10329390 8323 Heinrich Peters 53 Supervised Classification 16345 sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1) 8185010 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 0.04763431960619049 13389 cache_size 200 13389 class_weight null 13389 coef0 -0.21633948699433825 13389 decision_function_shape "ovr" 13389 degree 1 13389 gamma 2.0076472291150194 13389 kernel "poly" 13389 max_iter -1 13389 probability false 13389 random_state 23357 13389 shrinking true 13389 tol 0.001 13389 verbose false 13389 memory null 16345 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}] 16345 verbose false 16345 openml-python Sklearn_0.21.2. 54 vehicle https://www.openml.org/data/download/54/dataset_54_vehicle.arff -1 21580477 description https://api.openml.org/data/download/21580477/description.xml -1 21580478 predictions https://api.openml.org/data/download/21580478/predictions.arff area_under_roc_curve 0.8428483258787408 [0.730961,0.729275,0.953179,0.965026] average_cost 0 f_measure 0.7566043349853079 [0.60199,0.601942,0.912281,0.919431] kappa 0.6864098647692137 kb_relative_information_score 0.7172844873585639 mean_absolute_error 0.11761229314420804 mean_prior_absolute_error 0.3748407731887084 number_of_instances 846 [212,217,218,199] precision 0.7525323339740877 [0.636842,0.635897,0.87395,0.869955] predictive_accuracy 0.764775413711584 prior_entropy 1.9990667866719984 recall 0.764775413711584 [0.570755,0.571429,0.954128,0.974874] relative_absolute_error 0.31376600828052864 root_mean_prior_squared_error 0.4329203297871725 root_mean_squared_error 0.3429464872895012 root_relative_squared_error 0.7921699760741123 total_cost 0 area_under_roc_curve 0.8274896978021978 [0.667783,0.694444,0.984127,0.969231] area_under_roc_curve 0.8191811660561661 [0.738839,0.678571,0.945527,0.919231] area_under_roc_curve 0.8349378052503053 [0.691592,0.724026,0.946609,0.984615] area_under_roc_curve 0.8663118131868133 [0.762649,0.786436,0.93759,0.984615] area_under_roc_curve 0.850318605006105 [0.683408,0.761544,0.969336,0.992308] area_under_roc_curve 0.8903655372405371 [0.834077,0.825036,0.930736,0.976923] area_under_roc_curve 0.8486470518728585 [0.747067,0.769795,0.952381,0.942915] area_under_roc_curve 0.8408738159242193 [0.747067,0.714286,0.936508,0.976562] area_under_roc_curve 0.8416338645673324 [0.785714,0.65873,0.961144,0.960938] area_under_roc_curve 0.8091357846902202 [0.650794,0.674603,0.967742,0.942187] 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 0.727356428737503 [0.5,0.55,0.956522,0.909091] f_measure 0.7205802124450434 [0.615385,0.52381,0.893617,0.857143] f_measure 0.7503650354072429 [0.536585,0.590909,0.930233,0.952381] f_measure 0.7923249299719888 [0.65,0.7,0.875,0.952381] f_measure 0.7718515281457407 [0.526316,0.638298,0.954545,0.97561] f_measure 0.8318963602137337 [0.744186,0.769231,0.888889,0.930233] f_measure 0.7665681202266568 [0.634146,0.666667,0.909091,0.878049] f_measure 0.7496980354410158 [0.634146,0.578947,0.869565,0.930233] f_measure 0.7484379850233508 [0.682927,0.486486,0.933333,0.888889] f_measure 0.7061876142353498 [0.473684,0.511628,0.916667,0.923077] kappa 0.6551088159350793 kappa 0.6390991323610854 kappa 0.6706034323675955 kappa 0.733296419342931 kappa 0.7016992981159956 kappa 0.7805642633228841 kappa 0.6986973758731356 kappa 0.6827794561933535 kappa 0.6826596146581034 kappa 0.6185430463576159 kb_relative_information_score 0.6890250942836318 kb_relative_information_score 0.6742539900416367 kb_relative_information_score 0.7032761975891659 kb_relative_information_score 0.7597916751223371 kb_relative_information_score 0.7312610231964918 kb_relative_information_score 0.8024179129626419 kb_relative_information_score 0.7277473705636908 kb_relative_information_score 0.7142165475450584 kb_relative_information_score 0.7144115983499322 kb_relative_information_score 