10416338 8323 Heinrich Peters 23 Supervised Classification 16374 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)),svc=sklearn.svm.classes.SVC)(2) 8254041 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 C 81356.92108932823 13389 cache_size 200 13389 class_weight null 13389 coef0 -0.33706310267468553 13389 decision_function_shape "ovr" 13389 degree 2 13389 gamma 2.238549391298506 13389 kernel "poly" 13389 max_iter -1 13389 probability false 13389 random_state 1 13389 shrinking true 13389 tol 0.001 13389 verbose false 13389 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 memory null 16374 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": "svc", "step_name": "svc"}}] 16374 verbose false 16374 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": [true, false, false, true, false, false, false, false, false]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [false, true, true, false, 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 openml-python Sklearn_0.21.2. 23 cmc https://www.openml.org/data/download/23/dataset_23_cmc.arff -1 21754542 description https://api.openml.org/data/download/21754542/description.xml -1 21754543 predictions https://api.openml.org/data/download/21754543/predictions.arff area_under_roc_curve 0.6136451257366697 [0.632651,0.596661,0.601319] average_cost 0 f_measure 0.5004261987245193 [0.588326,0.372457,0.475622] kappa 0.22544968679960925 kb_relative_information_score 0.28526636961890584 mean_absolute_error 0.3312966734555364 mean_prior_absolute_error 0.4308274628344832 number_of_instances 1473 [629,333,511] precision 0.49876753393451945 [0.569094,0.388889,0.483806] predictive_accuracy 0.5030549898167006 prior_entropy 1.5390347976697278 recall 0.5030549898167006 [0.608903,0.357357,0.46771] relative_absolute_error 0.7689776117703413 root_mean_prior_squared_error 0.46411194018393376 root_mean_squared_error 0.5755837675399962 root_relative_squared_error 1.24018306297374 total_cost 0 area_under_roc_curve 0.6349627099890417 [0.658357,0.605005,0.626036] area_under_roc_curve 0.6318257742597854 [0.642764,0.621001,0.625531] area_under_roc_curve 0.599380272999053 [0.639216,0.56063,0.576006] area_under_roc_curve 0.5820018796992482 [0.611111,0.55941,0.560662] area_under_roc_curve 0.6216322055137845 [0.638889,0.590112,0.620711] area_under_roc_curve 0.6139176065162908 [0.64881,0.624402,0.564032] area_under_roc_curve 0.6275454260651628 [0.652778,0.626396,0.59712] area_under_roc_curve 0.568765664160401 [0.583333,0.550638,0.5625] area_under_roc_curve 0.6082393483709273 [0.625,0.605263,0.589461] area_under_roc_curve 0.647265221878225 [0.624288,0.624402,0.68917] 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 0.5223708765446999 [0.601626,0.394366,0.509804] f_measure 0.5247741044616046 [0.59375,0.412698,0.514286] f_measure 0.4798340149121069 [0.608696,0.290909,0.446602] f_measure 0.458118556701031 [0.571429,0.3125,0.412371] f_measure 0.5137146991189313 [0.614286,0.350877,0.494845] f_measure 0.49873625706006136 [0.590164,0.41791,0.438095] f_measure 0.5132818632765684 [0.616541,0.422535,0.444444] f_measure 0.4408472479901051 [0.557143,0.30303,0.386364] f_measure 0.49817415028316403 [0.586466,0.37931,0.466019] f_measure 0.5350850639690381 [0.535714,0.41791,0.608696] kappa 0.26337188923939714 kappa 0.26362925581064744 kappa 0.19640917975819883 kappa 0.16030368763557484 kappa 0.24449339207048465 kappa 0.22388698630136988 kappa 0.25214961306964745 kappa 0.13604701784936873 kappa 0.21797114123305641 kappa 0.2916164694210191 kb_relative_information_score 0.3134884798845469 kb_relative_information_score 0.32076108392045777 kb_relative_information_score 0.2637298662528939 kb_relative_information_score 0.2257352077318021 kb_relative_information_score 0.3085768072087569 kb_relative_information_score 0.2806815342855123 kb_relative_information_score 0.3083060027260108 kb_relative_information_score 