3llm14e4.json @@ -0,0 +1 @@ +{"cols": ["char_max", "word_max", "char_var", "sapbert_max", "sapbert_pref", "sapbert_var", "reading_ctx", "reading_ctx_gap", "ctx_dense", "gte_max", "gte_pref", "gte_var", "qwen3_max", "qwen3_pref", "qwen3_var", "num_match", "num_conflict", "cand_neg", "cand_hist", "neg_match", "hist_match", "fz_ratio", "fz_tset", "fz_partial", "fz_tsort", "tok_qcov", "tok_dcov", "tok_dextra", "ctx_overlap", "cand_lat", "lat_match", "lat_conflict", "lat_missing", "nn_char_max", "nn_char_sum", "nn_dense_max", "nn_dense_sum", "nn_cnt", "nn_entctx_max", "nn_ctx_max", "prior", "exact", "mention", "n_desc", "semtag", "best_order", "best_is_pref", "char_max_rank", "char_max_gap", "word_max_rank", "word_max_gap", "char_var_rank", "char_var_gap", "sapbert_max_rank", "sapbert_max_gap", "sapbert_var_rank", "sapbert_var_gap", "gte_max_rank", "gte_max_gap", "gte_var_rank", "gte_var_gap", "qwen3_max_rank", "qwen3_max_gap", "qwen3_var_rank", "qwen3_var_gap", "fz_tset_rank", "fz_tset_gap", "nn_char_max_rank", "nn_char_max_gap", "nn_dense_max_rank", "nn_dense_max_gap", "nn_entctx_max_rank", "nn_entctx_max_gap", "nn_ctx_max_rank", "nn_ctx_max_gap", "prior_rank", "prior_gap", "q_len", "q_ntok", "q_digit", "q_abbr", "q_nvar", "q_lat", "q_neg", "q_hist", "q_fam", "subconcept", "n_cand"]} \ No newline at end of file diff --git a/ranker_SNOMEDCT_US_s1_d3llm14e4.txt b/ranker_SNOMEDCT_US_s1_d3llm14e4.txt new file mode 100644 index 0000000000000000000000000000000000000000..def03e3762fb5ea520e076e392361507507e1a52 --- /dev/null +++ b/ranker_SNOMEDCT_US_s1_d3llm14e4.txt @@ -0,0 +1,3718 @@ +tree +version=v4 +num_class=1 +num_tree_per_iteration=1 +label_index=0 +max_feature_idx=87 +objective=lambdarank +feature_names=char_max word_max char_var sapbert_max sapbert_pref sapbert_var reading_ctx reading_ctx_gap ctx_dense gte_max gte_pref gte_var qwen3_max qwen3_pref qwen3_var num_match num_conflict cand_neg cand_hist neg_match hist_match fz_ratio fz_tset fz_partial fz_tsort tok_qcov tok_dcov tok_dextra ctx_overlap cand_lat lat_match lat_conflict lat_missing nn_char_max nn_char_sum nn_dense_max nn_dense_sum nn_cnt nn_entctx_max nn_ctx_max prior exact mention n_desc semtag best_order best_is_pref char_max_rank char_max_gap word_max_rank word_max_gap char_var_rank char_var_gap sapbert_max_rank sapbert_max_gap sapbert_var_rank sapbert_var_gap gte_max_rank gte_max_gap gte_var_rank gte_var_gap qwen3_max_rank qwen3_max_gap qwen3_var_rank qwen3_var_gap fz_tset_rank fz_tset_gap nn_char_max_rank nn_char_max_gap nn_dense_max_rank nn_dense_max_gap nn_entctx_max_rank nn_entctx_max_gap nn_ctx_max_rank nn_ctx_max_gap prior_rank prior_gap q_len q_ntok q_digit q_abbr q_nvar q_lat q_neg q_hist q_fam subconcept n_cand +feature_infos=[0:1.0000001192092896] [0:1.0000001192092896] [0:1.0000001192092896] [-0.22487562894821167:1.0000755786895752] [-0.22487562894821167:1.0000648498535156] [-0.20326696336269379:1.0000648498535156] [-0.16142846643924713:0.75836026668548584] [0:0.4073173999786377] [-0.19607745110988617:0.99998879432678223] [0.64043503999710083:1.0001192092895508] [0.63986283540725708:1.0001192092895508] [0.65842556953430176:1.0001227855682373] [0.12051869928836823:0.81241023540496826] [0.11195492744445801:0.81241023540496826] [0.10765054821968079:0.84735214710235596] [0:3] [0:1] [0:1] [0:1] [0:1] [0:1] [0:100] [0:100] [0:100] [0:100] [0:1] 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332.718 280.248 191.568 165.591 146.586 141.868 100.171 91.1147 87.9254 85.9228 82.8593 78.2521 77.3142 77.2525 60.9627 55.2781 54.6596 51.0994 48.6331 47.8387 44.9203 43.3297 42.3859 41.7945 44.0358 39.9317 39.1588 38.8553 38.7932 38.3869 37.87 41.0362 40.6255 38.2071 37.215 36.2912 35.4457 34.5865 33.9539 33.4988 32.0938 31.2326 30.589 29.8268 29.8119 29.2624 29.0626 28.8368 27.3209 26.8804 26.7334 26.711 28.1655 26.2601 +threshold=0.1358563303947449 4.5000000000000009 16.500000000000004 7.5000000000000009 0.49099218845367437 0.28666624426841741 1.0000000180025095e-35 0.21896290779113772 0.022451430559158329 0.70470771193504345 33.500000000000007 0.26781517267227178 0.73767948150634777 6.5000000000000009 0.26236963272094732 0.044677257537841804 0.077522903680801405 0.45061561465263372 0.086464256048202529 0.94866982102394115 0.78765133023262035 3.5000000000000004 16.500000000000004 5.5000000000000009 1.0000000180025095e-35 0.24757498502731326 0.69235050678253185 0 13.500000000000002 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7.3884733014847352 2.9242853418281802 2.3163314672910928 2.8233150520754853 3.404637684117005 3.4511294346229411 1.9788362054247262 618.41221963343583 1.6282348205390915 118.45519404529909 2.7734793741246886 5.4303390114005197 13.047971990225106 1.893294297010925 4.2617108215117687 71.253480918224795 4.5024343586992499 11.816276148078034 15.39128582463127 4.4453501309762933 1.8634059555934062 5.766236855299212 +leaf_count=65134 290 21 1962 978 11609 24307 1078 24515 11623 984 2749 503 6799 1457 10141 18665 112 2885 6201 4979 20894 242 13136 42919 73 326 53648 105 1239 920 27616 4461 5421 85051 2354 34864 5746 12329 16909 801 818 2060 719 1744 2432 4653 3629 411219 197 39849 394 404 7016 1154 418 2731 65 240 770 136 176 76 +internal_value=0.000285859 0.00037061 0.000270186 0.000720311 0.00332029 0.000417086 0.0111701 0.0157047 0.0187562 0.021221 -0.00376789 0.00272287 0.0129421 -0.00135556 -0.0022327 0.0182384 -0.00332472 0.0199902 0.0213667 0.00683762 -0.00555222 -0.0177643 0.0183772 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186503 142107 117592 5190 473772 43928 79993 78536 105969 68395 87304 84419 35703 30724 942 42986 44396 43318 43245 259215 205567 1344 204223 203303 175687 171226 165805 141498 137990 103126 97380 29850 12941 4398 3597 1537 8543 48716 46284 9830 429844 700 45300 40647 798 18625 3508 68283 3149 2441 1463 1087 376 1022 252 +cat_boundaries=0 1 2 +cat_threshold=15038 875792 +is_linear=0 +shrinkage=0.05 + + +end of trees + +feature_importances: +semtag=469 +ctx_dense=382 +sapbert_max_gap=363 +qwen3_max_gap=303 +nn_dense_max_gap=291 +n_cand=283 +gte_max_rank=259 +nn_char_max_gap=238 +qwen3_max_rank=231 +prior=225 +char_var_gap=223 +gte_max_gap=222 +word_max_rank=209 +ctx_overlap=193 +gte_var_gap=183 +char_var_rank=182 +q_len=182 +sapbert_pref=181 +word_max_gap=177 +char_max_gap=175 +char_max_rank=172 +reading_ctx=168 +nn_entctx_max_gap=167 +qwen3_pref=165 +qwen3_var=165 +gte_var=162 +sapbert_var_gap=160 +qwen3_var_rank=159 +prior_rank=159 +fz_partial=158 +prior_gap=158 +sapbert_max_rank=154 +fz_ratio=153 +sapbert_var=150 +sapbert_max=147 +gte_pref=144 +char_var=139 +fz_tsort=136 +nn_dense_sum=135 +char_max=134 +nn_char_sum=134 +qwen3_max=128 +gte_max=123 +sapbert_var_rank=122 +qwen3_var_gap=122 +gte_var_rank=119 +nn_ctx_max_gap=116 +nn_char_max_rank=112 +fz_tset_rank=109 +fz_tset=106 +word_max=105 +nn_ctx_max=95 +nn_dense_max=91 +fz_tset_gap=89 +nn_char_max=87 +nn_entctx_max=78 +nn_entctx_max_rank=75 +nn_dense_max_rank=69 +reading_ctx_gap=59 +tok_dcov=55 +tok_dextra=53 +subconcept=53 +q_ntok=50 +n_desc=48 +nn_ctx_max_rank=48 +tok_qcov=37 +cand_neg=31 +best_order=26 +nn_cnt=21 +exact=13 +neg_match=7 +q_neg=6 +q_nvar=5 +num_conflict=4 +lat_conflict=4 +lat_missing=4 +q_digit=4 +num_match=3 +cand_hist=2 +hist_match=2 +lat_match=2 +q_abbr=2 +q_lat=2 +best_is_pref=1 + +parameters: +[boosting: gbdt] +[objective: lambdarank] +[metric: map] +[tree_learner: serial] +[device_type: cpu] +[data_sample_strategy: bagging] +[data: ] +[valid: ] +[num_iterations: 169] +[learning_rate: 0.05] +[num_leaves: 63] +[num_threads: 16] +[seed: 13] +[deterministic: 1] +[force_col_wise: 1] +[force_row_wise: 0] +[histogram_pool_size: -1] +[max_depth: -1] +[min_data_in_leaf: 20] +[min_sum_hessian_in_leaf: 0.001] +[bagging_fraction: 0.8] +[pos_bagging_fraction: 1] +[neg_bagging_fraction: 1] +[bagging_freq: 1] +[bagging_seed: 16376] +[bagging_by_query: 0] +[feature_fraction: 0.8] +[feature_fraction_bynode: 1] +[feature_fraction_seed: 20348] +[extra_trees: 0] +[extra_seed: 30076] +[early_stopping_round: 0] +[early_stopping_min_delta: 0] +[first_metric_only: 0] +[max_delta_step: 0] +[lambda_l1: 0] +[lambda_l2: 1] +[linear_lambda: 0] +[min_gain_to_split: 0] +[drop_rate: 0.1] +[max_drop: 50] +[skip_drop: 0.5] +[xgboost_dart_mode: 0] +[uniform_drop: 0] +[drop_seed: 24096] +[top_rate: 0.2] +[other_rate: 0.1] +[min_data_per_group: 100] +[max_cat_threshold: 32] +[cat_l2: 10] +[cat_smooth: 10] +[max_cat_to_onehot: 4] +[top_k: 20] +[monotone_constraints: ] +[monotone_constraints_method: basic] +[monotone_penalty: 0] +[feature_contri: ] +[forcedsplits_filename: ] +[refit_decay_rate: 0.9] +[cegb_tradeoff: 1] +[cegb_penalty_split: 0] +[cegb_penalty_feature_lazy: ] +[cegb_penalty_feature_coupled: ] +[path_smooth: 0] +[interaction_constraints: ] +[verbosity: -1] +[saved_feature_importance_type: 0] +[use_quantized_grad: 0] +[num_grad_quant_bins: 4] +[quant_train_renew_leaf: 0] +[stochastic_rounding: 1] +[linear_tree: 0] +[max_bin: 255] +[max_bin_by_feature: ] +[min_data_in_bin: 3] +[bin_construct_sample_cnt: 200000] +[data_random_seed: 81] +[is_enable_sparse: 1] +[enable_bundle: 1] +[use_missing: 1] +[zero_as_missing: 0] +[feature_pre_filter: 1] +[pre_partition: 0] +[two_round: 0] +[header: 0] +[label_column: ] +[weight_column: ] +[group_column: ] +[ignore_column: ] +[categorical_feature: 29,44,82,86] +[forcedbins_filename: ] +[precise_float_parser: 0] +[parser_config_file: ] +[objective_seed: 11872] +[num_class: 1] +[is_unbalance: 0] +[scale_pos_weight: 1] +[sigmoid: 1] +[boost_from_average: 1] +[reg_sqrt: 0] +[alpha: 0.9] +[fair_c: 1] +[poisson_max_delta_step: 0.7] +[tweedie_variance_power: 1.5] +[lambdarank_truncation_level: 20] +[lambdarank_norm: 1] +[label_gain: ] +[lambdarank_position_bias_regularization: 0] +[eval_at: 1] +[multi_error_top_k: 1] +[auc_mu_weights: ] +[num_machines: 1] +[local_listen_port: 12400] +[time_out: 120] +[machine_list_filename: ] +[machines: ] +[gpu_platform_id: -1] +[gpu_device_id: -1] +[gpu_device_id_list: ] +[gpu_use_dp: 0] +[num_gpu: 1] + +end of parameters + +pandas_categorical:[] diff --git a/ranker_SNOMEDCT_US_s1_d3llm7e4.json b/ranker_SNOMEDCT_US_s1_d3llm7e4.json new file mode 100644 index 0000000000000000000000000000000000000000..ac170f53071c62c2e73e34e4e26077956f41a40c --- /dev/null +++ b/ranker_SNOMEDCT_US_s1_d3llm7e4.json @@ -0,0 +1 @@ +{"cols": ["char_max", "word_max", "char_var", "sapbert_max", "sapbert_pref", "sapbert_var", "reading_ctx", "reading_ctx_gap", "ctx_dense", "gte_max", "gte_pref", "gte_var", "qwen3_max", "qwen3_pref", "qwen3_var", "num_match", "num_conflict", "cand_neg", "cand_hist", "neg_match", "hist_match", "fz_ratio", "fz_tset", "fz_partial", "fz_tsort", "tok_qcov", "tok_dcov", "tok_dextra", "ctx_overlap", "cand_lat", "lat_match", "lat_conflict", "lat_missing", "nn_char_max", "nn_char_sum", "nn_dense_max", "nn_dense_sum", "nn_cnt", "nn_entctx_max", "nn_ctx_max", "prior", "exact", "mention", "n_desc", "semtag", "best_order", "best_is_pref", "char_max_rank", "char_max_gap", "word_max_rank", "word_max_gap", "char_var_rank", "char_var_gap", "sapbert_max_rank", "sapbert_max_gap", "sapbert_var_rank", "sapbert_var_gap", "gte_max_rank", "gte_max_gap", "gte_var_rank", "gte_var_gap", "qwen3_max_rank", "qwen3_max_gap", "qwen3_var_rank", "qwen3_var_gap", "fz_tset_rank", "fz_tset_gap", "nn_char_max_rank", "nn_char_max_gap", "nn_dense_max_rank", "nn_dense_max_gap", "nn_entctx_max_rank", "nn_entctx_max_gap", "nn_ctx_max_rank", "nn_ctx_max_gap", "prior_rank", "prior_gap", "q_len", "q_ntok", "q_digit", "q_abbr", "q_nvar", "q_lat", "q_neg", "q_hist", "q_fam", "subconcept", "n_cand"]} \ No newline at end of file diff --git a/ranker_SNOMEDCT_US_s1_d3llm7e4.txt b/ranker_SNOMEDCT_US_s1_d3llm7e4.txt new file mode 100644 index 0000000000000000000000000000000000000000..def03e3762fb5ea520e076e392361507507e1a52 --- /dev/null +++ b/ranker_SNOMEDCT_US_s1_d3llm7e4.txt @@ -0,0 +1,3718 @@ +tree +version=v4 +num_class=1 +num_tree_per_iteration=1 +label_index=0 +max_feature_idx=87 +objective=lambdarank +feature_names=char_max word_max char_var sapbert_max sapbert_pref sapbert_var reading_ctx reading_ctx_gap ctx_dense gte_max gte_pref gte_var qwen3_max qwen3_pref qwen3_var num_match num_conflict cand_neg cand_hist neg_match hist_match fz_ratio fz_tset fz_partial fz_tsort tok_qcov tok_dcov tok_dextra ctx_overlap cand_lat lat_match lat_conflict lat_missing nn_char_max nn_char_sum nn_dense_max nn_dense_sum nn_cnt nn_entctx_max nn_ctx_max prior exact mention n_desc semtag best_order best_is_pref char_max_rank char_max_gap word_max_rank word_max_gap char_var_rank char_var_gap sapbert_max_rank sapbert_max_gap sapbert_var_rank sapbert_var_gap gte_max_rank gte_max_gap gte_var_rank gte_var_gap qwen3_max_rank qwen3_max_gap qwen3_var_rank qwen3_var_gap fz_tset_rank fz_tset_gap nn_char_max_rank nn_char_max_gap nn_dense_max_rank nn_dense_max_gap nn_entctx_max_rank nn_entctx_max_gap nn_ctx_max_rank nn_ctx_max_gap prior_rank prior_gap q_len q_ntok q_digit q_abbr q_nvar q_lat q_neg q_hist q_fam subconcept n_cand +feature_infos=[0:1.0000001192092896] [0:1.0000001192092896] [0:1.0000001192092896] [-0.22487562894821167:1.0000755786895752] [-0.22487562894821167:1.0000648498535156] [-0.20326696336269379:1.0000648498535156] [-0.16142846643924713:0.75836026668548584] [0:0.4073173999786377] [-0.19607745110988617:0.99998879432678223] [0.64043503999710083:1.0001192092895508] [0.63986283540725708:1.0001192092895508] [0.65842556953430176:1.0001227855682373] 