10221043 1 Jan van Rijn 14967 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) 8146475 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": [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]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [0, 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 0.04439226704471478 9667 loss "deviance" 9667 max_depth 30 9667 max_features 0.275173174310007 9667 max_leaf_nodes null 9667 min_impurity_decrease 0.09741712240446332 9667 min_impurity_split null 9667 min_samples_leaf 7 9667 min_samples_split 11 9667 min_weight_fraction_leaf 0.3741118867093155 9667 n_estimators 278 9667 n_iter_no_change 1819 9667 presort "auto" 9667 random_state 23372 9667 subsample 0.6485633797324869 9667 tol 0.002257981555704155 9667 validation_fraction 0.8473478323751332 9667 verbose 0 9667 warm_start false 9667 openml-python Sklearn_0.20.3. 23380 cjs https://www.openml.org/data/download/1910442/phpDAC5gS -1 21363002 description https://api.openml.org/data/download/21363002/description.xml -1 21363003 predictions https://api.openml.org/data/download/21363003/predictions.arff area_under_roc_curve 0.6344048450032261 [0.62141,0.608908,0.624101,0.502872,0.749933,0.789774] average_cost 0 f_measure 0.19792443011201882 [0.060976,0.064516,0.434035,0.010791,0.232558,0.362545] kappa 0.10660427128345426 kb_relative_information_score 379.1498677790329 mean_absolute_error 0.2604143241284335 mean_prior_absolute_error 0.27287997162595995 number_of_instances 2796 [576,341,680,511,414,274] precision 0.22520541259951493 [0.25,0.209677,0.306618,0.066667,0.235732,0.270125] predictive_accuracy 0.2814735336194564 prior_entropy 2.5206634795042744 recall 0.2814735336194564 [0.034722,0.038123,0.742647,0.005871,0.229469,0.551095] relative_absolute_error 0.9543182028961317 root_mean_prior_squared_error 0.3693707377543301 root_mean_squared_error 0.3612965290977436 root_relative_squared_error 0.9781406380330089 total_cost 0 area_under_roc_curve 0.6426354250949771 [0.640805,0.607604,0.66284,0.464381,0.733136,0.832058] area_under_roc_curve 0.6200316445244896 [0.603604,0.634326,0.569575,0.481334,0.737167,0.840349] area_under_roc_curve 0.6478145824993162 [0.721536,0.54627,0.605855,0.500771,0.785284,0.786848] area_under_roc_curve 0.622811376664521 [0.61269,0.472143,0.594686,0.568114,0.767782,0.782384] area_under_roc_curve 0.6146123959897337 [0.601041,0.685856,0.58109,0.490806,0.686601,0.767604] area_under_roc_curve 0.6446733587928268 [0.592847,0.677668,0.659267,0.501627,0.754261,0.780266] area_under_roc_curve 0.6498540445160081 [0.571914,0.523709,0.74662,0.539345,0.800934,0.703263] area_under_roc_curve 0.6447720886167161 [0.652323,0.605042,0.642354,0.479317,0.742214,0.845899] area_under_roc_curve 0.6414883299555763 [0.598743,0.659784,0.626812,0.514577,0.788075,0.757349] area_under_roc_curve 0.6509000426978427 [0.621701,0.669928,0.662845,0.456828,0.778983,0.825838] 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 f_measure 0.21838402226423892 [0.186047,0,0.447489,0.036364,0.164384,0.404762] f_measure 0.20056282868762854 [0.153846,0.1,0.373206,0,0.16092,0.423529] f_measure 0.19695104988807755 [0.105263,0,0.439462,0,0.222222,0.372093] f_measure 0.18421597070908635 [0,0.042553,0.422907,0.070175,0.225,0.302326] kappa 0.1172090370417314 kappa 0.08219868885526975 kappa 0.07734228953455212 kappa 0.11524659404871544 kappa 0.07552436398436879 kappa 0.10516240289841317 kappa 0.1469656193767218 kappa 0.13397236920404657 kappa 0.08574064647493003 kappa 0.12643106022896963 kb_relative_information_score 38.091382945867764 kb_relative_information_score 36.20613873089532 kb_relative_information_score 39.59110600915982 kb_relative_information_score 38.785580466527776 kb_relative_information_score 35.868935036660645 kb_relative_information_score 40.238440335026176 kb_relative_information_score 38.4025718413981 kb_relative_information_score 38.71393992577926 kb_relative_information_score 34.916211800296075 kb_relative_information_score 38.33556068742232 mean_absolute_error 0.25959340407584924 mean_absolute_error 0.26211662013613884 mean_absolute_error 0.2590361873432007 mean_absolute_error 0.25978186321509017 mean_absolute_error 0.26198991529206206 mean_absolute_error 0.2589601705233237 mean_absolute_error 0.260210541438016 mean_absolute_error 0.26006013278145895 mean_absolute_error 0.26206921217156426 mean_absolute_error 0.26032880643731776 mean_prior_absolute_error 0.272904982835389 mean_prior_absolute_error 0.272904982835389 mean_prior_absolute_error 0.272904982835389 mean_prior_absolute_error 0.272904982835389 mean_prior_absolute_error 0.272804289453111 mean_prior_absolute_error 0.27287651677373237 mean_prior_absolute_error 0.2728747259382053 mean_prior_absolute_error 0.2728747259382053 mean_prior_absolute_error 0.2728747259382053 mean_prior_absolute_error 0.2728747259382053 number_of_instances 280 [58,34,68,51,41,28] number_of_instances 280 [58,34,68,51,41,28] number_of_instances 