10228498 6138 Felix Neutatz 10101 Supervised Classification 12647 sklearn.pipeline.C58b630419e517(n3=sklearn.compose._column_transformer.C3771de2902eab9(n4=sklearn.preprocessing._function_transformer.C3771de2902e830),n5=fastsklearnfeature.transformations.mdlp_discretization.MDLPDiscretizerTransformation.C58b630419e4b0,c=sklearn.linear_model.logistic.LogisticRegression)(1) 8153726 C 0.001 9801 class_weight "balanced" 9801 dual false 9801 fit_intercept true 9801 intercept_scaling 1 9801 max_iter 10000 9801 multi_class "auto" 9801 n_jobs null 9801 penalty "l2" 9801 random_state 26840 9801 solver "lbfgs" 9801 tol 0.0001 9801 verbose 0 9801 warm_start false 9801 memory null 12647 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "n3", "step_name": "n3"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "n5", "step_name": "n5"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "c", "step_name": "c"}}] 12647 n_jobs null 12648 remainder "drop" 12648 sparse_threshold 0.3 12648 transformer_weights null 12648 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "n4", "step_name": "n4", "argument_1": [0]}}] 12648 accept_sparse false 12649 check_inverse true 12649 func {"oml-python:serialized_object": "function", "value": "fastsklearnfeature.candidates.Identity.identity"} 12649 inv_kw_args null 12649 inverse_func null 12649 kw_args null 12649 pass_y "deprecated" 12649 validate false 12649 ComplexityDriven openml-python Sklearn_0.20.3. 1464 blood-transfusion-service-center https://www.openml.org/data/download/1586225/php0iVrYT -1 21378291 description https://api.openml.org/data/download/21378291/description.xml -1 21378292 predictions https://api.openml.org/data/download/21378292/predictions.arff area_under_roc_curve 0.6594322885866352 [0.659432,0.659432] average_cost 0 f_measure 0.6645199013032912 [0.715037,0.502752] kappa 0.2682233004100965 kb_relative_information_score -0.6963427817907131 mean_absolute_error 0.4973030419617903 mean_prior_absolute_error 0.3630445632798566 number_of_instances 748 [570,178] precision 0.7688613419891019 [0.892388,0.373297] predictive_accuracy 0.6377005347593583 prior_entropy 0.7916465694609683 recall 0.6377005347593583 [0.596491,0.769663] relative_absolute_error 1.3698126683650105 root_mean_prior_squared_error 0.4258399633559147 root_mean_squared_error 0.49735288050335863 root_relative_squared_error 1.1679337856970315 total_cost 0 area_under_roc_curve 0.695906432748538 [0.695906,0.695906] area_under_roc_curve 0.7602339181286549 [0.760234,0.760234] area_under_roc_curve 0.6783625730994152 [0.678363,0.678363] area_under_roc_curve 0.6403508771929824 [0.640351,0.640351] area_under_roc_curve 0.7046783625730996 [0.704678,0.704678] area_under_roc_curve 0.6505847953216374 [0.650585,0.650585] area_under_roc_curve 0.6505847953216374 [0.650585,0.650585] area_under_roc_curve 0.6345029239766082 [0.634503,0.634503] area_under_roc_curve 0.6599587203302374 [0.659959,0.659959] area_under_roc_curve 0.7569659442724459 [0.756966,0.756966] 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 0.6786111111111113 [0.729167,0.518519] f_measure 0.7156363636363636 [0.757895,0.581818] f_measure 0.6536170212765957 [0.702128,0.5] f_measure 0.6536263736263735 [0.714286,0.461538] f_measure 0.6909161641703948 [0.742268,0.528302] f_measure 0.6414545454545455 [0.694737,0.472727] f_measure 0.6414545454545455 [0.694737,0.472727] f_measure 0.5883661816172409 [0.629213,0.459016] f_measure 0.6639732516021175 [0.721649,0.470588] f_measure 0.7138194798572156 [0.757895,0.566038] kappa 0.2919389978213508 kappa 0.38238453276047274 kappa 0.2584745762711865 kappa 0.21524663677130054 kappa 0.3093922651933701 kappa 0.2212674543501611 kappa 0.2212674543501611 kappa 0.18235877106045603 kappa 0.23682200152788377 kappa 0.369162342475908 kb_relative_information_score -0.6871154608034833 kb_relative_information_score -0.6856385640110156 kb_relative_information_score -0.6884946904606654 kb_relative_information_score -0.688033381268117 kb_relative_information_score -0.6864376507994531 kb_relative_information_score -0.6889752391456925 kb_relative_information_score -0.6889752391456925 kb_relative_information_score -0.6920804416705721 kb_relative_information_score -0.7310170748783807 kb_relative_information_score -0.728993803123842 mean_absolute_error 0.4970839436816729 mean_absolute_error 0.4966751680039134 mean_absolute_error 0.49746352793925497 mean_absolute_error 0.4973387503662751 mean_absolute_error 0.49689740513413044 mean_absolute_error 0.49759683369543256 mean_absolute_error 0.49759683369543256 mean_absolute_error 0.4984504468582053 mean_absolute_error 0.4972333113849837 mean_absolute_error 0.4966850289440197 mean_prior_absolute_error 0.36410666666666686 mean_prior_absolute_error 0.36410666666666686 mean_prior_absolute_error 0.36410666666666686 mean_prior_absolute_error 0.36410666666666686 mean_prior_absolute_error 0.36410666666666686 mean_prior_absolute_error 0.36410666666666686 mean_prior_absolute_error 0.36410666666666686 mean_prior_absolute_error 0.36410666666666686 mean_prior_absolute_error 0.35873873873873896 mean_prior_absolute_error 