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+word_max_rank=209 +ctx_overlap=193 +gte_var_gap=183 +char_var_rank=182 +q_len=182 +sapbert_pref=181 +word_max_gap=177 +char_max_gap=175 +char_max_rank=172 +reading_ctx=168 +nn_entctx_max_gap=167 +qwen3_pref=165 +qwen3_var=165 +gte_var=162 +sapbert_var_gap=160 +qwen3_var_rank=159 +prior_rank=159 +fz_partial=158 +prior_gap=158 +sapbert_max_rank=154 +fz_ratio=153 +sapbert_var=150 +sapbert_max=147 +gte_pref=144 +char_var=139 +fz_tsort=136 +nn_dense_sum=135 +char_max=134 +nn_char_sum=134 +qwen3_max=128 +gte_max=123 +sapbert_var_rank=122 +qwen3_var_gap=122 +gte_var_rank=119 +nn_ctx_max_gap=116 +nn_char_max_rank=112 +fz_tset_rank=109 +fz_tset=106 +word_max=105 +nn_ctx_max=95 +nn_dense_max=91 +fz_tset_gap=89 +nn_char_max=87 +nn_entctx_max=78 +nn_entctx_max_rank=75 +nn_dense_max_rank=69 +reading_ctx_gap=59 +tok_dcov=55 +tok_dextra=53 +subconcept=53 +q_ntok=50 +n_desc=48 +nn_ctx_max_rank=48 +tok_qcov=37 +cand_neg=31 +best_order=26 +nn_cnt=21 +exact=13 +neg_match=7 +q_neg=6 +q_nvar=5 +num_conflict=4 +lat_conflict=4 +lat_missing=4 +q_digit=4 +num_match=3 +cand_hist=2 +hist_match=2 +lat_match=2 +q_abbr=2 +q_lat=2 +best_is_pref=1 + +parameters: +[boosting: gbdt] +[objective: lambdarank] +[metric: map] +[tree_learner: serial] +[device_type: cpu] +[data_sample_strategy: bagging] +[data: ] +[valid: ] +[num_iterations: 169] +[learning_rate: 0.05] +[num_leaves: 63] +[num_threads: 16] +[seed: 13] +[deterministic: 1] +[force_col_wise: 1] +[force_row_wise: 0] +[histogram_pool_size: -1] +[max_depth: -1] +[min_data_in_leaf: 20] +[min_sum_hessian_in_leaf: 0.001] +[bagging_fraction: 0.8] +[pos_bagging_fraction: 1] +[neg_bagging_fraction: 1] +[bagging_freq: 1] +[bagging_seed: 16376] +[bagging_by_query: 0] +[feature_fraction: 0.8] +[feature_fraction_bynode: 1] +[feature_fraction_seed: 20348] +[extra_trees: 0] +[extra_seed: 30076] +[early_stopping_round: 0] +[early_stopping_min_delta: 0] +[first_metric_only: 0] +[max_delta_step: 0] +[lambda_l1: 0] +[lambda_l2: 1] +[linear_lambda: 0] +[min_gain_to_split: 0] +[drop_rate: 0.1] +[max_drop: 50] +[skip_drop: 0.5] +[xgboost_dart_mode: 0] +[uniform_drop: 0] +[drop_seed: 24096] +[top_rate: 0.2] +[other_rate: 0.1] +[min_data_per_group: 100] +[max_cat_threshold: 32] +[cat_l2: 10] +[cat_smooth: 10] +[max_cat_to_onehot: 4] +[top_k: 20] +[monotone_constraints: ] +[monotone_constraints_method: basic] +[monotone_penalty: 0] +[feature_contri: ] +[forcedsplits_filename: ] +[refit_decay_rate: 0.9] +[cegb_tradeoff: 1] +[cegb_penalty_split: 0] +[cegb_penalty_feature_lazy: ] +[cegb_penalty_feature_coupled: ] +[path_smooth: 0] +[interaction_constraints: ] +[verbosity: -1] +[saved_feature_importance_type: 0] +[use_quantized_grad: 0] +[num_grad_quant_bins: 4] +[quant_train_renew_leaf: 0] +[stochastic_rounding: 1] +[linear_tree: 0] +[max_bin: 255] +[max_bin_by_feature: ] +[min_data_in_bin: 3] +[bin_construct_sample_cnt: 200000] +[data_random_seed: 81] +[is_enable_sparse: 1] +[enable_bundle: 1] +[use_missing: 1] +[zero_as_missing: 0] +[feature_pre_filter: 1] +[pre_partition: 0] +[two_round: 0] +[header: 0] +[label_column: ] +[weight_column: ] +[group_column: ] +[ignore_column: ] +[categorical_feature: 29,44,82,86] +[forcedbins_filename: ] +[precise_float_parser: 0] +[parser_config_file: ] +[objective_seed: 11872] +[num_class: 1] +[is_unbalance: 0] +[scale_pos_weight: 1] +[sigmoid: 1] +[boost_from_average: 1] +[reg_sqrt: 0] +[alpha: 0.9] +[fair_c: 1] +[poisson_max_delta_step: 0.7] +[tweedie_variance_power: 1.5] +[lambdarank_truncation_level: 20] +[lambdarank_norm: 1] +[label_gain: ] +[lambdarank_position_bias_regularization: 0] +[eval_at: 1] +[multi_error_top_k: 1] +[auc_mu_weights: ] +[num_machines: 1] +[local_listen_port: 12400] +[time_out: 120] +[machine_list_filename: ] +[machines: ] +[gpu_platform_id: -1] +[gpu_device_id: -1] +[gpu_device_id_list: ] +[gpu_use_dp: 0] +[num_gpu: 1] + +end of parameters + +pandas_categorical:[] diff --git a/ranker_SNOMEDCT_US_s1_sap4.json b/ranker_SNOMEDCT_US_s1_sap4.json new file mode 100644 index 0000000000000000000000000000000000000000..e7ab7fbaee621ef4f3fc39aea7792b40c674da2d --- /dev/null +++ b/ranker_SNOMEDCT_US_s1_sap4.json @@ -0,0 +1 @@ +{"cols": ["char_max", "word_max", "char_var", "sapbert_max", "sapbert_pref", "sapbert_var", "reading_ctx", "reading_ctx_gap", "ctx_dense", "num_match", "num_conflict", "cand_neg", "cand_hist", "neg_match", "hist_match", "fz_ratio", "fz_tset", "fz_partial", "fz_tsort", "tok_qcov", "tok_dcov", "tok_dextra", "ctx_overlap", "cand_lat", "lat_match", "lat_conflict", "lat_missing", "nn_char_max", "nn_char_sum", "nn_dense_max", "nn_dense_sum", "nn_cnt", "nn_entctx_max", "nn_ctx_max", "prior", "exact", "mention", "n_desc", "semtag", "best_order", "best_is_pref", "char_max_rank", "char_max_gap", "word_max_rank", "word_max_gap", "char_var_rank", "char_var_gap", "sapbert_max_rank", "sapbert_max_gap", "sapbert_var_rank", "sapbert_var_gap", "fz_tset_rank", "fz_tset_gap", "nn_char_max_rank", "nn_char_max_gap", "nn_dense_max_rank", "nn_dense_max_gap", "nn_entctx_max_rank", "nn_entctx_max_gap", "nn_ctx_max_rank", "nn_ctx_max_gap", "prior_rank", "prior_gap", "q_len", "q_ntok", "q_digit", "q_abbr", "q_nvar", "q_lat", "q_neg", "q_hist", "q_fam", "subconcept", "n_cand"]} \ No newline at end of file diff --git a/ranker_SNOMEDCT_US_s1_sap4.txt b/ranker_SNOMEDCT_US_s1_sap4.txt new file mode 100644 index 0000000000000000000000000000000000000000..619f94fdad7f4e2aacb42f2f53c9577e8e036bef --- /dev/null +++ b/ranker_SNOMEDCT_US_s1_sap4.txt @@ -0,0 +1,4487 @@ +tree +version=v4 +num_class=1 +num_tree_per_iteration=1 +label_index=0 +max_feature_idx=73 +objective=lambdarank +feature_names=char_max word_max char_var sapbert_max sapbert_pref sapbert_var reading_ctx reading_ctx_gap ctx_dense num_match num_conflict cand_neg cand_hist neg_match hist_match fz_ratio fz_tset fz_partial fz_tsort tok_qcov tok_dcov tok_dextra ctx_overlap cand_lat lat_match lat_conflict lat_missing nn_char_max nn_char_sum nn_dense_max nn_dense_sum nn_cnt nn_entctx_max nn_ctx_max prior exact mention n_desc semtag best_order best_is_pref char_max_rank char_max_gap word_max_rank word_max_gap char_var_rank char_var_gap sapbert_max_rank sapbert_max_gap sapbert_var_rank sapbert_var_gap fz_tset_rank fz_tset_gap nn_char_max_rank nn_char_max_gap nn_dense_max_rank nn_dense_max_gap nn_entctx_max_rank nn_entctx_max_gap nn_ctx_max_rank nn_ctx_max_gap prior_rank prior_gap q_len q_ntok q_digit q_abbr q_nvar q_lat q_neg q_hist q_fam subconcept n_cand +feature_infos=[0:1.0000001192092896] [0:1.0000001192092896] [0:1.0000002384185791] [-0.23509082198143005:1.0000761747360229] [-0.23509082198143005:1.0000655651092529] [-0.23509082198143005:1.0000655651092529] [-0.16151890158653259:0.75809895992279053] [0:0.40738597512245178] [-0.19644646346569061:1.0000041723251343] [0:3] [0:1] [0:1] [0:1] [0:1] [0:1] [0:100] [0:100] [0:100] [0:100] [0:1] [0:1] [0:22] [0:5] -1:0:1:2 [0:1] [0:1] [0:1] [0:1.0000001192092896] [0:7.3839993476867676] [0:1.0000004768371582] [0:5.9335556030273438] [0:12] [0:1.0000004768371582] [0:1.0000002384185791] [0:3.4011973816621555] [0:1] none [1:22] -1:1:0:2:6:3:4:8:11:5:19:7:10:18:15:13:16:12:14:9 [1:21] [0:1] [1:211] [0:1.0000001192092896] [1:166] [0:1.0000001192092896] [1:238] [0:1.0000001192092896] [1:247] [0:1.1792451143264771] [1:248] [0:1.1439464092254639] [1:248] [0:100] [1:21] [0:1.0000001192092896] [1:21] [0:1.0000008344650269] [1:21] [0:1.0000004768371582] [1:21] [0:1.0000002384185791] [1:54] [0:3.4011973816621555] [1:2724] [1:398] [0:1] [0:1] [0:3] -1:0:1:2 [0:1] [0:1] [0:1] -1:1:0:2:3:4 [51:248] +tree_sizes=7008 6994 6985 6978 7026 7000 7006 7022 7008 7023 6990 6982 7021 6975 6995 7037 6962 6965 7016 7012 6987 6963 6970 6974 6994 6997 7011 6997 6991 6978 7001 6950 6986 6992 7038 7030 6981 6982 6965 6969 6967 7014 6996 6995 6934 6980 7010 6993 6996 6981 7013 6983 6986 6976 7011 6961 6963 6968 7015 7014 7034 6959 7029 7021 7006 7050 6992 7059 6996 6995 7011 7041 6989 7041 7010 6980 7009 7039 7003 7064 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+sapbert_var_gap=292 +word_max_rank=291 +char_max_rank=282 +fz_tsort=279 +nn_entctx_max_gap=272 +reading_ctx=264 +q_len=259 +word_max=245 +nn_ctx_max_gap=240 +prior=239 +prior_gap=236 +prior_rank=235 +sapbert_var_rank=220 +fz_tset_rank=219 +char_max=216 +fz_tset=204 +ctx_overlap=197 +nn_char_sum=194 +nn_dense_sum=194 +fz_tset_gap=185 +nn_char_max=154 +nn_char_max_rank=150 +nn_ctx_max=147 +nn_dense_max=134 +nn_dense_max_rank=125 +n_desc=117 +nn_entctx_max=115 +reading_ctx_gap=101 +tok_dextra=101 +nn_entctx_max_rank=96 +tok_qcov=91 +nn_ctx_max_rank=86 +subconcept=79 +tok_dcov=76 +q_ntok=61 +best_order=56 +nn_cnt=36 +q_nvar=31 +exact=27 +cand_neg=24 +neg_match=24 +num_conflict=17 +q_neg=11 +cand_lat=9 +q_abbr=6 +lat_match=5 +q_digit=4 +cand_hist=3 +num_match=2 +hist_match=2 +lat_missing=2 +q_lat=2 +lat_conflict=1 +best_is_pref=1 + +parameters: +[boosting: gbdt] +[objective: lambdarank] +[metric: map] +[tree_learner: serial] +[device_type: cpu] +[data_sample_strategy: bagging] +[data: ] +[valid: ] +[num_iterations: 207] +[learning_rate: 0.05] +[num_leaves: 63] +[num_threads: 16] +[seed: 13] +[deterministic: 1] +[force_col_wise: 1] +[force_row_wise: 0] +[histogram_pool_size: -1] +[max_depth: -1] +[min_data_in_leaf: 20] +[min_sum_hessian_in_leaf: 0.001] +[bagging_fraction: 0.8] +[pos_bagging_fraction: 1] +[neg_bagging_fraction: 1] +[bagging_freq: 1] +[bagging_seed: 16376] +[bagging_by_query: 0] +[feature_fraction: 0.8] +[feature_fraction_bynode: 1] +[feature_fraction_seed: 20348] +[extra_trees: 0] +[extra_seed: 30076] +[early_stopping_round: 0] +[early_stopping_min_delta: 0] +[first_metric_only: 0] +[max_delta_step: 0] +[lambda_l1: 0] +[lambda_l2: 1] +[linear_lambda: 0] +[min_gain_to_split: 0] +[drop_rate: 0.1] +[max_drop: 50] +[skip_drop: 0.5] +[xgboost_dart_mode: 0] +[uniform_drop: 0] +[drop_seed: 24096] +[top_rate: 0.2] +[other_rate: 0.1] +[min_data_per_group: 100] +[max_cat_threshold: 32] +[cat_l2: 10] +[cat_smooth: 10] +[max_cat_to_onehot: 4] +[top_k: 20] +[monotone_constraints: ] +[monotone_constraints_method: basic] +[monotone_penalty: 0] +[feature_contri: ] +[forcedsplits_filename: ] +[refit_decay_rate: 0.9] +[cegb_tradeoff: 1] +[cegb_penalty_split: 0] +[cegb_penalty_feature_lazy: ] +[cegb_penalty_feature_coupled: ] +[path_smooth: 0] +[interaction_constraints: ] +[verbosity: -1] +[saved_feature_importance_type: 0] +[use_quantized_grad: 0] +[num_grad_quant_bins: 4] +[quant_train_renew_leaf: 0] +[stochastic_rounding: 1] +[linear_tree: 0] +[max_bin: 255] +[max_bin_by_feature: ] +[min_data_in_bin: 3] +[bin_construct_sample_cnt: 200000] +[data_random_seed: 81] +[is_enable_sparse: 1] +[enable_bundle: 1] +[use_missing: 1] +[zero_as_missing: 0] +[feature_pre_filter: 1] +[pre_partition: 0] +[two_round: 0] +[header: 0] +[label_column: ] +[weight_column: ] +[group_column: ] +[ignore_column: ] +[categorical_feature: 23,38,68,72] +[forcedbins_filename: ] +[precise_float_parser: 0] +[parser_config_file: ] +[objective_seed: 11872] +[num_class: 1] +[is_unbalance: 0] +[scale_pos_weight: 1] +[sigmoid: 1] +[boost_from_average: 1] +[reg_sqrt: 0] +[alpha: 0.9] +[fair_c: 1] +[poisson_max_delta_step: 0.7] +[tweedie_variance_power: 1.5] +[lambdarank_truncation_level: 20] +[lambdarank_norm: 1] +[label_gain: ] +[lambdarank_position_bias_regularization: 0] +[eval_at: 1] +[multi_error_top_k: 1] +[auc_mu_weights: ] +[num_machines: 1] +[local_listen_port: 12400] +[time_out: 120] +[machine_list_filename: ] +[machines: ] +[gpu_platform_id: -1] +[gpu_device_id: -1] +[gpu_device_id_list: ] +[gpu_use_dp: 0] +[num_gpu: 1] + +end of parameters + +pandas_categorical:[] diff --git a/ranker_SNOMEDCT_US_s2_d3ce4.json b/ranker_SNOMEDCT_US_s2_d3ce4.json new file mode 100644 index 0000000000000000000000000000000000000000..3c063ccd044c53a25d3e6824c3d5e91bf903794a --- /dev/null +++ b/ranker_SNOMEDCT_US_s2_d3ce4.json @@ -0,0 +1 @@ +{"cols": ["char_max", "word_max", "char_var", "sapbert_max", "sapbert_pref", "sapbert_var", "reading_ctx", "reading_ctx_gap", "ctx_dense", "gte_max", "gte_pref", "gte_var", "qwen3_max", "qwen3_pref", "qwen3_var", "num_match", "num_conflict", "cand_neg", "cand_hist", "neg_match", "hist_match", "fz_ratio", "fz_tset", "fz_partial", "fz_tsort", "tok_qcov", "tok_dcov", "tok_dextra", "ctx_overlap", "cand_lat", "lat_match", "lat_conflict", "lat_missing", "nn_char_max", "nn_char_sum", "nn_dense_max", "nn_dense_sum", "nn_cnt", "nn_entctx_max", "nn_ctx_max", "prior", "exact", "mention", "n_desc", "semtag", "best_order", "best_is_pref", "char_max_rank", "char_max_gap", "word_max_rank", "word_max_gap", "char_var_rank", "char_var_gap", "sapbert_max_rank", "sapbert_max_gap", "sapbert_var_rank", "sapbert_var_gap", "gte_max_rank", "gte_max_gap", "gte_var_rank", "gte_var_gap", "qwen3_max_rank", "qwen3_max_gap", "qwen3_var_rank", "qwen3_var_gap", "fz_tset_rank", "fz_tset_gap", "nn_char_max_rank", "nn_char_max_gap", "nn_dense_max_rank", "nn_dense_max_gap", "nn_entctx_max_rank", "nn_entctx_max_gap", "nn_ctx_max_rank", "nn_ctx_max_gap", "prior_rank", "prior_gap", "q_len", "q_ntok", "q_digit", "q_abbr", "q_nvar", "q_lat", "q_neg", "q_hist", "q_fam", "subconcept", "n_cand", "s1", "s1_rank", "s1_p", "s1_gap", "xs_cooc", "xs_cooc_top1", "xs_sim", "xs_sim_top1", "ce", "ce_lp", "ce_rank", "ce_gap", "ce_lp_rank", "ce_lp_gap"]} \ No newline