280 [58,34,68,51,41,28] number_of_instances 280 [58,34,68,51,41,28] number_of_instances 280 [58,34,68,52,41,27] number_of_instances 280 [58,35,68,51,41,27] number_of_instances 279 [57,34,68,51,42,27] number_of_instances 279 [57,34,68,51,42,27] number_of_instances 279 [57,34,68,51,42,27] number_of_instances 279 [57,34,68,51,42,27] precision 0.24133983477496956 [0.285714,0,0.324503,0.25,0.1875,0.303571] precision 0.2236538559627561 [0.3,0.333333,0.276596,0,0.152174,0.315789] precision 0.18190248921693702 [0.222222,0,0.316129,0,0.225,0.271186] precision 0.20086095865807377 [0,0.076923,0.301887,0.333333,0.236842,0.220339] predictive_accuracy 0.28928571428571426 predictive_accuracy 0.2571428571428572 predictive_accuracy 0.2571428571428572 predictive_accuracy 0.28928571428571426 predictive_accuracy 0.26071428571428573 predictive_accuracy 0.2785714285714286 predictive_accuracy 0.3118279569892473 predictive_accuracy 0.3082437275985663 predictive_accuracy 0.2616487455197133 predictive_accuracy 0.3010752688172043 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 recall 0.2892857142857143 [0.137931,0,0.720588,0.019608,0.146341,0.607143] recall 0.2571428571428571 [0.103448,0.058824,0.573529,0,0.170732,0.642857] recall 0.2571428571428571 [0,0.029412,0.720588,0,0.146341,0.571429] recall 0.2892857142857143 [0,0.029412,0.75,0,0.243902,0.678571] recall 0.26071428571428573 [0,0,0.705882,0,0.243902,0.555556] recall 0.2785714285714286 [0.068966,0,0.720588,0,0.219512,0.592593] recall 0.3118279569892473 [0.035088,0.205882,0.852941,0,0.261905,0.333333] recall 0.30824372759856633 [0,0.029412,0.823529,0,0.380952,0.481481] recall 0.2616487455197133 [0,0.029412,0.705882,0.039216,0.214286,0.481481] recall 0.3010752688172043 [0,0,0.852941,0,0.261905,0.555556] relative_absolute_error 0.9512226613774618 relative_absolute_error 0.9604684290218422 relative_absolute_error 0.949180863800667 relative_absolute_error 0.9519132282453984 relative_absolute_error 0.9603584892938141 relative_absolute_error 0.9490013050043877 relative_absolute_error 0.9535897490812058 relative_absolute_error 0.9530385486868128 relative_absolute_error 0.9604011924171827 relative_absolute_error 0.9540231530870007 root_mean_prior_squared_error 0.36940459271455434 root_mean_prior_squared_error 0.36940459271455434 root_mean_prior_squared_error 0.36940459271455434 root_mean_prior_squared_error 0.36940459271455434 root_mean_prior_squared_error 0.36926827610333357 root_mean_prior_squared_error 0.36936606105183667 root_mean_prior_squared_error 0.3693636368423697 root_mean_prior_squared_error 0.3693636368423697 root_mean_prior_squared_error 0.3693636368423697 root_mean_prior_squared_error 0.3693636368423697 root_mean_squared_error 0.3606772413857771 root_mean_squared_error 0.3637734987786459 root_mean_squared_error 0.3605116632391289 root_mean_squared_error 0.36157892918562734 root_mean_squared_error 0.36500318437077345 root_mean_squared_error 0.3608045565412257 root_mean_squared_error 0.3604146125848585 root_mean_squared_error 0.3594759309288738 root_mean_squared_error 0.3615977273557381 root_mean_squared_error 0.3590694758491397 root_relative_squared_error 0.9763745456854105 root_relative_squared_error 0.9847562968978578 root_relative_squared_error 0.9759263158855821 root_relative_squared_error 0.978815467692428 root_relative_squared_error 0.9884498831647087 root_relative_squared_error 0.976821085060629 root_relative_squared_error 0.9757717778230284 root_relative_squared_error 0.9732304295083719 root_relative_squared_error 0.9789748943533771 root_relative_squared_error 0.9721300096532696 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 1330.1142759955837 usercpu_time_millis 1245.3050450021692 usercpu_time_millis 1229.9447910008894 usercpu_time_millis 1242.5128659997426 usercpu_time_millis 1230.5501789996924 usercpu_time_millis 1221.9932890002383 usercpu_time_millis 1220.5955919998814 usercpu_time_millis 1222.6927449992218 usercpu_time_millis 1213.8482080044923 usercpu_time_millis 1222.1700130030513 usercpu_time_millis_testing 4.04184499711846 usercpu_time_millis_testing 4.005246999440715 usercpu_time_millis_testing 3.9769880022504367 usercpu_time_millis_testing 4.182587999821408 usercpu_time_millis_testing 4.0014400001382455 usercpu_time_millis_testing 3.9828709996072575 usercpu_time_millis_testing 3.9785240005585365 usercpu_time_millis_testing 3.857818999676965 usercpu_time_millis_testing 3.959094003221253 usercpu_time_millis_testing 3.870026001095539 usercpu_time_millis_training 1326.0724309984653 usercpu_time_millis_training 1241.2997980027285 usercpu_time_millis_training 1225.967802998639 usercpu_time_millis_training 1238.3302779999212 usercpu_time_millis_training 1226.5487389995542 usercpu_time_millis_training 1218.010418000631 usercpu_time_millis_training 1216.617067999323 usercpu_time_millis_training 1218.8349259995448 usercpu_time_millis_training 1209.889114001271 usercpu_time_millis_training 1218.2999870019557