10161742 1 Jan van Rijn 14 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) 8087204 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]}}, {"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 "mae" 9667 init null 9667 learning_rate 0.022238860929305812 9667 loss "deviance" 9667 max_depth 11 9667 max_features 0.48246499665040055 9667 max_leaf_nodes null 9667 min_impurity_decrease 0.0925376158119835 9667 min_impurity_split null 9667 min_samples_leaf 2 9667 min_samples_split 18 9667 min_weight_fraction_leaf 0.05333524231344128 9667 n_estimators 134 9667 n_iter_no_change 865 9667 presort "auto" 9667 random_state 25781 9667 subsample 0.776562418054716 9667 tol 0.0002860413784426976 9667 validation_fraction 0.9479418219452574 9667 verbose 0 9667 warm_start false 9667 openml-python Sklearn_0.20.3. 14 mfeat-fourier https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff -1 21244400 description https://api.openml.org/data/download/21244400/description.xml -1 21244401 predictions https://api.openml.org/data/download/21244401/predictions.arff area_under_roc_curve 0.5536780555555555 [0.973515,0.636572,0.666497,0.326486,0.515249,0.141535,0.533318,0.655974,0.469314,0.618321] average_cost 0 kappa 0.10055555555555555 kb_relative_information_score 111.33453112103577 mean_absolute_error 0.17762178821556251 mean_prior_absolute_error 0.18000000000000554 number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] predictive_accuracy 0.1905 prior_entropy 3.321928094887362 recall 0.1905 [0.945,0.705,0,0.01,0.21,0,0,0,0,0.035] relative_absolute_error 0.9867877123086503 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.2982288055836853 root_relative_squared_error 0.9940960186122691 total_cost 0 area_under_roc_curve 0.5636944444444445 [0.972639,0.626944,0.675,0.375278,0.498333,0.031111,0.503889,0.675,0.675,0.60375] area_under_roc_curve 0.5615833333333333 [0.972639,0.564583,0.655556,0.386944,0.459861,0.172222,0.514861,0.655556,0.610278,0.623333] area_under_roc_curve 0.5634444444444445 [0.977917,0.56,0.738889,0.335,0.523472,0.076528,0.453194,0.673472,0.692222,0.60375] area_under_roc_curve 0.5561944444444444 [0.997083,0.663333,0.7425,0.273611,0.466528,0.082361,0.53125,0.780556,0.425556,0.599167] area_under_roc_curve 0.5587222222222223 [0.995556,0.619861,0.737639,0.337083,0.482361,0.095833,0.524444,0.737639,0.444722,0.612083] area_under_roc_curve 0.5578611111111111 [0.979306,0.682778,0.758333,0.255972,0.542083,0.150417,0.481944,0.739444,0.386944,0.601389] area_under_roc_curve 0.55475 [0.911806,0.6825,0.722222,0.239028,0.535833,0.191806,0.54625,0.722222,0.402778,0.593056] area_under_roc_curve 0.5775277777777778 [0.98875,0.604028,0.694444,0.295556,0.576667,0.204722,0.596806,0.694444,0.493889,0.625972] area_under_roc_curve 0.5411944444444444 [0.964722,0.628472,0.708333,0.313194,0.491667,0.224028,0.630556,0.4225,0.375833,0.652639] area_under_roc_curve 0.5589722222222222 [0.996667,0.573889,0.381528,0.423056,0.610278,0.220278,0.701667,0.448194,0.511667,0.7225] 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 0.09444444444444443 kappa 0.08333333333333331 kappa 0.10555555555555556 kappa 0.11666666666666664 kappa 0.10555555555555556 kappa 0.11666666666666664 kappa 0.10555555555555556 kappa 0.11111111111111112 kappa 0.07777777777777778 kappa 0.08888888888888888 kb_relative_information_score 11.2389433452339 kb_relative_information_score 11.606245497593129 kb_relative_information_score 11.762377086018317 kb_relative_information_score 11.449677533941506 kb_relative_information_score 10.617507755741743 kb_relative_information_score 10.951952804718251 kb_relative_information_score 10.35493142477356 kb_relative_information_score 11.846244660487264 kb_relative_information_score 10.134484139204918 kb_relative_information_score 11.37216687332251 mean_absolute_error 0.17807889228996587 mean_absolute_error 