10559614 8323 Heinrich Peters 125920 Supervised Classification 18298 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)(4) 8276193 copy true 17405 with_mean true 17405 with_std true 17405 add_indicator false 17407 copy true 17407 fill_value null 17407 missing_values NaN 17407 strategy "most_frequent" 17407 verbose 0 17407 categorical_features null 17408 categories null 17408 drop null 17408 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 17408 handle_unknown "ignore" 17408 n_values null 17408 sparse true 17408 C 20782.267317842347 17495 cache_size 200 17495 class_weight null 17495 coef0 -0.3671201161021156 17495 decision_function_shape "ovr" 17495 degree 5 17495 gamma 0.10680238302677152 17495 kernel "rbf" 17495 max_iter -1 17495 probability true 17495 random_state 1 17495 shrinking true 17495 tol 0.001 17495 verbose false 17495 memory null 18298 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"}}] 18298 verbose false 18298 n_jobs null 18299 remainder "drop" 18299 sparse_threshold 0.3 18299 transformer_weights null 18299 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]}}] 18299 verbose false 18299 memory null 18300 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 18300 verbose false 18300 memory null 18301 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}] 18301 verbose false 18301 openml-python Sklearn_0.21.2. 23381 dresses-sales https://www.openml.org/data/download/1910507/phpcFPMhq -1 22044215 description https://api.openml.org/data/download/22044215/description.xml -1 22044216 predictions https://api.openml.org/data/download/22044216/predictions.arff area_under_roc_curve 0.5647619047619048 [0.564762,0.564762] average_cost 0 f_measure 0.48716577540106953 [0.719251,0.166667] kappa 0.03100775193798451 kb_relative_information_score 0.013906806124556732 mean_absolute_error 0.48133079582055904 mean_prior_absolute_error 0.4872509960159361 weighted_recall 0.58 [0.927586,0.1] number_of_instances 500 [290,210] precision 0.5506550218340611 [0.587336,0.5] predictive_accuracy 0.58 prior_entropy 0.9814541958069474 relative_absolute_error 0.9878497935483268 root_mean_prior_squared_error 0.4935586100816085 root_mean_squared_error 0.4940251699120177 root_relative_squared_error 1.0009452977232676 total_cost 0 unweighted_recall 0.5137931034482759 [0.927586,0.1] area_under_roc_curve 0.5139573070607554 [0.513957,0.513957] area_under_roc_curve 0.5993431855500821 [0.599343,0.599343] area_under_roc_curve 0.5188834154351396 [0.518883,0.518883] area_under_roc_curve 0.43513957307060763 [0.43514,0.43514] area_under_roc_curve 0.6486042692939245 [0.648604,0.648604] area_under_roc_curve 0.5385878489326765 [0.538588,0.538588] area_under_roc_curve 0.5188834154351396 [0.518883,0.518883] area_under_roc_curve 0.7717569786535303 [0.771757,0.771757] area_under_roc_curve 0.5632183908045977 [0.563218,0.563218] area_under_roc_curve 0.5845648604269293 [0.584565,0.584565] 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 0.44710526315789473 [0.710526,0.083333] f_measure 0.45833992094861664 [0.727273,0.086957] f_measure 0.45833992094861664 [0.727273,0.086957] f_measure 0.4654002713704206 [0.626866,0.242424] f_measure 0.568149688149688 [0.756757,0.307692] f_measure 0.44666666666666666 [0.666667,0.142857] f_measure 0.48480000000000006 [0.72,0.16] f_measure 0.5099265951439864 [0.753247,0.173913] f_measure 0.5338666666666666 [0.746667,0.24] f_measure 0.46946386946386953 [0.74359,0.090909] kappa -0.024208566108007368 kappa 0.01500938086303931 kappa 0.01500938086303931 kappa -0.09075043630017444 kappa 0.1743119266055047 kappa -0.08499095840867985 kappa 0.02957486136783716 kappa 0.10881801125703564 kappa 0.12199630314232894 kappa 0.05482041587901701 kb_relative_information_score -0.0021075384813014856 kb_relative_information_score 0.013789933462392247 kb_relative_information_score 0.0008272962105205287 kb_relative_information_score -0.029011805981866843 kb_relative_information_score 0.05634238771369118 kb_relative_information_score 0.013108119692660423 kb_relative_information_score 0.007234998538912851 kb_relative_information_score 0.05093425157219343 kb_relative_information_score 0.012149499815770683 kb_relative_information_score 0.015800918702593994 mean_absolute_error 0.4878134131453294 mean_absolute_error 0.48088414292224213 mean_absolute_error 0.4862822642711032 mean_absolute_error 0.4965660988689361 mean_absolute_error 0.4643668171078992 mean_absolute_error 0.48137019047110635 mean_absolute_error 0.4832398752202272 mean_absolute_error 0.4688125357295601 mean_absolute_error 0.4829384967166297 mean_absolute_error 0.48103412375255883 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 0.47319148936170213 [0.574468,0.333333] precision 0.5483333333333333 [0.583333,0.5] precision 0.5483333333333333 [0.583333,0.5] precision 0.4605263157894737 [0.552632,0.333333] precision 0.696888888888889 [0.622222,0.8] precision 0.44372093023255815 [0.55814,0.285714] precision 0.5504347826086957 [0.586957,0.5] precision 0.7704166666666665 [0.604167,1] precision 0.6680434782608696 [0.608696,0.75] precision 0.7632653061224489 [0.591837,1] predictive_accuracy 0.56 predictive_accuracy 0.58 predictive_accuracy 0.58 predictive_accuracy 0.5 predictive_accuracy 