0.35873873873873896 number_of_instances 75 [57,18] number_of_instances 75 [57,18] number_of_instances 75 [57,18] number_of_instances 75 [57,18] number_of_instances 75 [57,18] number_of_instances 75 [57,18] number_of_instances 75 [57,18] number_of_instances 75 [57,18] number_of_instances 74 [57,17] number_of_instances 74 [57,17] precision 0.7753846153846153 [0.897436,0.388889] precision 0.8237837837837838 [0.947368,0.432432] precision 0.7662588904694168 [0.891892,0.368421] precision 0.7334863701578191 [0.853659,0.352941] precision 0.7800000000000001 [0.9,0.4] precision 0.7443243243243243 [0.868421,0.351351] precision 0.7443243243243243 [0.868421,0.351351] precision 0.743139534883721 [0.875,0.325581] precision 0.7550675675675675 [0.875,0.352941] precision 0.8254504504504505 [0.947368,0.416667] predictive_accuracy 0.6533333333333333 predictive_accuracy 0.6933333333333332 predictive_accuracy 0.6266666666666666 predictive_accuracy 0.6266666666666666 predictive_accuracy 0.6666666666666667 predictive_accuracy 0.6133333333333334 predictive_accuracy 0.6133333333333334 predictive_accuracy 0.56 predictive_accuracy 0.6351351351351352 predictive_accuracy 0.6891891891891891 prior_entropy 0.7950473279640615 prior_entropy 0.7950473279640615 prior_entropy 0.7950473279640615 prior_entropy 0.7950473279640615 prior_entropy 0.7950473279640615 prior_entropy 0.7950473279640615 prior_entropy 0.7950473279640615 prior_entropy 0.7950473279640615 prior_entropy 0.7778597106646706 prior_entropy 0.7778597106646706 recall 0.6533333333333333 [0.614035,0.777778] recall 0.6933333333333334 [0.631579,0.888889] recall 0.6266666666666667 [0.578947,0.777778] recall 0.6266666666666667 [0.614035,0.666667] recall 0.6666666666666666 [0.631579,0.777778] recall 0.6133333333333333 [0.578947,0.722222] recall 0.6133333333333333 [0.578947,0.722222] recall 0.56 [0.491228,0.777778] recall 0.6351351351351351 [0.614035,0.705882] recall 0.6891891891891891 [0.631579,0.882353] relative_absolute_error 1.3652151668421508 relative_absolute_error 1.364092485729218 relative_absolute_error 1.3662576752396405 relative_absolute_error 1.3659149801329504 relative_absolute_error 1.3647028484348822 relative_absolute_error 1.3666237925573979 relative_absolute_error 1.3666237925573979 relative_absolute_error 1.3689681966590512 relative_absolute_error 1.3860597077783317 relative_absolute_error 1.3845313463783566 root_mean_prior_squared_error 0.4270852113779844 root_mean_prior_squared_error 0.4270852113779844 root_mean_prior_squared_error 0.4270852113779844 root_mean_prior_squared_error 0.4270852113779844 root_mean_prior_squared_error 0.4270852113779844 root_mean_prior_squared_error 0.4270852113779844 root_mean_prior_squared_error 0.4270852113779844 root_mean_prior_squared_error 0.4270852113779844 root_mean_prior_squared_error 0.4207539065176338 root_mean_prior_squared_error 0.4207539065176338 root_mean_squared_error 0.49713198760540267 root_mean_squared_error 0.49671559632130713 root_mean_squared_error 0.49751373265662735 root_mean_squared_error 0.49739365325686824 root_mean_squared_error 0.4969442836353563 root_mean_squared_error 0.49765029464699256 root_mean_squared_error 0.4976502946469925 root_mean_squared_error 0.49850496054585125 root_mean_squared_error 0.49728581791374316 root_mean_squared_error 0.49672637739358205 root_relative_squared_error 1.1640112426309808 root_relative_squared_error 1.1630362819603641 root_relative_squared_error 1.1649050807716015 root_relative_squared_error 1.164623920486581 root_relative_squared_error 1.163571742584981 root_relative_squared_error 1.1652248342697957 root_relative_squared_error 1.1652248342697957 root_relative_squared_error 1.1672259944038614 root_relative_squared_error 1.18189233708969 root_relative_squared_error 1.180562722529979 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 46.76372400000028 usercpu_time_millis 16.190558999999993 usercpu_time_millis 10.490588999999773 usercpu_time_millis 7.98664899999979 usercpu_time_millis 7.59162499999988 usercpu_time_millis 8.60897699999974 usercpu_time_millis 9.195897999999758 usercpu_time_millis 9.338282999999947 usercpu_time_millis 9.531466000000322 usercpu_time_millis 9.364413999999766 usercpu_time_millis_testing 2.1209560000001737 usercpu_time_millis_testing 0.8397369999997295 usercpu_time_millis_testing 0.6041039999997722 usercpu_time_millis_testing 0.5325809999998654 usercpu_time_millis_testing 0.5866389999997779 usercpu_time_millis_testing 0.6138499999996938 usercpu_time_millis_testing 0.5941989999995734 usercpu_time_millis_testing 0.5873020000000118 usercpu_time_millis_testing 0.6212400000000784 usercpu_time_millis_testing 0.6068780000001439 usercpu_time_millis_training 44.64276800000011 usercpu_time_millis_training 15.350822000000264 usercpu_time_millis_training 9.886485 usercpu_time_millis_training 7.454067999999925 usercpu_time_millis_training 7.004986000000102 usercpu_time_millis_training 7.995127000000046 usercpu_time_millis_training 8.601699000000185 usercpu_time_millis_training 8.750980999999936 usercpu_time_millis_training 8.910226000000243 usercpu_time_millis_training 8.757535999999622