10226858 1 Jan van Rijn 9986 Supervised Classification 9666 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(4) 8152290 copy true 9559 fill_value -1 9559 missing_values NaN 9559 strategy "constant" 9559 verbose 0 9559 n_jobs null 9606 remainder "passthrough" 9606 sparse_threshold 0.3 9606 transformer_weights null 9606 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": []}}] 9606 memory null 9607 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 9607 axis 0 9608 copy true 9608 missing_values "NaN" 9608 strategy "mean" 9608 verbose 0 9608 copy true 9609 with_mean true 9609 with_std true 9609 memory null 9610 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}] 9610 categorical_features null 9611 categories null 9611 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 9611 handle_unknown "ignore" 9611 n_values null 9611 sparse true 9611 threshold 0.0 9612 memory null 9666 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variancethreshold", "step_name": "variancethreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}] 9666 criterion "friedman_mse" 9667 init null 9667 learning_rate 5.7628210394723986e-05 9667 loss "deviance" 9667 max_depth 29 9667 max_features 0.5691122441394714 9667 max_leaf_nodes null 9667 min_impurity_decrease 0.1832354334864591 9667 min_impurity_split null 9667 min_samples_leaf 9 9667 min_samples_split 3 9667 min_weight_fraction_leaf 0.37541685461536806 9667 n_estimators 323 9667 n_iter_no_change 605 9667 presort "auto" 9667 random_state 7259 9667 subsample 0.32784182464756917 9667 tol 3.1731579887429746e-05 9667 validation_fraction 0.807586311029996 9667 verbose 0 9667 warm_start false 9667 openml-python Sklearn_0.20.3. 1476 gas-drift https://www.openml.org/data/download/1588715/phpbL6t4U -1 21374632 description https://api.openml.org/data/download/21374632/description.xml -1 21374633 predictions https://api.openml.org/data/download/21374633/predictions.arff area_under_roc_curve 0.8763009589506103 [0.883857,0.89108,0.867193,0.808136,0.90611,0.873352] average_cost 0 kappa 0.282988637025062 kb_relative_information_score 522.2754663881271 mean_absolute_error 0.27607029286371754 mean_prior_absolute_error 0.27476832857057837 number_of_instances 13910 [2565,2926,1641,1936,3009,1833] predictive_accuracy 0.4351545650611071 prior_entropy 2.5457299651568843 recall 0.4351545650611071 [0.196881,0.936774,0,0,0.932868,0] relative_absolute_error 1.0047384074427805 root_mean_prior_squared_error 0.37065282342196226 root_mean_squared_error 0.3704644434968128 root_relative_squared_error 0.9994917617963617 total_cost 0 area_under_roc_curve 0.8872628880697472 [0.897958,0.895493,0.871186,0.827878,0.920865,0.880914] area_under_roc_curve 0.8803581606646588 [0.87789,0.909465,0.851387,0.832793,0.911319,0.862681] area_under_roc_curve 0.876584060943149 [0.889328,0.904152,0.85629,0.76083,0.916787,0.888774] area_under_roc_curve 0.8761020649853125 [0.882095,0.884579,0.872657,0.811917,0.907184,0.87377] area_under_roc_curve 0.8789089181362778 [0.907224,0.902747,0.854078,0.791272,0.895975,0.888218] area_under_roc_curve 0.8699245034580443 [0.868072,0.86663,0.882082,0.81799,0.908144,0.859088] area_under_roc_curve 0.8833689457038255 [0.895731,0.890218,0.869931,0.845152,0.899758,0.880711] area_under_roc_curve 0.8774297193897133 [0.873838,0.885938,0.872441,0.81293,0.915153,0.879632] area_under_roc_curve 0.8738329234960276 [0.886523,0.886422,0.884459,0.805872,0.895052,0.863546] area_under_roc_curve 0.8706793698206334 [0.881898,0.901307,0.856515,0.775719,0.903153,0.866258] average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 kappa 0.30885657425882757 kappa 0.28824693628938247 kappa 0.2967519578547302 kappa 0.27779484372189867 kappa 0.27794982245383176 kappa 0.2640970083958157 kappa 0.2732726346685989 kappa 0.2788456174821646 kappa 0.2695128619695713 kappa 0.2944555631136293 kb_relative_information_score 52.37565464314052 kb_relative_information_score 52.19909427836919 kb_relative_information_score 52.10758522114225 kb_relative_information_score 52.13235284803874 kb_relative_information_score 52.19298972972798 kb_relative_information_score 52.16769804980917 kb_relative_information_score 52.38000772975729 kb_relative_information_score 52.28472542362233 kb_relative_information_score 52.168416112073594 kb_relative_information_score 52.26694235244188 mean_absolute_error 0.27603914033809523 mean_absolute_error 0.27607173788397965 mean_absolute_error 0.2760662301051522 mean_absolute_error 0.2760756169104842 mean_absolute_error 0.27606767846036234 mean_absolute_error 0.2760929985955715 mean_absolute_error 0.27605220352217524 mean_absolute_error 0.2760641488396676 mean_absolute_error 0.2760828127588108 mean_absolute_error 0.27609036122287706 mean_prior_absolute_error 0.27477202746106094 mean_prior_absolute_error 0.27477202746106094 mean_prior_absolute_error 0.27477202746106094 mean_prior_absolute_error 0.2747532058256237 mean_prior_absolute_error 0.27476403730658433 mean_prior_absolute_error 0.27476403730658433 mean_prior_absolute_error 0.27476403730658433 mean_prior_absolute_error 0.27476403730658433 mean_prior_absolute_error 