10444956 8323 Heinrich Peters 125920 Supervised Classification 17651 sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1) 8263646 add_indicator false 12737 copy true 12737 fill_value null 12737 missing_values NaN 12737 strategy "most_frequent" 12737 verbose 0 12737 copy true 13294 with_mean true 13294 with_std true 13294 categorical_features null 16348 categories null 16348 drop null 16348 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 16348 handle_unknown "ignore" 16348 n_values null 16348 sparse true 16348 n_jobs null 16375 remainder "drop" 16375 sparse_threshold 0.3 16375 transformer_weights null 16375 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "num", "step_name": "num", "argument_1": [false, false, true, false, false, false, false, false, false, false, false, false]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [true, true, false, true, true, true, true, true, true, true, true, true]}}] 16375 verbose false 16375 memory null 16376 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 16376 verbose false 16376 memory null 16377 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}] 16377 verbose false 16377 bootstrap false 17650 class_weight null 17650 criterion "entropy" 17650 max_depth null 17650 max_features 0.8505427867970985 17650 max_leaf_nodes null 17650 min_impurity_decrease 0 17650 min_impurity_split null 17650 min_samples_leaf 1 17650 min_samples_split 2 17650 min_weight_fraction_leaf 0.0 17650 n_estimators 300 17650 n_jobs 1 17650 oob_score false 17650 random_state 1 17650 verbose 0 17650 warm_start false 17650 memory null 17651 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "randomforestclassifier", "step_name": "randomforestclassifier"}}] 17651 verbose false 17651 openml-python Sklearn_0.21.2. 23381 dresses-sales https://www.openml.org/data/download/1910507/phpcFPMhq -1 21814341 description https://api.openml.org/data/download/21814341/description.xml -1 21814342 predictions https://api.openml.org/data/download/21814342/predictions.arff area_under_roc_curve 0.5579392446633826 [0.557939,0.557939] average_cost 0 f_measure 0.5356872030122165 [0.601375,0.444976] kappa 0.046366326866162495 kb_relative_information_score 0.05421639354153825 mean_absolute_error 0.45566333333333353 mean_prior_absolute_error 0.4872509960159361 weighted_recall 0.536 [0.603448,0.442857] number_of_instances 500 [290,210] precision 0.5353912012644889 [0.599315,0.447115] predictive_accuracy 0.536 prior_entropy 0.9814541958069474 relative_absolute_error 0.935171681657128 root_mean_prior_squared_error 0.4935586100816085 root_mean_squared_error 0.5699717585596286 root_relative_squared_error 1.15482081948765 total_cost 0 unweighted_recall 0.5231527093596059 [0.603448,0.442857] area_under_roc_curve 0.45320197044334976 [0.453202,0.453202] area_under_roc_curve 0.6009852216748769 [0.600985,0.600985] area_under_roc_curve 0.5853858784893268 [0.585386,0.585386] area_under_roc_curve 0.43185550082101815 [0.431856,0.431856] area_under_roc_curve 0.5213464696223317 [0.521346,0.521346] area_under_roc_curve 0.4688013136288998 [0.468801,0.468801] area_under_roc_curve 0.6789819376026273 [0.678982,0.678982] area_under_roc_curve 0.6863711001642037 [0.686371,0.686371] area_under_roc_curve 0.5246305418719212 [0.524631,0.524631] area_under_roc_curve 0.5673234811165845 [0.567323,0.567323] 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 0.52 [0.586207,0.428571] f_measure 0.52 [0.586207,0.428571] f_measure 0.5811995104039168 [0.631579,0.511628] f_measure 0.3950000000000001 [0.5,0.25] f_measure 0.44272727272727275 [0.5,0.363636] f_measure 0.5509362279511534 [0.686567,0.363636] f_measure 0.6210852713178293 [0.666667,0.55814] f_measure 0.62228823765556 [0.641509,0.595745] f_measure 0.5030303030303029 [0.545455,0.444444] f_measure 