0.20629077720194128 kb_relative_information_score 0.28375220036378085 kb_relative_information_score 0.3408680692926231 mean_absolute_error 0.3198198198198196 mean_absolute_error 0.3153153153153151 mean_absolute_error 0.33783783783783755 mean_absolute_error 0.35827664399092934 mean_absolute_error 0.3174603174603173 mean_absolute_error 0.3356009070294782 mean_absolute_error 0.3219954648526075 mean_absolute_error 0.36734693877550983 mean_absolute_error 0.33106575963718793 mean_absolute_error 0.3083900226757368 mean_prior_absolute_error 0.4311933885104624 mean_prior_absolute_error 0.4311933885104624 mean_prior_absolute_error 0.4311933885104624 mean_prior_absolute_error 0.43061777556551145 mean_prior_absolute_error 0.43061777556551145 mean_prior_absolute_error 0.43061777556551145 mean_prior_absolute_error 0.43061777556551145 mean_prior_absolute_error 0.43061777556551145 mean_prior_absolute_error 0.43061777556551145 mean_prior_absolute_error 0.4309803415494479 number_of_instances 148 [63,34,51] number_of_instances 148 [63,34,51] number_of_instances 148 [63,34,51] number_of_instances 147 [63,33,51] number_of_instances 147 [63,33,51] number_of_instances 147 [63,33,51] number_of_instances 147 [63,33,51] number_of_instances 147 [63,33,51] number_of_instances 147 [63,33,51] number_of_instances 147 [62,33,52] precision 0.525100438276114 [0.616667,0.378378,0.509804] precision 0.5241361387913113 [0.584615,0.448276,0.5] precision 0.47831130581130576 [0.56,0.380952,0.442308] precision 0.45591207029796493 [0.542857,0.322581,0.434783] precision 0.5138810464897421 [0.558442,0.416667,0.521739] precision 0.5017084046424596 [0.610169,0.411765,0.425926] precision 0.5175521220634003 [0.585714,0.394737,0.512821] precision 0.44450015878587307 [0.506494,0.30303,0.459459] precision 0.49767660910518063 [0.557143,0.44,0.461538] precision 0.5420212529456226 [0.6,0.411765,0.555556] predictive_accuracy 0.5202702702702703 predictive_accuracy 0.527027027027027 predictive_accuracy 0.4932432432432432 predictive_accuracy 0.4625850340136054 predictive_accuracy 0.5238095238095238 predictive_accuracy 0.4965986394557823 predictive_accuracy 0.5170068027210885 predictive_accuracy 0.4489795918367347 predictive_accuracy 0.5034013605442177 predictive_accuracy 0.5374149659863946 prior_entropy 1.5416928769893397 prior_entropy 1.5416928769893397 prior_entropy 1.5416928769893397 prior_entropy 1.5375970957879994 prior_entropy 1.5375970957879994 prior_entropy 1.5375970957879994 prior_entropy 1.5375970957879994 prior_entropy 1.5375970957879994 prior_entropy 1.5375970957879994 prior_entropy 1.5396325244845115 recall 0.5202702702702703 [0.587302,0.411765,0.509804] recall 0.527027027027027 [0.603175,0.382353,0.529412] recall 0.49324324324324326 [0.666667,0.235294,0.45098] recall 0.46258503401360546 [0.603175,0.30303,0.392157] recall 0.5238095238095238 [0.68254,0.30303,0.470588] recall 0.4965986394557823 [0.571429,0.424242,0.45098] recall 0.5170068027210885 [0.650794,0.454545,0.392157] recall 0.4489795918367347 [0.619048,0.30303,0.333333] recall 0.5034013605442177 [0.619048,0.333333,0.470588] recall 0.5374149659863946 [0.483871,0.424242,0.673077] relative_absolute_error 0.741708542713566 relative_absolute_error 0.7312619435204172 relative_absolute_error 0.7834949394861611 relative_absolute_error 0.8320061649113771 relative_absolute_error 0.7372206524531194 relative_absolute_error 0.7793475468790118 relative_absolute_error 0.7477523760595923 relative_absolute_error 0.8530696121243234 relative_absolute_error 0.7688158232725385 relative_absolute_error 0.7155547317240085 root_mean_prior_squared_error 0.46450599425333045 root_mean_prior_squared_error 0.46450599425333045 root_mean_prior_squared_error 0.46450599425333045 root_mean_prior_squared_error 0.4638859835695881 root_mean_prior_squared_error 0.4638859835695881 root_mean_prior_squared_error 0.4638859835695881 