10559551 8323 Heinrich Peters 14954 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) 8276164 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 690.6018801899403 17495 cache_size 200 17495 class_weight null 17495 coef0 -0.6356144967116901 17495 decision_function_shape "ovr" 17495 degree 5 17495 gamma 0.0008714226148272087 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, true, false, false, false, false, false, false, false, false, false, false, false, false, true, false, false, false, true, true, false, true, true, true, true, true, true, true, true, true, true, true, true, true, false, true, false]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [true, false, true, true, true, true, true, true, true, true, true, true, true, true, false, true, true, true, false, false, true, false, false, false, false, false, false, false, false, false, false, false, false, false, true, false, 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. 6332 cylinder-bands https://www.openml.org/data/download/1854224/phpAz9Len -1 22044089 description https://api.openml.org/data/download/22044089/description.xml -1 22044090 predictions https://api.openml.org/data/download/22044090/predictions.arff area_under_roc_curve 0.866860661268556 [0.866861,0.866861] average_cost 0 f_measure 0.8061499215256738 [0.762557,0.838006] kappa 0.6010230179028134 kb_relative_information_score 0.42943348044734087 mean_absolute_error 0.29304175341853306 mean_prior_absolute_error 0.48794587945879536 weighted_recall 0.8074074074074075 [0.732456,0.862179] number_of_instances 540 [228,312] precision 0.8067436267436268 [0.795238,0.815152] predictive_accuracy 0.8074074074074075 prior_entropy 0.9824743303740947 relative_absolute_error 0.6005620003258558 root_mean_prior_squared_error 0.49391365607219145 root_mean_squared_error 0.3785097338535566 root_relative_squared_error 0.7663479824867058 total_cost 0 unweighted_recall 0.7973178137651822 [0.732456,0.862179] area_under_roc_curve 0.8793828892005608 [0.879383,0.879383] area_under_roc_curve 0.8751753155680225 [0.875175,0.875175] area_under_roc_curve 0.9593267882187938 [0.959327,0.959327] area_under_roc_curve 0.8302945301542777 [0.830295,0.830295] area_under_roc_curve 0.8948106591865357 [0.894811,0.894811] area_under_roc_curve 0.7896213183730715 [0.789621,0.789621] area_under_roc_curve 0.9593267882187938 [0.959327,0.959327] area_under_roc_curve 0.7573632538569425 [0.757363,0.757363] area_under_roc_curve 0.9247159090909092 [0.924716,0.924716] area_under_roc_curve 0.78125 [0.78125,0.78125] 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 0.8518518518518519 [0.826087,0.870968] f_measure 0.7956496178718401 [0.755556,0.825397] f_measure 0.9076334793111912 [0.893617,0.918033] f_measure 0.8116081449414784 [0.761905,0.848485] f_measure 0.7709150326797385 [0.7,0.823529] f_measure 0.7362514029180696 [0.666667,0.787879] f_measure 0.9259259259259259 [0.913043,0.935484] f_measure 0.6859538296580502 [0.638298,0.721311] f_measure 0.8309671156413055 [0.780488,0.865672] f_measure 0.7384960718294052 [0.666667,0.787879] kappa 0.697054698457223 kappa 0.5811001410437235 kappa 0.8117154811715482 kappa 0.612625538020086 kappa 0.5297532656023222 kappa 0.4576757532281205 kappa 0.8485273492286115 kappa 0.35983263598326376 kappa 0.6473149492017417 kappa 0.4553314121037463 kb_relative_information_score 0.48835447521127195 kb_relative_information_score 0.4423426579783694 kb_relative_information_score 0.5743466749594607 kb_relative_information_score 0.34966797041974906 kb_relative_information_score 0.417012520967162 kb_relative_information_score 0.3577422761316856 kb_relative_information_score 0.6064371134892711 kb_relative_information_score 0.27060280155016325 kb_relative_information_score 0.4598594529365819 kb_relative_information_score 0.32736108911228046 mean_absolute_error 0.26771439548246073 mean_absolute_error 0.2832890249061764 mean_absolute_error 0.22860739986347575 mean_absolute_error 0.3360640463262538 mean_absolute_error 0.2976092432039834 mean_absolute_error 0.32126051828278307 mean_absolute_error 0.2135255418505329 mean_absolute_error 0.3626323152361134 mean_absolute_error 0.28133938672669234 mean_absolute_error 0.33837566230685767 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.4856498564985656 mean_prior_absolute_error 0.4856498564985656 number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [22,32] number_of_instances 54 [22,32] precision 0.8518518518518519 [0.826087,0.870968] precision 0.7955597643097643 [0.772727,0.8125] precision 0.9084876543209878 [0.875,0.933333] precision 0.8179337231968811 [0.842105,0.8] precision 0.7851969616675499 [0.823529,0.756757] precision 0.7402951824004455 [0.736842,0.742857] precision 0.9259259259259259 [0.913043,0.935484] precision 0.6871913580246913 [0.625,0.733333] precision 0.8340852130325815 [0.842105,0.828571] precision 0.7383442265795206 [0.7,0.764706] predictive_accuracy 0.8518518518518519 predictive_accuracy 0.7962962962962963 predictive_accuracy 0.9074074074074074 predictive_accuracy 0.8148148148148148 predictive_accuracy 0.7777777777777777 predictive_accuracy 0.7407407407407408 predictive_accuracy 0.9259259259259259 predictive_accuracy 0.6851851851851852 predictive_accuracy 0.8333333333333333 predictive_accuracy 0.7407407407407408 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9757955887617137 