at end of file diff --git a/ranker_SNOMEDCT_US_s2_d3ce4.txt b/ranker_SNOMEDCT_US_s2_d3ce4.txt new file mode 100644 index 0000000000000000000000000000000000000000..a314ee522a42eb99e12e34f13ceeaa89f9fe83d9 --- /dev/null +++ b/ranker_SNOMEDCT_US_s2_d3ce4.txt @@ -0,0 +1,1004 @@ +tree +version=v4 +num_class=1 +num_tree_per_iteration=1 +label_index=0 +max_feature_idx=101 +objective=lambdarank +feature_names=char_max word_max char_var sapbert_max sapbert_pref sapbert_var reading_ctx reading_ctx_gap ctx_dense gte_max gte_pref gte_var qwen3_max qwen3_pref qwen3_var num_match num_conflict cand_neg cand_hist neg_match hist_match fz_ratio fz_tset fz_partial fz_tsort tok_qcov tok_dcov tok_dextra ctx_overlap cand_lat lat_match lat_conflict lat_missing nn_char_max nn_char_sum nn_dense_max nn_dense_sum nn_cnt nn_entctx_max nn_ctx_max prior exact mention n_desc semtag best_order best_is_pref char_max_rank char_max_gap word_max_rank word_max_gap char_var_rank char_var_gap sapbert_max_rank sapbert_max_gap sapbert_var_rank sapbert_var_gap gte_max_rank gte_max_gap gte_var_rank gte_var_gap qwen3_max_rank qwen3_max_gap qwen3_var_rank qwen3_var_gap fz_tset_rank fz_tset_gap nn_char_max_rank nn_char_max_gap nn_dense_max_rank nn_dense_max_gap nn_entctx_max_rank nn_entctx_max_gap nn_ctx_max_rank nn_ctx_max_gap prior_rank prior_gap q_len q_ntok q_digit q_abbr q_nvar q_lat q_neg q_hist q_fam subconcept n_cand s1 s1_rank s1_p s1_gap xs_cooc xs_cooc_top1 xs_sim xs_sim_top1 ce ce_lp ce_rank ce_gap ce_lp_rank ce_lp_gap +feature_infos=[0:1.0000002384185791] [0:1.0000001192092896] [0:1.0000002384185791] [-0.056679505854845047:1.0000755786895752] [-0.056679505854845047:1.0000715255737305] 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-0.00108707 -0.00908846 -0.0142961 -0.000618685 -0.0366621 0.00391954 0.0117666 0.0187698 0.0222136 -0.0549611 -0.0107653 -0.0316305 -0.0481658 0.0183264 0.0224876 0.0309578 0.0026452 -0.0156276 0.00727854 -0.0224323 0.00855159 -0.0393353 -0.0139128 -0.0416512 +internal_weight=3448.97 2244.55 1204.42 544.772 1699.78 701.599 389.374 132.387 610.443 298.675 467.837 256.986 502.819 491.184 279.604 238.978 142.605 70.1215 17.7697 52.3518 454.411 424.334 214.838 203.822 94.2728 109.549 21.7082 211.58 45.0341 12.1237 21.9043 209.496 165.039 149.873 28.9872 44.4577 217.009 1089.34 141.741 106.283 96.817 60.7154 36.1016 11.4639 947.596 327.536 299.247 24.6377 28.2888 22.7711 17.2295 37.9443 35.4586 31.7382 235.119 47.0787 188.04 22.244 23.6241 23.4546 120.886 16.107 +internal_count=99850 19518 80332 3481 16037 61314 27851 15143 8806 1155 7994 12708 19018 18791 9209 12112 812 382 163 219 7676 7258 3993 3879 2169 1710 1934 9582 179 56 290 3265 2709 2551 317 556 11282 7231 1265 1052 1002 668 334 84 5966 1954 1748 250 206 293 247 375 213 157 5255 1146 4109 626 464 682 2234 522 +cat_boundaries=0 1 2 +cat_threshold=266704 16708 +is_linear=0 +shrinkage=0.05 + + +end of trees + +feature_importances: +s1_p=210 +ce_lp=156 +ce=109 +ce_rank=102 +s1_gap=90 +sapbert_pref=53 +qwen3_max_gap=50 +ce_gap=45 +sapbert_max=42 +ctx_dense=41 +ce_lp_gap=40 +gte_max_gap=39 +nn_char_max_gap=39 +char_var=37 +semtag=37 +sapbert_max_gap=36 +gte_var_gap=36 +prior_gap=35 +s1=35 +qwen3_pref=34 +gte_pref=33 +word_max_gap=33 +prior_rank=31 +char_max_gap=30 +word_max_rank=30 +qwen3_var=28 +fz_ratio=28 +qwen3_var_rank=28 +char_max=27 +qwen3_max=27 +xs_sim_top1=27 +reading_ctx=26 +nn_ctx_max_gap=26 +qwen3_var_gap=25 +s1_rank=25 +xs_sim=25 +word_max=24 +gte_max=24 +char_var_rank=24 +char_var_gap=22 +sapbert_var_gap=22 +gte_max_rank=22 +gte_var_rank=22 +qwen3_max_rank=22 +n_cand=22 +fz_tset_gap=21 +fz_tset_rank=20 +gte_var=19 +nn_char_max=19 +fz_partial=18 +nn_dense_max_gap=18 +fz_tset=17 +n_desc=17 +fz_tsort=16 +q_len=16 +sapbert_var=15 +nn_char_sum=15 +nn_ctx_max=15 +best_order=15 +nn_entctx_max_gap=15 +nn_dense_max=14 +nn_dense_sum=13 +sapbert_var_rank=13 +sapbert_max_rank=12 +nn_char_max_rank=12 +xs_cooc_top1=12 +char_max_rank=11 +nn_dense_max_rank=10 +reading_ctx_gap=8 +nn_entctx_max=8 +nn_entctx_max_rank=8 +q_ntok=8 +xs_cooc=8 +tok_dextra=7 +prior=7 +nn_ctx_max_rank=6 +best_is_pref=5 +tok_dcov=4 +ce_lp_rank=4 +tok_qcov=2 +ctx_overlap=2 +q_nvar=2 +cand_neg=1 +nn_cnt=1 +q_lat=1 +q_neg=1 +subconcept=1 + +parameters: +[boosting: gbdt] +[objective: lambdarank] +[metric: map] +[tree_learner: serial] +[device_type: cpu] +[data_sample_strategy: bagging] +[data: ] +[valid: ] +[num_iterations: 38] +[learning_rate: 0.05] +[num_leaves: 63] +[num_threads: 16] +[seed: 13] +[deterministic: 1] +[force_col_wise: 1] +[force_row_wise: 0] +[histogram_pool_size: -1] +[max_depth: -1] +[min_data_in_leaf: 20] +[min_sum_hessian_in_leaf: 0.001] +[bagging_fraction: 0.8] +[pos_bagging_fraction: 1] +[neg_bagging_fraction: 1] +[bagging_freq: 1] +[bagging_seed: 16376] +[bagging_by_query: 0] +[feature_fraction: 0.8] +[feature_fraction_bynode: 1] +[feature_fraction_seed: 20348] +[extra_trees: 0] +[extra_seed: 30076] +[early_stopping_round: 0] +[early_stopping_min_delta: 0] +[first_metric_only: 0] +[max_delta_step: 0] +[lambda_l1: 0] +[lambda_l2: 1] +[linear_lambda: 0] +[min_gain_to_split: 0] +[drop_rate: 0.1] +[max_drop: 50] +[skip_drop: 0.5] +[xgboost_dart_mode: 0] +[uniform_drop: 0] +[drop_seed: 24096] +[top_rate: 0.2] +[other_rate: 0.1] +[min_data_per_group: 100] +[max_cat_threshold: 32] +[cat_l2: 10] +[cat_smooth: 10] +[max_cat_to_onehot: 4] +[top_k: 20] +[monotone_constraints: ] +[monotone_constraints_method: basic] +[monotone_penalty: 0] +[feature_contri: ] +[forcedsplits_filename: ] +[refit_decay_rate: 0.9] +[cegb_tradeoff: 1] +[cegb_penalty_split: 0] +[cegb_penalty_feature_lazy: ] +[cegb_penalty_feature_coupled: ] +[path_smooth: 0] +[interaction_constraints: ] +[verbosity: -1] +[saved_feature_importance_type: 0] +[use_quantized_grad: 0] +[num_grad_quant_bins: 4] +[quant_train_renew_leaf: 0] +[stochastic_rounding: 1] +[linear_tree: 0] +[max_bin: 255] +[max_bin_by_feature: ] +[min_data_in_bin: 3] +[bin_construct_sample_cnt: 200000] +[data_random_seed: 81] +[is_enable_sparse: 1] +[enable_bundle: 1] +[use_missing: 1] +[zero_as_missing: 0] +[feature_pre_filter: 1] +[pre_partition: 0] +[two_round: 0] +[header: 0] +[label_column: ] +[weight_column: ] +[group_column: ] +[ignore_column: ] +[categorical_feature: 29,44,82,86] +[forcedbins_filename: ] +[precise_float_parser: 0] +[parser_config_file: ] +[objective_seed: 11872] +[num_class: 1] +[is_unbalance: 0] +[scale_pos_weight: 1] +[sigmoid: 1] +[boost_from_average: 1] +[reg_sqrt: 0] +[alpha: 0.9] +[fair_c: 1] +[poisson_max_delta_step: 0.7] +[tweedie_variance_power: 1.5] +[lambdarank_truncation_level: 20] +[lambdarank_norm: 1] +[label_gain: ] +[lambdarank_position_bias_regularization: 0] +[eval_at: 