0.64 predictive_accuracy 0.52 predictive_accuracy 0.58 predictive_accuracy 0.62 predictive_accuracy 0.62 predictive_accuracy 0.6 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 1.0011542657357129 relative_absolute_error 0.9869331142557872 relative_absolute_error 0.9980118424533679 relative_absolute_error 1.0191176681611036 relative_absolute_error 0.9530341054299485 relative_absolute_error 0.9879306443846909 relative_absolute_error 0.9917678551126494 relative_absolute_error 0.9621581886191299 relative_absolute_error 0.9911493268673267 relative_absolute_error 0.9872409244635508 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 0.4974360609982473 root_mean_squared_error 0.48870964866327393 root_mean_squared_error 0.495269776400764 root_mean_squared_error 0.5276040729330969 root_mean_squared_error 0.4771416482282496 root_mean_squared_error 0.4970834037993564 root_mean_squared_error 0.4968391839445029 root_mean_squared_error 0.47509522762856604 root_mean_squared_error 0.49173172403021226 root_mean_squared_error 0.4914772824391448 root_relative_squared_error 1.0078561103735943 root_relative_squared_error 0.9901755104271557 root_relative_squared_error 1.003466997199933 root_relative_squared_error 1.0689795743728578 root_relative_squared_error 0.966737563648937 root_relative_squared_error 1.0071415909797732 root_relative_squared_error 1.0066467766864653 root_relative_squared_error 0.962591307139816 root_relative_squared_error 0.9962985428395345 root_relative_squared_error 0.995783018267842 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 0.4893267651888341 [0.931034,0.047619] unweighted_recall 0.506568144499179 [0.965517,0.047619] unweighted_recall 0.506568144499179 [0.965517,0.047619] unweighted_recall 0.4573070607553366 [0.724138,0.190476] unweighted_recall 0.5779967159277504 [0.965517,0.190476] unweighted_recall 0.4614121510673235 [0.827586,0.095238] unweighted_recall 0.513136288998358 [0.931034,0.095238] unweighted_recall 0.5476190476190477 [1,0.095238] unweighted_recall 0.5541871921182266 [0.965517,0.142857] unweighted_recall 0.5238095238095238 [1,0.047619] usercpu_time_millis 181.97200000000004 usercpu_time_millis 181.9779999999991 usercpu_time_millis 179.19400000000073 usercpu_time_millis 185.92600000000027 usercpu_time_millis 178.57599999999786 usercpu_time_millis 187.4959999999959 usercpu_time_millis 173.79999999999995 usercpu_time_millis 179.72999999999928 usercpu_time_millis 178.92600000000058 usercpu_time_millis 175.70199999999758 usercpu_time_millis_testing 6.918000000000646 usercpu_time_millis_testing 7.359999999998479 usercpu_time_millis_testing 7.200000000000983 usercpu_time_millis_testing 7.464000000000581 usercpu_time_millis_testing 7.258000000000209 usercpu_time_millis_testing 7.327999999997559 usercpu_time_millis_testing 7.376000000000715 usercpu_time_millis_testing 6.8139999999985434 usercpu_time_millis_testing 7.211999999999108 usercpu_time_millis_testing 6.807999999999481 usercpu_time_millis_training 175.05399999999938 usercpu_time_millis_training 174.61800000000062 usercpu_time_millis_training 171.99399999999974 usercpu_time_millis_training 178.46199999999968 usercpu_time_millis_training 171.31799999999765 usercpu_time_millis_training 180.16799999999833 usercpu_time_millis_training 166.42399999999924 usercpu_time_millis_training 172.91600000000074 usercpu_time_millis_training 171.71400000000148 usercpu_time_millis_training 168.8939999999981 wall_clock_time_millis 91.4926528930664 wall_clock_time_millis 90.85917472839355 wall_clock_time_millis 89.91074562072754 wall_clock_time_millis 93.18733215332031 wall_clock_time_millis 89.73193168640137 wall_clock_time_millis 94.12312507629395 wall_clock_time_millis 87.2197151184082 wall_clock_time_millis 90.42024612426758 wall_clock_time_millis 89.70117568969727 wall_clock_time_millis 88.04106712341309 wall_clock_time_millis_testing 3.4627914428710938 wall_clock_time_millis_testing 3.6869049072265625 wall_clock_time_millis_testing 3.634929656982422 wall_clock_time_millis_testing 3.7381649017333984 wall_clock_time_millis_testing 3.654003143310547 wall_clock_time_millis_testing 3.6962032318115234 wall_clock_time_millis_testing 3.6928653717041016 wall_clock_time_millis_testing 3.4110546112060547 wall_clock_time_millis_testing 3.6101341247558594 wall_clock_time_millis_testing 3.412961959838867 wall_clock_time_millis_training 88.02986145019531 wall_clock_time_millis_training 87.17226982116699 wall_clock_time_millis_training 86.27581596374512 wall_clock_time_millis_training 89.44916725158691 wall_clock_time_millis_training 86.07792854309082 wall_clock_time_millis_training 90.42692184448242 wall_clock_time_millis_training 83.5268497467041 wall_clock_time_millis_training 87.00919151306152 wall_clock_time_millis_training 86.0910415649414 wall_clock_time_millis_training 84.62810516357422 weighted_recall 0.56 [0.931034,0.047619] weighted_recall 0.58 [0.965517,0.047619] weighted_recall 0.58 [0.965517,0.047619] weighted_recall 0.5 [0.724138,0.190476] weighted_recall 0.64 [0.965517,0.190476] weighted_recall 0.52 [0.827586,0.095238] weighted_recall 0.58 [0.931034,0.095238] weighted_recall 0.62 [1,0.095238] weighted_recall 0.62 [0.965517,0.142857] weighted_recall 0.6 [1,0.047619]