0.5741740226986128 [0.655738,0.461538] kappa 0.014778325123152677 kappa 0.014778325123152677 kappa 0.14355628058727551 kappa -0.2479201331114808 kappa -0.13452188006482974 kappa 0.08376963350785338 kappa 0.22512234910277315 kappa 0.2448330683624801 kappa -0.006441223832528141 kappa 0.12060301507537685 kb_relative_information_score -0.0345208744753934 kb_relative_information_score 0.09858718010089319 kb_relative_information_score 0.09636590030993952 kb_relative_information_score -0.10849433667638315 kb_relative_information_score -0.01965872312952395 kb_relative_information_score 0.07499403741017746 kb_relative_information_score 0.17153911148563686 kb_relative_information_score 0.19617471630346398 kb_relative_information_score -0.026887542680949384 kb_relative_information_score 0.09406446676751981 mean_absolute_error 0.5033666666666666 mean_absolute_error 0.43000000000000016 mean_absolute_error 0.4364666666666666 mean_absolute_error 0.5260333333333336 mean_absolute_error 0.48419999999999985 mean_absolute_error 0.4527999999999999 mean_absolute_error 0.4001333333333335 mean_absolute_error 0.3900666666666666 mean_absolute_error 0.49176666666666663 mean_absolute_error 0.4417999999999999 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 mean_prior_absolute_error 0.48725099601593624 number_of_instances 50 [29,21] number_of_instances 50 [29,21] number_of_instances 50 [29,21] number_of_instances 50 [29,21] number_of_instances 50 [29,21] number_of_instances 50 [29,21] number_of_instances 50 [29,21] number_of_instances 50 [29,21] number_of_instances 50 [29,21] number_of_instances 50 [29,21] precision 0.52 [0.586207,0.428571] precision 0.52 [0.586207,0.428571] precision 0.582857142857143 [0.642857,0.5] precision 0.39117147707979627 [0.483871,0.263158] precision 0.44682769726247984 [0.518519,0.347826] precision 0.5610526315789474 [0.605263,0.5] precision 0.6226623376623377 [0.678571,0.545455] precision 0.6369871794871795 [0.708333,0.538462] precision 0.5096153846153846 [0.576923,0.416667] precision 0.5725 [0.625,0.5] predictive_accuracy 0.52 predictive_accuracy 0.52 predictive_accuracy 0.58 predictive_accuracy 0.4 predictive_accuracy 0.44 predictive_accuracy 0.58 predictive_accuracy 0.62 predictive_accuracy 0.62 predictive_accuracy 0.5 predictive_accuracy 0.58 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 prior_entropy 0.9814541958069504 relative_absolute_error 1.0330746797492505 relative_absolute_error 0.8825020441537207 relative_absolute_error 0.8957737803216135 relative_absolute_error 1.0795941673480518 relative_absolute_error 0.9937383483237937 relative_absolute_error 0.9292951757972199 relative_absolute_error 0.8212057781411832 relative_absolute_error 0.8005456527664212 relative_absolute_error 1.0092676478604523 relative_absolute_error 0.9067195421095665 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_prior_squared_error 0.49355861008160823 root_mean_squared_error 0.6229154124848021 root_mean_squared_error 0.5261747702891967 root_mean_squared_error 0.5670675052897631 root_mean_squared_error 0.618424835996888 root_mean_squared_error 0.5957324156961001 root_mean_squared_error 0.576926434748063 root_mean_squared_error 0.5104133401252144 root_mean_squared_error 0.507499425287031 root_mean_squared_error 0.5995872191210662 root_mean_squared_error 0.560763963020291 root_relative_squared_error 1.2620900532599464 root_relative_squared_error 1.066083661679401 root_relative_squared_error 1.1489365066410258 root_relative_squared_error 1.2529916880482213 root_relative_squared_error 1.2070145338921305 root_relative_squared_error 1.168911701596433 root_relative_squared_error 1.034149399279691 root_relative_squared_error 1.0282455111118771 root_relative_squared_error 1.2148247581415437 root_relative_squared_error 