1] +[multi_error_top_k: 1] +[auc_mu_weights: ] +[num_machines: 1] +[local_listen_port: 12400] +[time_out: 120] +[machine_list_filename: ] +[machines: ] +[gpu_platform_id: -1] +[gpu_device_id: -1] +[gpu_device_id_list: ] +[gpu_use_dp: 0] +[num_gpu: 1] + +end of parameters + +pandas_categorical:[] diff --git a/ranker_SNOMEDCT_US_s2_d3llm14e4.json b/ranker_SNOMEDCT_US_s2_d3llm14e4.json new file mode 100644 index 0000000000000000000000000000000000000000..289102e0798cd9cea48744b681eb4636887c8391 --- /dev/null +++ b/ranker_SNOMEDCT_US_s2_d3llm14e4.json @@ -0,0 +1 @@ +{"cols": ["char_max", "word_max", "char_var", "sapbert_max", "sapbert_pref", "sapbert_var", "reading_ctx", "reading_ctx_gap", "ctx_dense", "gte_max", "gte_pref", "gte_var", "qwen3_max", "qwen3_pref", "qwen3_var", "num_match", "num_conflict", "cand_neg", "cand_hist", "neg_match", "hist_match", "fz_ratio", "fz_tset", "fz_partial", "fz_tsort", "tok_qcov", "tok_dcov", "tok_dextra", "ctx_overlap", "cand_lat", "lat_match", "lat_conflict", "lat_missing", "nn_char_max", "nn_char_sum", "nn_dense_max", "nn_dense_sum", "nn_cnt", "nn_entctx_max", "nn_ctx_max", "prior", "exact", "mention", "n_desc", "semtag", "best_order", "best_is_pref", "char_max_rank", "char_max_gap", "word_max_rank", "word_max_gap", "char_var_rank", "char_var_gap", "sapbert_max_rank", "sapbert_max_gap", "sapbert_var_rank", "sapbert_var_gap", "gte_max_rank", "gte_max_gap", "gte_var_rank", "gte_var_gap", "qwen3_max_rank", "qwen3_max_gap", "qwen3_var_rank", "qwen3_var_gap", "fz_tset_rank", "fz_tset_gap", "nn_char_max_rank", "nn_char_max_gap", "nn_dense_max_rank", "nn_dense_max_gap", "nn_entctx_max_rank", "nn_entctx_max_gap", "nn_ctx_max_rank", "nn_ctx_max_gap", "prior_rank", "prior_gap", "q_len", "q_ntok", "q_digit", "q_abbr", "q_nvar", "q_lat", "q_neg", "q_hist", "q_fam", "subconcept", "n_cand", "s1", "s1_rank", "s1_p", "s1_gap", "xs_cooc", "xs_cooc_top1", "xs_sim", "xs_sim_top1", "llm_lp", "llm_lp_rank", "llm_lp_gap", "ce", "ce_lp", "ce_rank", "ce_gap", "ce_lp_rank", "ce_lp_gap"]} \ No newline at end of file diff --git a/ranker_SNOMEDCT_US_s2_d3llm14e4.txt b/ranker_SNOMEDCT_US_s2_d3llm14e4.txt new file mode 100644 index 0000000000000000000000000000000000000000..a6a9133b265047fc7e725ada9b325a5095c43cac --- /dev/null +++ b/ranker_SNOMEDCT_US_s2_d3llm14e4.txt @@ -0,0 +1,1307 @@ +tree +version=v4 +num_class=1 +num_tree_per_iteration=1 +label_index=0 +max_feature_idx=104 +objective=lambdarank +feature_names=char_max word_max char_var sapbert_max sapbert_pref sapbert_var reading_ctx reading_ctx_gap ctx_dense gte_max gte_pref gte_var qwen3_max qwen3_pref qwen3_var num_match num_conflict cand_neg cand_hist neg_match hist_match fz_ratio fz_tset fz_partial fz_tsort tok_qcov tok_dcov tok_dextra ctx_overlap cand_lat lat_match lat_conflict lat_missing nn_char_max nn_char_sum nn_dense_max nn_dense_sum nn_cnt nn_entctx_max nn_ctx_max prior exact mention n_desc semtag best_order best_is_pref char_max_rank char_max_gap word_max_rank word_max_gap char_var_rank char_var_gap sapbert_max_rank sapbert_max_gap sapbert_var_rank sapbert_var_gap gte_max_rank gte_max_gap gte_var_rank gte_var_gap qwen3_max_rank qwen3_max_gap qwen3_var_rank qwen3_var_gap fz_tset_rank fz_tset_gap nn_char_max_rank nn_char_max_gap nn_dense_max_rank nn_dense_max_gap nn_entctx_max_rank nn_entctx_max_gap nn_ctx_max_rank nn_ctx_max_gap prior_rank prior_gap q_len q_ntok q_digit q_abbr q_nvar q_lat q_neg q_hist q_fam subconcept n_cand s1 s1_rank s1_p s1_gap xs_cooc xs_cooc_top1 xs_sim xs_sim_top1 llm_lp llm_lp_rank llm_lp_gap ce ce_lp ce_rank ce_gap ce_lp_rank ce_lp_gap +feature_infos=[0:1.0000002384185791] [0:1.0000001192092896] [0:1.0000002384185791] [-0.056679505854845047:1.0000755786895752] [-0.056679505854845047:1.0000715255737305] [-0.061544004827737808:1.0000715255737305] [-0.16142846643924713:0.75836026668548584] [0:0.4073173999786377] [-0.14609634876251221:1.0000033378601074] [0.68049824237823486:1.0002431869506836] 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63] +[num_threads: 16] +[seed: 13] +[deterministic: 1] +[force_col_wise: 1] +[force_row_wise: 0] +[histogram_pool_size: -1] +[max_depth: -1] +[min_data_in_leaf: 20] +[min_sum_hessian_in_leaf: 0.001] +[bagging_fraction: 0.8] +[pos_bagging_fraction: 1] +[neg_bagging_fraction: 1] +[bagging_freq: 1] +[bagging_seed: 16376] +[bagging_by_query: 0] +[feature_fraction: 0.8] +[feature_fraction_bynode: 1] +[feature_fraction_seed: 20348] +[extra_trees: 0] +[extra_seed: 30076] +[early_stopping_round: 0] +[early_stopping_min_delta: 0] +[first_metric_only: 0] +[max_delta_step: 0] +[lambda_l1: 0] +[lambda_l2: 1] +[linear_lambda: 0] +[min_gain_to_split: 0] +[drop_rate: 0.1] +[max_drop: 50] +[skip_drop: 0.5] +[xgboost_dart_mode: 0] +[uniform_drop: 0] +[drop_seed: 24096] +[top_rate: 0.2] +[other_rate: 0.1] +[min_data_per_group: 100] +[max_cat_threshold: 32] +[cat_l2: 10] +[cat_smooth: 10] +[max_cat_to_onehot: 4] +[top_k: 20] +[monotone_constraints: ] +[monotone_constraints_method: basic] +[monotone_penalty: 0] +[feature_contri: ] +[forcedsplits_filename: ] +[refit_decay_rate: 0.9] +[cegb_tradeoff: 1] +[cegb_penalty_split: 0] +[cegb_penalty_feature_lazy: ] +[cegb_penalty_feature_coupled: ] +[path_smooth: 0] +[interaction_constraints: ] +[verbosity: -1] +[saved_feature_importance_type: 0] +[use_quantized_grad: 0] +[num_grad_quant_bins: 4] +[quant_train_renew_leaf: 0] +[stochastic_rounding: 1] +[linear_tree: 0] +[max_bin: 255] +[max_bin_by_feature: ] +[min_data_in_bin: 3] +[bin_construct_sample_cnt: 200000] +[data_random_seed: 81] +[is_enable_sparse: 1] +[enable_bundle: 1] +[use_missing: 1] +[zero_as_missing: 0] +[feature_pre_filter: 1] +[pre_partition: 0] +[two_round: 0] +[header: 0] +[label_column: ] +[weight_column: ] +[group_column: ] +[ignore_column: ] +[categorical_feature: 29,44,82,86] +[forcedbins_filename: ] +[precise_float_parser: 0] +[parser_config_file: ] +[objective_seed: 11872] +[num_class: 1] +[is_unbalance: 0] +[scale_pos_weight: 1] +[sigmoid: 1] +[boost_from_average: 1] +[reg_sqrt: 0] +[alpha: 0.9] +[fair_c: 1] +[poisson_max_delta_step: 0.7] +[tweedie_variance_power: 1.5] +[lambdarank_truncation_level: 20] +[lambdarank_norm: 1] +[label_gain: ] +[lambdarank_position_bias_regularization: 0] +[eval_at: 1] +[multi_error_top_k: 1] +[auc_mu_weights: ] +[num_machines: 1] +[local_listen_port: 12400] +[time_out: 120] +[machine_list_filename: ] +[machines: ] +[gpu_platform_id: -1] +[gpu_device_id: -1] +[gpu_device_id_list: ] +[gpu_use_dp: 0] +[num_gpu: 1] + +end of parameters + +pandas_categorical:[] diff --git a/ranker_SNOMEDCT_US_s2_d3llm7e4.json b/ranker_SNOMEDCT_US_s2_d3llm7e4.json new file mode 100644 index 0000000000000000000000000000000000000000..289102e0798cd9cea48744b681eb4636887c8391 --- /dev/null +++ b/ranker_SNOMEDCT_US_s2_d3llm7e4.json @@ -0,0 +1 @@ +{"cols": ["char_max", "word_max", "char_var", "sapbert_max", "sapbert_pref", "sapbert_var", "reading_ctx", "reading_ctx_gap", "ctx_dense", "gte_max", "gte_pref", "gte_var", "qwen3_max", "qwen3_pref", "qwen3_var", "num_match", "num_conflict", "cand_neg", "cand_hist", "neg_match", "hist_match", "fz_ratio", "fz_tset", "fz_partial", "fz_tsort", "tok_qcov", "tok_dcov", "tok_dextra", "ctx_overlap", "cand_lat", "lat_match", "lat_conflict", "lat_missing", "nn_char_max", "nn_char_sum", "nn_dense_max", "nn_dense_sum", "nn_cnt", "nn_entctx_max", "nn_ctx_max", "prior", "exact", "mention", "n_desc", "semtag", "best_order", "best_is_pref", "char_max_rank", "char_max_gap", "word_max_rank", "word_max_gap", "char_var_rank", "char_var_gap", "sapbert_max_rank", "sapbert_max_gap", "sapbert_var_rank", "sapbert_var_gap", "gte_max_rank", "gte_max_gap", "gte_var_rank", "gte_var_gap", "qwen3_max_rank", "qwen3_max_gap", "qwen3_var_rank", "qwen3_var_gap", "fz_tset_rank", "fz_tset_gap", "nn_char_max_rank", "nn_char_max_gap", "nn_dense_max_rank", "nn_dense_max_gap", "nn_entctx_max_rank", "nn_entctx_max_gap", "nn_ctx_max_rank", "nn_ctx_max_gap", "prior_rank", "prior_gap", "q_len", "q_ntok", "q_digit", "q_abbr", "q_nvar", "q_lat", "q_neg", "q_hist", "q_fam", "subconcept", "n_cand", "s1", "s1_rank", "s1_p", "s1_gap", "xs_cooc", "xs_cooc_top1", "xs_sim", "xs_sim_top1", "llm_lp", "llm_lp_rank", "llm_lp_gap", "ce", "ce_lp", "ce_rank", "ce_gap", "ce_lp_rank", "ce_lp_gap"]} \ No newline at end of file diff --git a/ranker_SNOMEDCT_US_s2_d3llm7e4.txt b/ranker_SNOMEDCT_US_s2_d3llm7e4.txt new file mode 100644 index 0000000000000000000000000000000000000000..74a442bf2b43b441fd38f81521ab6c193a4a9a47 --- /dev/null +++ b/ranker_SNOMEDCT_US_s2_d3llm7e4.txt @@ -0,0 +1,581 @@ +tree +version=v4 +num_class=1 +num_tree_per_iteration=1 +label_index=0 +max_feature_idx=104 +objective=lambdarank +feature_names=char_max word_max char_var sapbert_max sapbert_pref sapbert_var reading_ctx reading_ctx_gap ctx_dense gte_max gte_pref gte_var qwen3_max qwen3_pref qwen3_var num_match num_conflict cand_neg cand_hist neg_match hist_match fz_ratio fz_tset fz_partial fz_tsort tok_qcov tok_dcov tok_dextra ctx_overlap cand_lat lat_match lat_conflict lat_missing nn_char_max nn_char_sum nn_dense_max nn_dense_sum nn_cnt nn_entctx_max nn_ctx_max prior exact mention n_desc semtag best_order best_is_pref char_max_rank char_max_gap word_max_rank word_max_gap char_var_rank char_var_gap sapbert_max_rank sapbert_max_gap sapbert_var_rank sapbert_var_gap gte_max_rank gte_max_gap gte_var_rank gte_var_gap qwen3_max_rank qwen3_max_gap qwen3_var_rank qwen3_var_gap fz_tset_rank fz_tset_gap nn_char_max_rank nn_char_max_gap nn_dense_max_rank nn_dense_max_gap nn_entctx_max_rank nn_entctx_max_gap nn_ctx_max_rank nn_ctx_max_gap prior_rank prior_gap q_len q_ntok q_digit q_abbr q_nvar q_lat q_neg q_hist q_fam subconcept n_cand s1 s1_rank s1_p s1_gap xs_cooc xs_cooc_top1 xs_sim xs_sim_top1 llm_lp llm_lp_rank llm_lp_gap ce ce_lp ce_rank ce_gap ce_lp_rank ce_lp_gap +feature_infos=[0:1.0000002384185791] [0:1.0000001192092896] [0:1.0000002384185791] [-0.056679505854845047:1.0000755786895752] 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734.71309763961472 20.959375428734347 42.202203433960676 13.481204541400073 63.661312882555649 14.881681710481642 6.3673596223816267 16.105996901169423 8.3955259360373002 223.0250251267571 7.702189637348055 160.84514258941635 8.1913569085299951 6.8702263431623569 7.4186306493356815 13.0677348151803 19.894149863161154 4.1698504686355582 7.6603216342627993 8.9165104059502465 3.3559045754373065 8.9811499640345591 6.9800296202301979 8.4138268772512657 127.58116070693359 43.7829813612625 7.1976630082353941 +leaf_count=2685 145 7869 2719 27657 2150 557 717 212 130 851 1139 13729 666 16 188 2438 266 41 225 184 172 55 1217 994 397 262 61 47 52 566 125 43 493 4134 363 21061 598 260 69 1347 151 15 40 40 544 35 494 109 59 100 131 68 44 74 29 45 22 54 120 597 315 61 +internal_value=-0.000200069 -0.0321084 0.0307699 -0.0417859 0.016778 -0.000923173 0.0242052 0.0462939 -0.0243004 -0.0187173 -0.0466395 -0.0422427 -0.00357082 0.0102007 0.0343429 -0.0322157 0.0282084 0.0162613 0.00178259 -0.0103878 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77401 9369 9755 4645 3522 5384 8720 68681 41024 4724 4371 1484 5123 803 447 3081 1458 3599 3161 3042 1825 831 434 356 391 99 950 1274 377 897 27295 26156 22022 961 895 635 1643 296 56 292 80 767 579 772 152 404 225 261 680 186 142 90 1623 92 70 179 1578 981 2211 +cat_boundaries=0 1 2 +cat_threshold=3366 13 +is_linear=0 +shrinkage=0.05 + + +end of trees + +feature_importances: +ce_lp=103 +s1_p=87 +llm_lp=78 +llm_lp_gap=61 +s1_gap=51 +ce_rank=44 +ce=31 +gte_var=25 +s1_rank=24 +ce_gap=23 +ce_lp_gap=23 +sapbert_max_gap=20 +word_max_gap=17 +s1=16 +ctx_dense=15 +gte_max=15 +sapbert_pref=14 +fz_ratio=14 +char_max_gap=14 +q_len=14 +char_var_gap=13 +qwen3_var_gap=13 +gte_var_gap=12 +nn_ctx_max_gap=12 +prior_gap=12 +sapbert_var_rank=11 +nn_dense_max_gap=11 +llm_lp_rank=11 +sapbert_var=10 +reading_ctx=10 +word_max_rank=10 +qwen3_max_gap=10 +fz_tset_rank=10 +gte_pref=9 +qwen3_pref=9 +best_order=9 +gte_max_gap=9 +qwen3_var_rank=9 +sapbert_max=8 +qwen3_var=8 +fz_partial=8 +fz_tsort=8 +nn_dense_max=8 +char_var_rank=8 +sapbert_max_rank=8 +qwen3_max_rank=8 +word_max=7 +qwen3_max=7 +nn_dense_sum=7 +n_desc=7 +char_max_rank=7 +sapbert_var_gap=7 +gte_var_rank=7 +prior_rank=7 +ce_lp_rank=7 +char_max=6 +char_var=6 +reading_ctx_gap=6 +semtag=6 +fz_tset_gap=6 +nn_char_max_gap=6 +n_cand=6 +nn_ctx_max=5 +nn_entctx_max_gap=5 +xs_cooc=5 +xs_sim=5 +fz_tset=4 +nn_char_max=4 +nn_char_max_rank=4 +xs_sim_top1=4 +tok_qcov=3 +nn_char_sum=3 +nn_entctx_max=3 +nn_dense_max_rank=3 +nn_ctx_max_rank=3 +subconcept=3 +xs_cooc_top1=3 +tok_dcov=2 +gte_max_rank=2 +q_ntok=2 +q_nvar=2 +tok_dextra=1 +ctx_overlap=1 +nn_entctx_max_rank=1 + +parameters: +[boosting: gbdt] +[objective: lambdarank] +[metric: map] +[tree_learner: serial] +[device_type: cpu] +[data_sample_strategy: bagging] +[data: ] +[valid: ] +[num_iterations: 18] +[learning_rate: 0.05] +[num_leaves: 63] +[num_threads: 16] +[seed: 13] +[deterministic: 1] +[force_col_wise: 1] +[force_row_wise: 0] +[histogram_pool_size: -1] +[max_depth: -1] +[min_data_in_leaf: 20] +[min_sum_hessian_in_leaf: 0.001] +[bagging_fraction: 0.8] +[pos_bagging_fraction: 1] +[neg_bagging_fraction: 1] +[bagging_freq: 1] +[bagging_seed: 16376] +[bagging_by_query: 0] +[feature_fraction: 0.8] +[feature_fraction_bynode: 1] +[feature_fraction_seed: 20348] +[extra_trees: 0] +[extra_seed: 30076] +[early_stopping_round: 0] +[early_stopping_min_delta: 