0.27476403730658433 mean_prior_absolute_error 0.2747938109641058 number_of_instances 1391 [257,292,164,193,301,184] number_of_instances 1391 [257,292,164,193,301,184] number_of_instances 1391 [257,292,164,193,301,184] number_of_instances 1391 [257,293,164,193,301,183] number_of_instances 1391 [256,293,164,194,301,183] number_of_instances 1391 [256,293,164,194,301,183] number_of_instances 1391 [256,293,164,194,301,183] number_of_instances 1391 [256,293,164,194,301,183] number_of_instances 1391 [256,293,164,194,301,183] number_of_instances 1391 [257,292,165,194,300,183] predictive_accuracy 0.45506829618979155 predictive_accuracy 0.4392523364485982 predictive_accuracy 0.44572250179726813 predictive_accuracy 0.43134435657800146 predictive_accuracy 0.43134435657800146 predictive_accuracy 0.4205607476635514 predictive_accuracy 0.4277498202731847 predictive_accuracy 0.43206326383896476 predictive_accuracy 0.4248741912293314 predictive_accuracy 0.4435657800143782 prior_entropy 2.5457299651568843 prior_entropy 2.5457299651568843 prior_entropy 2.5457299651568843 prior_entropy 2.5457299651568843 prior_entropy 2.5457299651568843 prior_entropy 2.5457299651568843 prior_entropy 2.5457299651568843 prior_entropy 2.5457299651568843 prior_entropy 2.5457299651568843 prior_entropy 2.5457299651568843 recall 0.4550682961897915 [0.287938,0.94863,0,0,0.936877,0] recall 0.4392523364485981 [0.18677,0.955479,0,0,0.943522,0] recall 0.44572250179726813 [0.241245,0.945205,0,0,0.936877,0] recall 0.43134435657800146 [0.171206,0.921502,0,0,0.950166,0] recall 0.43134435657800146 [0.195312,0.938567,0,0,0.913621,0] recall 0.4205607476635514 [0.152344,0.897611,0,0,0.940199,0] recall 0.42774982027318476 [0.164062,0.94198,0,0,0.920266,0] recall 0.43206326383896476 [0.183594,0.928328,0,0,0.936877,0] recall 0.4248741912293314 [0.144531,0.945392,0,0,0.920266,0] recall 0.44356578001437813 [0.241245,0.945205,0,0,0.93,0] relative_absolute_error 1.0046115060864915 relative_absolute_error 1.0047301409642322 relative_absolute_error 1.004710096060541 relative_absolute_error 1.0048130870061616 relative_absolute_error 1.0047445843588454 relative_absolute_error 1.0048367366487059 relative_absolute_error 1.0046882635304764 relative_absolute_error 1.0047317383520342 relative_absolute_error 1.0047996654334896 relative_absolute_error 1.0047182658671325 root_mean_prior_squared_error 0.3706578130852553 root_mean_prior_squared_error 0.3706578130852553 root_mean_prior_squared_error 0.3706578130852553 root_mean_prior_squared_error 0.37063242271245894 root_mean_prior_squared_error 0.37064703458501796 root_mean_prior_squared_error 0.37064703458501796 root_mean_prior_squared_error 0.37064703458501796 root_mean_prior_squared_error 0.37064703458501796 root_mean_prior_squared_error 0.37064703458501796 root_mean_prior_squared_error 0.37068719684417073 root_mean_squared_error 0.37042264130035396 root_mean_squared_error 0.37046637821856293 root_mean_squared_error 0.3704586042639538 root_mean_squared_error 0.37047120297742225 root_mean_squared_error 0.37046100773398055 root_mean_squared_error 0.370494708278399 root_mean_squared_error 0.3704408584217003 root_mean_squared_error 0.3704565425331339 root_mean_squared_error 0.37048136956401473 root_mean_squared_error 0.37049111577147226 root_relative_squared_error 0.999365528591064 root_relative_squared_error 0.9994835266924528 root_relative_squared_error 0.9994625532923659 root_relative_squared_error 0.9995650144856275 root_relative_squared_error 0.999498102416371 root_relative_squared_error 0.9995890259670105 root_relative_squared_error 0.9994437398816681 root_relative_squared_error 0.9994860553731469 root_relative_squared_error 0.9995530383207065 root_relative_squared_error 0.9994710335982256 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 usercpu_time_millis 7734.094729996286 usercpu_time_millis 7716.803719995369 usercpu_time_millis 7682.285893999506 usercpu_time_millis 7721.636617992772 usercpu_time_millis 7717.86762499687 usercpu_time_millis 7721.693897001387 usercpu_time_millis 7678.692271991167 usercpu_time_millis 7675.516809002147 usercpu_time_millis 7737.328156996227 usercpu_time_millis 7739.247351993981 usercpu_time_millis_testing 26.14527099649422 usercpu_time_millis_testing 26.754456994240172 usercpu_time_millis_testing 26.59539099840913 usercpu_time_millis_testing 26.75098699546652 usercpu_time_millis_testing 26.466205999895465 usercpu_time_millis_testing 26.75899500172818 usercpu_time_millis_testing 26.607016996422317 usercpu_time_millis_testing 27.233681998040993 usercpu_time_millis_testing 26.706669996201526 usercpu_time_millis_testing 26.908690997515805 usercpu_time_millis_training 7707.949458999792 usercpu_time_millis_training 7690.049263001129 usercpu_time_millis_training 7655.690503001097 usercpu_time_millis_training 7694.885630997305 usercpu_time_millis_training 7691.401418996975 usercpu_time_millis_training 7694.934901999659 usercpu_time_millis_training 7652.085254994745 usercpu_time_millis_training 7648.283127004106 usercpu_time_millis_training 7710.621487000026 usercpu_time_millis_training 7712.3386609964655