prior_entropy 0.9757955887617137 relative_absolute_error 0.5480112552091656 relative_absolute_error 0.5798925151037879 relative_absolute_error 0.46795925158792834 relative_absolute_error 0.6879229618042231 relative_absolute_error 0.6092059959500752 relative_absolute_error 0.657620146111378 relative_absolute_error 0.4370866945643719 relative_absolute_error 0.7423081971136208 relative_absolute_error 0.5793049930151133 relative_absolute_error 0.6967481978610592 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.4915838450298872 root_mean_prior_squared_error 0.4915838450298872 root_mean_squared_error 0.3618792610564473 root_mean_squared_error 0.37441636486459345 root_mean_squared_error 0.29965925442087776 root_mean_squared_error 0.39884492558589796 root_mean_squared_error 0.3736270196327061 root_mean_squared_error 0.4256902401303302 root_mean_squared_error 0.28370406825672173 root_mean_squared_error 0.45849027778035584 root_mean_squared_error 0.3429848094771775 root_mean_squared_error 0.42840376503197763 root_relative_squared_error 0.7318167115166283 root_relative_squared_error 0.7571700905802297 root_relative_squared_error 0.6059912068616854 root_relative_squared_error 0.8065711778985792 root_relative_squared_error 0.7555738232778019 root_relative_squared_error 0.8608595882158299 root_relative_squared_error 0.5737255505314461 root_relative_squared_error 0.9271900422478978 root_relative_squared_error 0.6977137530960253 root_relative_squared_error 0.8714764924911875 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 0.8485273492286115 [0.826087,0.870968] unweighted_recall 0.7889200561009817 [0.73913,0.83871] unweighted_recall 0.9081346423562412 [0.913043,0.903226] unweighted_recall 0.7994389901823282 [0.695652,0.903226] unweighted_recall 0.755960729312763 [0.608696,0.903226] unweighted_recall 0.723702664796634 [0.608696,0.83871] unweighted_recall 0.9242636746143057 [0.913043,0.935484] unweighted_recall 0.6809256661991585 [0.652174,0.709677] unweighted_recall 0.8167613636363636 [0.727273,0.90625] unweighted_recall 0.7244318181818181 [0.636364,0.8125] usercpu_time_millis 315.0819999999612 usercpu_time_millis 283.09999999999036 usercpu_time_millis 290.82800000003317 usercpu_time_millis 269.35600000001614 usercpu_time_millis 291.84400000002597 usercpu_time_millis 282.10999999998876 usercpu_time_millis 298.48800000007714 usercpu_time_millis 279.137999999989 usercpu_time_millis 303.75600000002123 usercpu_time_millis 283.8419999999928 usercpu_time_millis_testing 8.735999999998967 usercpu_time_millis_testing 8.647999999993772 usercpu_time_millis_testing 8.64200000000892 usercpu_time_millis_testing 8.970000000033451 usercpu_time_millis_testing 10.120000000028995 usercpu_time_millis_testing 8.221999999989293 usercpu_time_millis_testing 8.634000000029118 usercpu_time_millis_testing 8.827999999994063 usercpu_time_millis_testing 8.350000000007185 usercpu_time_millis_testing 8.651999999983673 usercpu_time_millis_training 306.34599999996226 usercpu_time_millis_training 274.4519999999966 usercpu_time_millis_training 282.18600000002425 usercpu_time_millis_training 260.3859999999827 usercpu_time_millis_training 281.723999999997 usercpu_time_millis_training 273.88799999999947 usercpu_time_millis_training 289.854000000048 usercpu_time_millis_training 270.30999999999494 usercpu_time_millis_training 295.40600000001405 usercpu_time_millis_training 275.19000000000915 wall_clock_time_millis 159.13629531860352 wall_clock_time_millis 141.94011688232422 wall_clock_time_millis 145.60174942016602 wall_clock_time_millis 135.03694534301758 wall_clock_time_millis 147.05395698547363 wall_clock_time_millis 143.15128326416016 wall_clock_time_millis 150.98905563354492 wall_clock_time_millis 140.38801193237305 wall_clock_time_millis 152.76789665222168 wall_clock_time_millis 144.28997039794922 wall_clock_time_millis_testing 4.388093948364258 wall_clock_time_millis_testing 4.328012466430664 wall_clock_time_millis_testing 4.32586669921875 wall_clock_time_millis_testing 4.494905471801758 wall_clock_time_millis_testing 5.160093307495117 wall_clock_time_millis_testing 4.116296768188477 wall_clock_time_millis_testing 4.321098327636719 wall_clock_time_millis_testing 4.461050033569336 wall_clock_time_millis_testing 4.178047180175781 wall_clock_time_millis_testing 4.357099533081055 wall_clock_time_millis_training 154.74820137023926 wall_clock_time_millis_training 137.61210441589355 wall_clock_time_millis_training 141.27588272094727 wall_clock_time_millis_training 130.54203987121582 wall_clock_time_millis_training 141.89386367797852 wall_clock_time_millis_training 139.03498649597168 wall_clock_time_millis_training 146.6679573059082 wall_clock_time_millis_training 135.9269618988037 wall_clock_time_millis_training 148.5898494720459 wall_clock_time_millis_training 139.93287086486816 weighted_recall 0.8518518518518519 [0.826087,0.870968] weighted_recall 0.7962962962962963 [0.73913,0.83871] weighted_recall 0.9074074074074074 [0.913043,0.903226] weighted_recall 0.8148148148148148 [0.695652,0.903226] weighted_recall 0.7777777777777778 [0.608696,0.903226] weighted_recall 0.7407407407407407 [0.608696,0.83871] weighted_recall 0.9259259259259259 [0.913043,0.935484] weighted_recall 0.6851851851851852 [0.652174,0.709677] weighted_recall 0.8333333333333334 [0.727273,0.90625] weighted_recall 0.7407407407407407 [0.636364,0.8125]