10396831 8323 Heinrich Peters 9977 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) 8235558 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 0.10267761840714641 13389 cache_size 200 13389 class_weight null 13389 coef0 0.6852838957856056 13389 decision_function_shape "ovr" 13389 degree 4 13389 gamma 0.006747269765424403 13389 kernel "rbf" 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, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false]}}] 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. 1486 nomao https://www.openml.org/data/download/1592278/phpDYCOet -1 21715401 description https://api.openml.org/data/download/21715401/description.xml -1 21715402 predictions https://api.openml.org/data/download/21715402/predictions.arff area_under_roc_curve 0.9334286078452799 [0.933429,0.933429] average_cost 0 f_measure 0.9479350084502022 [0.908223,0.963813] kappa 0.8720410429545663 kb_relative_information_score 0.8620793854182494 mean_absolute_error 0.051907732482228346 mean_prior_absolute_error 0.4080904194746198 number_of_instances 34465 [9844,24621] precision 0.9478510988114215 [0.917401,0.960026] predictive_accuracy 0.9480922675177716 prior_entropy 0.8629999933345911 recall 0.9480922675177716 [0.899228,0.967629] relative_absolute_error 0.12719664565773178 root_mean_prior_squared_error 0.4517106852187937 root_mean_squared_error 0.2278326852807304 root_relative_squared_error 0.5043774538350266 total_cost 0 area_under_roc_curve 0.9308132309398611 [0.930813,0.930813] area_under_roc_curve 0.9382706478575876 [0.938271,0.938271] area_under_roc_curve 0.9300469677163957 [0.930047,0.930047] area_under_roc_curve 0.9359358698924156 [0.935936,0.935936] area_under_roc_curve 0.9351235222076064 [0.935124,0.935124] area_under_roc_curve 0.9272478254839412 [0.927248,0.927248] area_under_roc_curve 0.9357882084101101 [0.935788,0.935788] area_under_roc_curve 0.9366992101074545 [0.936699,0.936699] area_under_roc_curve 0.9356829499448528 [0.935683,0.935683] area_under_roc_curve 0.9286686083757669 [0.928669,0.928669] 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 0.9458721311290388 [0.904517,0.962394] f_measure 0.9500710271619248 [0.912513,0.965097] f_measure 0.9439318749378242 [0.901581,0.960876] f_measure 0.9496793349669398 [0.911418,0.964987] f_measure 0.9485480553031204 [0.909555,0.964148] f_measure 0.9453809469039479 [0.902958,0.962336] f_measure 0.9466694005861883 [0.906883,0.962571] f_measure 0.9507972853056764 [0.9132,0.965824] f_measure 0.9501992047765692 [0.912082,0.965434] f_measure 0.9481814199410765 [0.907475,0.964451] kappa 0.8669168325167449 kappa 0.8776103208929712 kappa 0.8624577126380057 kappa 0.8764088769585108 kappa 0.8737059192840151 kappa 0.8653179835882405 kappa 0.8694546472748833 kappa 0.8790294002423675 kappa 0.8775225919735151 kappa 0.8719665250887607 kb_relative_information_score 0.8565919263778077 kb_relative_information_score 0.8674450264387028 kb_relative_information_score 0.8512609889690067 kb_relative_information_score 0.866674357987765 kb_relative_information_score 0.8635916841840118 kb_relative_information_score 0.85579738602029 kb_relative_information_score 0.8581107969397495 kb_relative_information_score 0.8696778515370545 kb_relative_information_score 0.8681355775907471 kb_relative_information_score 0.8635087557518268 mean_absolute_error 0.053959965187119235 mean_absolute_error 0.04989846243109951 mean_absolute_error 0.0559907165651291 mean_absolute_error 0.0501885697708152 mean_absolute_error 0.05134899912967798 mean_absolute_error 0.0542658154381892 mean_absolute_error 0.053395240858966915 