0.6557911338524934 mean_absolute_error 0.12941176470588237 mean_absolute_error 0.13529411764705881 mean_absolute_error 0.12352941176470589 mean_absolute_error 0.1 mean_absolute_error 0.11176470588235295 mean_absolute_error 0.08235294117647059 mean_absolute_error 0.1130952380952381 mean_absolute_error 0.11904761904761904 mean_absolute_error 0.11904761904761904 mean_absolute_error 0.14285714285714285 mean_prior_absolute_error 0.37483044982698976 mean_prior_absolute_error 0.37483044982698976 mean_prior_absolute_error 0.37483044982698976 mean_prior_absolute_error 0.37483044982698976 mean_prior_absolute_error 0.37483044982698976 mean_prior_absolute_error 0.37483044982698976 mean_prior_absolute_error 0.37478291316526624 mean_prior_absolute_error 0.37490896358543435 mean_prior_absolute_error 0.37486694677871163 mean_prior_absolute_error 0.37486694677871163 number_of_instances 85 [21,22,22,20] number_of_instances 85 [21,22,22,20] number_of_instances 85 [21,22,22,20] number_of_instances 85 [21,22,22,20] number_of_instances 85 [21,22,22,20] number_of_instances 85 [21,22,22,20] number_of_instances 84 [22,22,21,19] number_of_instances 84 [22,21,21,20] number_of_instances 84 [21,21,22,20] number_of_instances 84 [21,21,22,20] precision 0.7215342277261781 [0.526316,0.611111,0.916667,0.833333] precision 0.7169839572192512 [0.666667,0.55,0.84,0.818182] precision 0.7492258721670486 [0.55,0.590909,0.952381,0.909091] precision 0.7933009542916662 [0.684211,0.777778,0.807692,0.909091] precision 0.7717712967539957 [0.588235,0.6,0.954545,0.952381] precision 0.8377203659887578 [0.727273,0.882353,0.869565,0.869565] precision 0.7649875677335632 [0.684211,0.7,0.869565,0.818182] precision 0.7480020383439417 [0.684211,0.647059,0.8,0.869565] precision 0.7452316252587992 [0.7,0.5625,0.913043,0.8] precision 0.7045285725626284 [0.529412,0.5,0.846154,0.947368] predictive_accuracy 0.7411764705882353 predictive_accuracy 0.7294117647058823 predictive_accuracy 0.7529411764705882 predictive_accuracy 0.8 predictive_accuracy 0.776470588235294 predictive_accuracy 0.8352941176470589 predictive_accuracy 0.7738095238095238 predictive_accuracy 0.7619047619047619 predictive_accuracy 0.7619047619047619 predictive_accuracy 0.7142857142857143 prior_entropy 1.9989496630655892 prior_entropy 1.9989496630655892 prior_entropy 1.9989496630655892 prior_entropy 1.9989496630655892 prior_entropy 1.9989496630655892 prior_entropy 1.9989496630655892 prior_entropy 1.998373047127382 prior_entropy 1.9998531439726461 prior_entropy 1.99937603159913 prior_entropy 1.99937603159913 recall 0.7411764705882353 [0.47619,0.5,1,1] recall 0.7294117647058823 [0.571429,0.5,0.954545,0.9] recall 0.7529411764705882 [0.52381,0.590909,0.909091,1] recall 0.8 [0.619048,0.636364,0.954545,1] recall 0.7764705882352941 [0.47619,0.681818,0.954545,1] recall 0.8352941176470589 [0.761905,0.681818,0.909091,1] recall 0.7738095238095238 [0.590909,0.636364,0.952381,0.947368] recall 0.7619047619047619 [0.590909,0.52381,0.952381,1] recall 0.7619047619047619 [0.666667,0.428571,0.954545,1] recall 0.7142857142857143 [0.428571,0.52381,1,0.9] relative_absolute_error 0.345254140280265 relative_absolute_error 0.3609475102930043 relative_absolute_error 0.32956077026752567 relative_absolute_error 0.2667872902165684 relative_absolute_error 0.2981740302420471 relative_absolute_error 0.21970718017835045 relative_absolute_error 0.30176199106859236 relative_absolute_error 0.3175374040383284 relative_absolute_error 0.3175729950869588 relative_absolute_error 0.38108759410435056 root_mean_prior_squared_error 0.43290840668819885 root_mean_prior_squared_error 0.43290840668819885 root_mean_prior_squared_error 0.43290840668819885 root_mean_prior_squared_error 0.43290840668819885 root_mean_prior_squared_error 0.43290840668819885 root_mean_prior_squared_error 0.43290840668819885 root_mean_prior_squared_error 