0] +[first_metric_only: 0] +[max_delta_step: 0] +[lambda_l1: 0] +[lambda_l2: 1] +[linear_lambda: 0] +[min_gain_to_split: 0] +[drop_rate: 0.1] +[max_drop: 50] +[skip_drop: 0.5] +[xgboost_dart_mode: 0] +[uniform_drop: 0] +[drop_seed: 24096] +[top_rate: 0.2] +[other_rate: 0.1] +[min_data_per_group: 100] +[max_cat_threshold: 32] +[cat_l2: 10] +[cat_smooth: 10] +[max_cat_to_onehot: 4] +[top_k: 20] +[monotone_constraints: ] +[monotone_constraints_method: basic] +[monotone_penalty: 0] +[feature_contri: ] +[forcedsplits_filename: ] +[refit_decay_rate: 0.9] +[cegb_tradeoff: 1] +[cegb_penalty_split: 0] +[cegb_penalty_feature_lazy: ] +[cegb_penalty_feature_coupled: ] +[path_smooth: 0] +[interaction_constraints: ] +[verbosity: -1] +[saved_feature_importance_type: 0] +[use_quantized_grad: 0] +[num_grad_quant_bins: 4] +[quant_train_renew_leaf: 0] +[stochastic_rounding: 1] +[linear_tree: 0] +[max_bin: 255] +[max_bin_by_feature: ] +[min_data_in_bin: 3] +[bin_construct_sample_cnt: 200000] +[data_random_seed: 81] +[is_enable_sparse: 1] +[enable_bundle: 1] +[use_missing: 1] +[zero_as_missing: 0] +[feature_pre_filter: 1] +[pre_partition: 0] +[two_round: 0] +[header: 0] +[label_column: ] +[weight_column: ] +[group_column: ] +[ignore_column: ] +[categorical_feature: 29,44,82,86] +[forcedbins_filename: ] +[precise_float_parser: 0] +[parser_config_file: ] +[objective_seed: 11872] +[num_class: 1] +[is_unbalance: 0] +[scale_pos_weight: 1] +[sigmoid: 1] +[boost_from_average: 1] +[reg_sqrt: 0] +[alpha: 0.9] +[fair_c: 1] +[poisson_max_delta_step: 0.7] +[tweedie_variance_power: 1.5] +[lambdarank_truncation_level: 20] +[lambdarank_norm: 1] +[label_gain: ] +[lambdarank_position_bias_regularization: 0] +[eval_at: 1] +[multi_error_top_k: 1] +[auc_mu_weights: ] +[num_machines: 1] +[local_listen_port: 12400] +[time_out: 120] +[machine_list_filename: ] +[machines: ] +[gpu_platform_id: -1] +[gpu_device_id: -1] +[gpu_device_id_list: ] +[gpu_use_dp: 0] +[num_gpu: 1] + +end of parameters + +pandas_categorical:[] diff --git a/ranker_SNOMEDCT_US_s2_sap4.json b/ranker_SNOMEDCT_US_s2_sap4.json new file mode 100644 index 0000000000000000000000000000000000000000..c1919a026048c4546be776cc05b280dd18655003 --- /dev/null +++ b/ranker_SNOMEDCT_US_s2_sap4.json @@ -0,0 +1 @@ +{"cols": ["char_max", "word_max", "char_var", "sapbert_max", "sapbert_pref", "sapbert_var", "reading_ctx", "reading_ctx_gap", "ctx_dense", "num_match", "num_conflict", "cand_neg", "cand_hist", "neg_match", "hist_match", "fz_ratio", "fz_tset", "fz_partial", "fz_tsort", "tok_qcov", "tok_dcov", "tok_dextra", "ctx_overlap", "cand_lat", "lat_match", "lat_conflict", "lat_missing", "nn_char_max", "nn_char_sum", "nn_dense_max", "nn_dense_sum", "nn_cnt", "nn_entctx_max", "nn_ctx_max", "prior", "exact", "mention", "n_desc", "semtag", "best_order", "best_is_pref", "char_max_rank", "char_max_gap", "word_max_rank", "word_max_gap", "char_var_rank", "char_var_gap", "sapbert_max_rank", "sapbert_max_gap", "sapbert_var_rank", "sapbert_var_gap", "fz_tset_rank", "fz_tset_gap", "nn_char_max_rank", "nn_char_max_gap", "nn_dense_max_rank", "nn_dense_max_gap", "nn_entctx_max_rank", "nn_entctx_max_gap", "nn_ctx_max_rank", "nn_ctx_max_gap", "prior_rank", "prior_gap", "q_len", "q_ntok", "q_digit", "q_abbr", "q_nvar", "q_lat", "q_neg", "q_hist", "q_fam", "subconcept", "n_cand", "s1", "s1_rank", "s1_p", "s1_gap", "xs_cooc", "xs_cooc_top1", "xs_sim", "xs_sim_top1"]} \ No newline at end of file diff --git a/ranker_SNOMEDCT_US_s2_sap4.txt b/ranker_SNOMEDCT_US_s2_sap4.txt new file mode 100644 index 0000000000000000000000000000000000000000..39d5b5337d679988e1b7d204db57e2d56c6486df --- /dev/null +++ b/ranker_SNOMEDCT_US_s2_sap4.txt @@ -0,0 +1,1570 @@ +tree +version=v4 +num_class=1 +num_tree_per_iteration=1 +label_index=0 +max_feature_idx=81 +objective=lambdarank +feature_names=char_max word_max char_var sapbert_max sapbert_pref sapbert_var reading_ctx reading_ctx_gap ctx_dense num_match num_conflict cand_neg cand_hist neg_match hist_match fz_ratio fz_tset fz_partial fz_tsort tok_qcov tok_dcov tok_dextra ctx_overlap cand_lat lat_match lat_conflict lat_missing nn_char_max nn_char_sum nn_dense_max nn_dense_sum nn_cnt nn_entctx_max nn_ctx_max prior exact mention n_desc semtag best_order best_is_pref char_max_rank char_max_gap word_max_rank word_max_gap char_var_rank char_var_gap sapbert_max_rank sapbert_max_gap sapbert_var_rank sapbert_var_gap fz_tset_rank fz_tset_gap nn_char_max_rank nn_char_max_gap nn_dense_max_rank nn_dense_max_gap nn_entctx_max_rank nn_entctx_max_gap 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+[feature_fraction_seed: 20348] +[extra_trees: 0] +[extra_seed: 30076] +[early_stopping_round: 0] +[early_stopping_min_delta: 0] +[first_metric_only: 0] +[max_delta_step: 0] +[lambda_l1: 0] +[lambda_l2: 1] +[linear_lambda: 0] +[min_gain_to_split: 0] +[drop_rate: 0.1] +[max_drop: 50] +[skip_drop: 0.5] +[xgboost_dart_mode: 0] +[uniform_drop: 0] +[drop_seed: 24096] +[top_rate: 0.2] +[other_rate: 0.1] +[min_data_per_group: 100] +[max_cat_threshold: 32] +[cat_l2: 10] +[cat_smooth: 10] +[max_cat_to_onehot: 4] +[top_k: 20] +[monotone_constraints: ] +[monotone_constraints_method: basic] +[monotone_penalty: 0] +[feature_contri: ] +[forcedsplits_filename: ] +[refit_decay_rate: 0.9] +[cegb_tradeoff: 1] +[cegb_penalty_split: 0] +[cegb_penalty_feature_lazy: ] +[cegb_penalty_feature_coupled: ] +[path_smooth: 0] +[interaction_constraints: ] +[verbosity: -1] +[saved_feature_importance_type: 0] +[use_quantized_grad: 0] +[num_grad_quant_bins: 4] +[quant_train_renew_leaf: 0] +[stochastic_rounding: 1] +[linear_tree: 0] +[max_bin: 255] +[max_bin_by_feature: ] +[min_data_in_bin: 3] +[bin_construct_sample_cnt: 200000] +[data_random_seed: 81] +[is_enable_sparse: 1] +[enable_bundle: 1] +[use_missing: 1] +[zero_as_missing: 0] +[feature_pre_filter: 1] +[pre_partition: 0] +[two_round: 0] +[header: 0] +[label_column: ] +[weight_column: ] +[group_column: ] +[ignore_column: ] +[categorical_feature: 23,38,68,72] +[forcedbins_filename: ] +[precise_float_parser: 0] +[parser_config_file: ] +[objective_seed: 11872] +[num_class: 1] +[is_unbalance: 0] +[scale_pos_weight: 1] +[sigmoid: 1] +[boost_from_average: 1] +[reg_sqrt: 0] +[alpha: 0.9] +[fair_c: 1] +[poisson_max_delta_step: 0.7] +[tweedie_variance_power: 1.5] +[lambdarank_truncation_level: 20] +[lambdarank_norm: 1] +[label_gain: ] +[lambdarank_position_bias_regularization: 0] +[eval_at: 1] +[multi_error_top_k: 1] +[auc_mu_weights: ] +[num_machines: 1] +[local_listen_port: 12400] +[time_out: 120] +[machine_list_filename: ] +[machines: ] +[gpu_platform_id: -1] +[gpu_device_id: -1] +[gpu_device_id_list: ] +[gpu_use_dp: 0] +[num_gpu: 1] + +end of parameters + +pandas_categorical:[]