root_mean_prior_squared_error 0.4638859835695881 root_mean_prior_squared_error 0.4638859835695881 root_mean_prior_squared_error 0.4638859835695881 root_mean_prior_squared_error 0.4642766112311287 root_mean_squared_error 0.5655261442407589 root_mean_squared_error 0.5615294429638709 root_mean_squared_error 0.5812381937190961 root_mean_squared_error 0.5985621471417395 root_mean_squared_error 0.5634361698190109 root_mean_squared_error 0.5793107171712588 root_mean_squared_error 0.5674464422768086 root_mean_squared_error 0.6060915267313262 root_mean_squared_error 0.5753831415997412 root_mean_squared_error 0.5553287518900285 root_relative_squared_error 1.2174786789346241 root_relative_squared_error 1.2088744815155734 root_relative_squared_error 1.2513039678926139 root_relative_squared_error 1.290321691842945 root_relative_squared_error 1.2146005479264264 root_relative_squared_error 1.2488213433686464 root_relative_squared_error 1.2232455007808731 root_relative_squared_error 1.3065527914154051 root_relative_squared_error 1.2403546603675886 root_relative_squared_error 1.1961161481244027 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 165655816.44975 usercpu_time_millis 231569350.7446968 usercpu_time_millis 148236414.54391882 usercpu_time_millis 142018960.79985097 usercpu_time_millis 128531838.76178297 usercpu_time_millis 172216776.6746818 usercpu_time_millis 191046655.31975263 usercpu_time_millis 162580764.3063129 usercpu_time_millis 189514855.78382576 usercpu_time_millis 129687009.37786372 usercpu_time_millis_testing 12.5743318349123 usercpu_time_millis_testing 16.887381905689836 usercpu_time_millis_testing 12.336791027337313 usercpu_time_millis_testing 8.029508870095015 usercpu_time_millis_testing 11.111342813819647 usercpu_time_millis_testing 6.1242119409143925 usercpu_time_millis_testing 6.138031370937824 usercpu_time_millis_testing 6.070271134376526 usercpu_time_millis_testing 7.768823765218258 usercpu_time_millis_testing 6.185133010149002 usercpu_time_millis_training 165655803.87541816 usercpu_time_millis_training 231569333.85731488 usercpu_time_millis_training 148236402.20712778 usercpu_time_millis_training 142018952.7703421 usercpu_time_millis_training 128531827.65044016 usercpu_time_millis_training 172216770.55046988 usercpu_time_millis_training 191046649.18172127 usercpu_time_millis_training 162580758.23604175 usercpu_time_millis_training 189514848.01500198 usercpu_time_millis_training 129687003.19273071 wall_clock_time_millis 165665073.12989235 wall_clock_time_millis 231647084.1369629 wall_clock_time_millis 148264483.23845863 wall_clock_time_millis 142028865.05913734 wall_clock_time_millis 128540250.02884865 wall_clock_time_millis 172232474.4784832 wall_clock_time_millis 191068882.6444149 wall_clock_time_millis 162591104.00032997 wall_clock_time_millis 189525602.89359093 wall_clock_time_millis 129690682.35063553 wall_clock_time_millis_testing 12.578964233398438 wall_clock_time_millis_testing 16.895294189453125 wall_clock_time_millis_testing 12.344121932983398 wall_clock_time_millis_testing 8.031845092773438 wall_clock_time_millis_testing 11.113405227661133 wall_clock_time_millis_testing 6.126880645751953 wall_clock_time_millis_testing 6.140470504760742 wall_clock_time_millis_testing 6.072521209716797 wall_clock_time_millis_testing 7.77125358581543 wall_clock_time_millis_testing 6.18743896484375 wall_clock_time_millis_training 165665060.55092812 wall_clock_time_millis_training 231647067.2416687 wall_clock_time_millis_training 148264470.8943367 wall_clock_time_millis_training 142028857.02729225 wall_clock_time_millis_training 128540238.91544342 wall_clock_time_millis_training 172232468.35160255 wall_clock_time_millis_training 191068876.5039444 wall_clock_time_millis_training 162591097.92780876 wall_clock_time_millis_training 189525595.12233734 wall_clock_time_millis_training 129690676.16319656