0.4328534993731614 root_mean_prior_squared_error 0.43299907891329226 root_mean_prior_squared_error 0.43295055783892555 root_mean_prior_squared_error 0.43295055783892555 root_mean_squared_error 0.3597384670922507 root_mean_squared_error 0.36782348707914075 root_mean_squared_error 0.3514675116774037 root_mean_squared_error 0.31622776601683794 root_mean_squared_error 0.33431228796194873 root_mean_squared_error 0.2869720215917757 root_mean_squared_error 0.33629635456727464 root_mean_squared_error 0.3450327796711771 root_mean_squared_error 0.3450327796711771 root_mean_squared_error 0.3779644730092272 root_relative_squared_error 0.8309805527785729 root_relative_squared_error 0.8496566049456846 root_relative_squared_error 0.811874997684088 root_relative_squared_error 0.7304726845939957 root_relative_squared_error 0.7722471608243364 root_relative_squared_error 0.6628931597497634 root_relative_squared_error 0.77692881091243 root_relative_squared_error 0.7968441423411657 root_relative_squared_error 0.7969334452261931 root_relative_squared_error 0.8729968495613873 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 32.702684999094345 usercpu_time_millis 33.64129699184559 usercpu_time_millis 33.018157992046326 usercpu_time_millis 34.15953001240268 usercpu_time_millis 34.07907500513829 usercpu_time_millis 34.14419099863153 usercpu_time_millis 33.40520399797242 usercpu_time_millis 33.71696999238338 usercpu_time_millis 33.89140800572932 usercpu_time_millis 34.07189798599575 usercpu_time_millis_testing 2.63907499902416 usercpu_time_millis_testing 2.5470409891568124 usercpu_time_millis_testing 2.5475989968981594 usercpu_time_millis_testing 2.6906060084002092 usercpu_time_millis_testing 2.6144810108235106 usercpu_time_millis_testing 2.63721399824135 usercpu_time_millis_testing 2.553247002651915 usercpu_time_millis_testing 2.5990479916799814 usercpu_time_millis_testing 2.6964370044879615 usercpu_time_millis_testing 2.555443992605433 usercpu_time_millis_training 30.063610000070184 usercpu_time_millis_training 31.09425600268878 usercpu_time_millis_training 30.470558995148167 usercpu_time_millis_training 31.468924004002474 usercpu_time_millis_training 31.464593994314782 usercpu_time_millis_training 31.50697700039018 usercpu_time_millis_training 30.851956995320506 usercpu_time_millis_training 31.117922000703402 usercpu_time_millis_training 31.194971001241356 usercpu_time_millis_training 31.516453993390314 wall_clock_time_millis 32.72080421447754 wall_clock_time_millis 33.658742904663086 wall_clock_time_millis 33.03647041320801 wall_clock_time_millis 34.19089317321777 wall_clock_time_millis 34.093379974365234 wall_clock_time_millis 34.23595428466797 wall_clock_time_millis 33.464908599853516 wall_clock_time_millis 33.78582000732422 wall_clock_time_millis 33.9200496673584 wall_clock_time_millis 34.08551216125488 wall_clock_time_millis_testing 2.6497840881347656 wall_clock_time_millis_testing 2.5572776794433594 wall_clock_time_millis_testing 2.557516098022461 wall_clock_time_millis_testing 2.7022361755371094 wall_clock_time_millis_testing 2.621173858642578 wall_clock_time_millis_testing 2.6578903198242188 wall_clock_time_millis_testing 2.5625228881835938 wall_clock_time_millis_testing 2.610445022583008 wall_clock_time_millis_testing 2.703428268432617 wall_clock_time_millis_testing 2.5625228881835938 wall_clock_time_millis_training 30.071020126342773 wall_clock_time_millis_training 31.101465225219727 wall_clock_time_millis_training 30.478954315185547 wall_clock_time_millis_training 31.488656997680664 wall_clock_time_millis_training 31.472206115722656 wall_clock_time_millis_training 31.57806396484375 wall_clock_time_millis_training 30.902385711669922 wall_clock_time_millis_training 31.17537498474121 wall_clock_time_millis_training 31.21662139892578 wall_clock_time_millis_training 31.52298927307129