mean_absolute_error 0.049042367962855486 mean_absolute_error 0.04962275101567034 mean_absolute_error 0.051363900174114914 mean_prior_absolute_error 0.4080229059806574 mean_prior_absolute_error 0.4081472833897437 mean_prior_absolute_error 0.4081472833897437 mean_prior_absolute_error 0.4081472833897437 mean_prior_absolute_error 0.4081472833897437 mean_prior_absolute_error 0.40805842175852763 mean_prior_absolute_error 0.40805842175852763 mean_prior_absolute_error 0.40805842175852763 mean_prior_absolute_error 0.40805842175852763 mean_prior_absolute_error 0.40805842175852763 number_of_instances 3447 [984,2463] number_of_instances 3447 [985,2462] number_of_instances 3447 [985,2462] number_of_instances 3447 [985,2462] number_of_instances 3447 [985,2462] number_of_instances 3446 [984,2462] number_of_instances 3446 [984,2462] number_of_instances 3446 [984,2462] number_of_instances 3446 [984,2462] number_of_instances 3446 [984,2462] precision 0.9457811574880711 [0.9139,0.958518] precision 0.9500435838805243 [0.914373,0.964315] precision 0.9438698887741458 [0.905738,0.959126] precision 0.9496030280409478 [0.919421,0.961678] precision 0.9484775985146677 [0.915638,0.961616] precision 0.9453550336986415 [0.922587,0.954455] precision 0.9467461738197273 [0.903226,0.96414] precision 0.9507225062063395 [0.923157,0.96174] precision 0.9501238290540087 [0.922997,0.960966] precision 0.9483236661314747 [0.934338,0.953913] predictive_accuracy 0.9460400348128808 predictive_accuracy 0.9501015375689005 predictive_accuracy 0.944009283434871 predictive_accuracy 0.9498114302291847 predictive_accuracy 0.9486510008703221 predictive_accuracy 0.9457341845618107 predictive_accuracy 0.946604759141033 predictive_accuracy 0.9509576320371446 predictive_accuracy 0.9503772489843297 predictive_accuracy 0.9486360998258851 prior_entropy 0.862791736866817 prior_entropy 0.863175399426382 prior_entropy 0.863175399426382 prior_entropy 0.863175399426382 prior_entropy 0.863175399426382 prior_entropy 0.862901291120622 prior_entropy 0.862901291120622 prior_entropy 0.862901291120622 prior_entropy 0.862901291120622 prior_entropy 0.862901291120622 recall 0.9460400348128808 [0.895325,0.966301] recall 0.9501015375689005 [0.91066,0.965881] recall 0.9440092834348709 [0.897462,0.962632] recall 0.9498114302291848 [0.903553,0.968318] recall 0.9486510008703221 [0.903553,0.966694] recall 0.9457341845618108 [0.884146,0.970349] recall 0.946604759141033 [0.910569,0.961007] recall 0.9509576320371446 [0.903455,0.969943] recall 0.9503772489843296 [0.901423,0.969943] recall 0.948636099825885 [0.882114,0.975223] relative_absolute_error 0.13224739198754012 relative_absolute_error 0.12225601997563951 relative_absolute_error 0.1371826270656885 relative_absolute_error 0.12296681078945136 relative_absolute_error 0.1258099740446988 relative_absolute_error 0.13298540734518036 relative_absolute_error 0.13085195161236998 relative_absolute_error 0.12018467294831808 relative_absolute_error 0.12160697677019165 relative_absolute_error 0.12587388823581241 root_mean_prior_squared_error 0.4516359481339797 root_mean_prior_squared_error 0.45177362368332785 root_mean_prior_squared_error 0.45177362368332785 root_mean_prior_squared_error 0.45177362368332785 root_mean_prior_squared_error 0.45177362368332785 root_mean_prior_squared_error 0.4516752654560011 root_mean_prior_squared_error 0.4516752654560011 root_mean_prior_squared_error 0.4516752654560011 root_mean_prior_squared_error 0.4516752654560011 root_mean_prior_squared_error 0.4516752654560011 root_mean_squared_error 0.2322928435985905 root_mean_squared_error 