1.13616488815294 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 unweighted_recall 0.5073891625615763 [0.586207,0.428571] unweighted_recall 0.5073891625615763 [0.586207,0.428571] unweighted_recall 0.5722495894909688 [0.62069,0.52381] unweighted_recall 0.37766830870279144 [0.517241,0.238095] unweighted_recall 0.4318555008210181 [0.482759,0.380952] unweighted_recall 0.5394088669950738 [0.793103,0.285714] unweighted_recall 0.6133004926108374 [0.655172,0.571429] unweighted_recall 0.6264367816091954 [0.586207,0.666667] unweighted_recall 0.4967159277504105 [0.517241,0.47619] unweighted_recall 0.5591133004926109 [0.689655,0.428571] usercpu_time_millis 1829.579958000977 usercpu_time_millis 1883.2098040002165 usercpu_time_millis 1888.372288998653 usercpu_time_millis 1883.760587003053 usercpu_time_millis 1817.168244997447 usercpu_time_millis 1992.1012220002012 usercpu_time_millis 1921.577254001022 usercpu_time_millis 1954.74204799757 usercpu_time_millis 1903.9989299999434 usercpu_time_millis 1910.402730001806 usercpu_time_millis_testing 29.56993599946145 usercpu_time_millis_testing 30.289545000414364 usercpu_time_millis_testing 30.69941599824233 usercpu_time_millis_testing 32.61628100153757 usercpu_time_millis_testing 31.957724997482728 usercpu_time_millis_testing 31.16911699908087 usercpu_time_millis_testing 31.253859000571538 usercpu_time_millis_testing 31.80883799723233 usercpu_time_millis_testing 60.590500997932395 usercpu_time_millis_testing 30.111012001725612 usercpu_time_millis_training 1800.0100220015156 usercpu_time_millis_training 1852.9202589998022 usercpu_time_millis_training 1857.6728730004106 usercpu_time_millis_training 1851.1443060015154 usercpu_time_millis_training 1785.2105199999642 usercpu_time_millis_training 1960.9321050011204 usercpu_time_millis_training 1890.3233950004505 usercpu_time_millis_training 1922.9332100003376 usercpu_time_millis_training 1843.408429002011 usercpu_time_millis_training 1880.2917180000804 wall_clock_time_millis 1829.5905590057373 wall_clock_time_millis 1883.209228515625 wall_clock_time_millis 1888.4055614471436 wall_clock_time_millis 1883.8117122650146 wall_clock_time_millis 1817.1684741973877 wall_clock_time_millis 1992.1021461486816 wall_clock_time_millis 1921.586513519287 wall_clock_time_millis 1954.7529220581055 wall_clock_time_millis 1904.2530059814453 wall_clock_time_millis 1910.4018211364746 wall_clock_time_millis_testing 29.573917388916016 wall_clock_time_millis_testing 30.29322624206543 wall_clock_time_millis_testing 30.70354461669922 wall_clock_time_millis_testing 32.62066841125488 wall_clock_time_millis_testing 31.961679458618164 wall_clock_time_millis_testing 31.1737060546875 wall_clock_time_millis_testing 31.25786781311035 wall_clock_time_millis_testing 31.812191009521484 wall_clock_time_millis_testing 60.60910224914551 wall_clock_time_millis_testing 30.11465072631836 wall_clock_time_millis_training 1800.0166416168213 wall_clock_time_millis_training 1852.9160022735596 wall_clock_time_millis_training 1857.7020168304443 wall_clock_time_millis_training 1851.1910438537598 wall_clock_time_millis_training 1785.2067947387695 wall_clock_time_millis_training 1960.9284400939941 wall_clock_time_millis_training 1890.3286457061768 wall_clock_time_millis_training 1922.940731048584 wall_clock_time_millis_training 1843.6439037322998 wall_clock_time_millis_training 1880.2871704101562 weighted_recall 0.52 [0.586207,0.428571] weighted_recall 0.52 [0.586207,0.428571] weighted_recall 0.58 [0.62069,0.52381] weighted_recall 0.4 [0.517241,0.238095] weighted_recall 0.44 [0.482759,0.380952] weighted_recall 0.58 [0.793103,0.285714] weighted_recall 0.62 [0.655172,0.571429] weighted_recall 0.62 [0.586207,0.666667] weighted_recall 0.5 [0.517241,0.47619] weighted_recall 0.58 [0.689655,0.428571]