0.17778229495432982 mean_absolute_error 0.17749030526996223 mean_absolute_error 0.17761740393892997 mean_absolute_error 0.17780100267493748 mean_absolute_error 0.17750629129053308 mean_absolute_error 0.1778054613965132 mean_absolute_error 0.17697419471910827 mean_absolute_error 0.17786275821702674 mean_absolute_error 0.1772992774043227 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] predictive_accuracy 0.185 predictive_accuracy 0.175 predictive_accuracy 0.195 predictive_accuracy 0.205 predictive_accuracy 0.195 predictive_accuracy 0.205 predictive_accuracy 0.195 predictive_accuracy 0.2 predictive_accuracy 0.17 predictive_accuracy 0.18 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 recall 0.185 [0.9,0,0,0,0.95,0,0,0,0,0] recall 0.175 [0.95,0,0,0,0.8,0,0,0,0,0] recall 0.195 [0.95,0.95,0,0,0.05,0,0,0,0,0] recall 0.205 [0.95,0.95,0,0,0.05,0,0,0,0,0.1] recall 0.195 [0.95,0.9,0,0,0.05,0,0,0,0,0.05] recall 0.205 [0.95,1,0,0,0.05,0,0,0,0,0.05] recall 0.195 [0.9,0.95,0,0,0,0,0,0,0,0.1] recall 0.2 [1,0.85,0,0,0.1,0,0,0,0,0.05] recall 0.17 [0.9,0.8,0,0,0,0,0,0,0,0] recall 0.18 [1,0.65,0,0.1,0.05,0,0,0,0,0] relative_absolute_error 0.9893271793887004 relative_absolute_error 0.9876794164129445 relative_absolute_error 0.9860572514997912 relative_absolute_error 0.9867633552162787 relative_absolute_error 0.9877833481940982 relative_absolute_error 0.9861460627251849 relative_absolute_error 0.9878081188695189 relative_absolute_error 0.9831899706617138 relative_absolute_error 0.9881264345390386 relative_absolute_error 0.9849959855795717 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_squared_error 0.2990431873106697 root_mean_squared_error 0.2989294348219163 root_mean_squared_error 0.2978334806952036 root_mean_squared_error 0.29826956797765425 root_mean_squared_error 0.29919889532375704 root_mean_squared_error 0.2980085823617941 root_mean_squared_error 0.2983128506001785 root_mean_squared_error 0.29684889290903393 root_mean_squared_error 0.2983064553048073 root_mean_squared_error 0.2975288138297881 root_relative_squared_error 0.9968106243688996 root_relative_squared_error 0.9964314494063882 root_relative_squared_error 0.9927782689840126 root_relative_squared_error 0.9942318932588481 root_relative_squared_error 0.9973296510791907 root_relative_squared_error 0.993361941205981 root_relative_squared_error 0.9943761686672622 root_relative_squared_error 0.9894963096967803 root_relative_squared_error 0.9943548510160249 root_relative_squared_error 0.9917627127659608 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 2201.7754839999993 usercpu_time_millis 2149.694448 usercpu_time_millis 2180.873972999998 usercpu_time_millis 2203.129064 usercpu_time_millis 2256.134386999999 usercpu_time_millis 2224.4490450000003 usercpu_time_millis 2215.5637750000033 usercpu_time_millis 2168.7190250000017 usercpu_time_millis 2250.569648999999 usercpu_time_millis 2261.0007220000025 usercpu_time_millis_testing 3.812964999999835 usercpu_time_millis_testing 2.1152009999996224 usercpu_time_millis_testing 3.3699399999989055 usercpu_time_millis_testing 2.2029050000007544 usercpu_time_millis_testing 3.9282529999997706 usercpu_time_millis_testing 2.22976200000069 usercpu_time_millis_testing 2.5055360000010296 usercpu_time_millis_testing 2.2102090000011287 usercpu_time_millis_testing 3.6847120000018663 usercpu_time_millis_testing 2.19179800000191 usercpu_time_millis_training 2197.9625189999997 usercpu_time_millis_training 2147.5792470000006 usercpu_time_millis_training 2177.5040329999993 usercpu_time_millis_training 2200.9261589999996 usercpu_time_millis_training 2252.2061339999996 usercpu_time_millis_training 2222.2192829999995 usercpu_time_millis_training 2213.0582390000022 usercpu_time_millis_training 2166.5088160000005 usercpu_time_millis_training 2246.884936999997 usercpu_time_millis_training 2258.8089240000004