0.22337963745851927 root_mean_squared_error 0.23662357567480274 root_mean_squared_error 0.22402805576716323 root_mean_squared_error 0.22660317546247666 root_mean_squared_error 0.23295024240852208 root_mean_squared_error 0.23107410252766733 root_mean_squared_error 0.22145511500720746 root_mean_squared_error 0.22276164619536806 root_mean_squared_error 0.22663605223819733 root_relative_squared_error 0.5143364795436519 root_relative_squared_error 0.4944503745864941 root_relative_squared_error 0.5237658049746277 root_relative_squared_error 0.49588564719793465 root_relative_squared_error 0.5015856694221592 root_relative_squared_error 0.5157471755141181 root_relative_squared_error 0.5115934393582083 root_relative_squared_error 0.49029719345740885 root_relative_squared_error 0.4931898273651823 root_relative_squared_error 0.501767684819736 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 93334.86949899816 usercpu_time_millis 91426.98996100808 usercpu_time_millis 89020.17044997774 usercpu_time_millis 91705.0509180117 usercpu_time_millis 83290.77602698817 usercpu_time_millis 94076.39642700087 usercpu_time_millis 91932.94649099698 usercpu_time_millis 91773.91571397311 usercpu_time_millis 94749.06104296679 usercpu_time_millis 91168.55810303241 usercpu_time_millis_testing 8636.518165003508 usercpu_time_millis_testing 8444.603370997356 usercpu_time_millis_testing 5913.677634001942 usercpu_time_millis_testing 8486.055768997176 usercpu_time_millis_testing 5878.686227981234 usercpu_time_millis_testing 8640.522906003753 usercpu_time_millis_testing 8360.782704985468 usercpu_time_millis_testing 8506.609312986257 usercpu_time_millis_testing 8619.199184991885 usercpu_time_millis_testing 8451.852630008943 usercpu_time_millis_training 84698.35133399465 usercpu_time_millis_training 82982.38659001072 usercpu_time_millis_training 83106.4928159758 usercpu_time_millis_training 83218.99514901452 usercpu_time_millis_training 77412.08979900694 usercpu_time_millis_training 85435.87352099712 usercpu_time_millis_training 83572.16378601152 usercpu_time_millis_training 83267.30640098685 usercpu_time_millis_training 86129.8618579749 usercpu_time_millis_training 82716.70547302347 wall_clock_time_millis 93335.45017242432 wall_clock_time_millis 91428.32827568054 wall_clock_time_millis 89020.19333839417 wall_clock_time_millis 91705.4603099823 wall_clock_time_millis 83291.64838790894 wall_clock_time_millis 94077.68702507019 wall_clock_time_millis 91934.01503562927 wall_clock_time_millis 91774.4882106781 wall_clock_time_millis 94749.77993965149 wall_clock_time_millis 91168.78390312195 wall_clock_time_millis_testing 8636.679649353027 wall_clock_time_millis_testing 8444.615125656128 wall_clock_time_millis_testing 5913.6834144592285 wall_clock_time_millis_testing 8486.101627349854 wall_clock_time_millis_testing 5878.687858581543 wall_clock_time_millis_testing 8640.678882598877 wall_clock_time_millis_testing 8360.792875289917 wall_clock_time_millis_testing 8506.620168685913 wall_clock_time_millis_testing 8619.212865829468 wall_clock_time_millis_testing 8451.86448097229 wall_clock_time_millis_training 84698.77052307129 wall_clock_time_millis_training 82983.71315002441 wall_clock_time_millis_training 83106.50992393494 wall_clock_time_millis_training 83219.35868263245 wall_clock_time_millis_training 77412.96052932739 wall_clock_time_millis_training 85437.00814247131 wall_clock_time_millis_training 83573.22216033936 wall_clock_time_millis_training 83267.86804199219 wall_clock_time_millis_training 86130.56707382202 wall_clock_time_millis_training 82716.91942214966