10551058 8323 Heinrich Peters 14 Supervised Classification 18601 sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,logisticregression=sklearn.linear_model.logistic.LogisticRegression)(2) 8275617 add_indicator false 12737 copy true 12737 fill_value null 12737 missing_values NaN 12737 strategy "median" 12737 verbose 0 12737 C 1.0 13106 class_weight null 13106 dual false 13106 fit_intercept true 13106 intercept_scaling 1 13106 l1_ratio null 13106 max_iter 100 13106 multi_class "warn" 13106 n_jobs null 13106 penalty "l2" 13106 random_state 1 13106 solver "warn" 13106 tol 0.0001 13106 verbose 0 13106 warm_start false 13106 copy true 13294 with_mean true 13294 with_std true 13294 memory null 18601 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": "logisticregression", "step_name": "logisticregression"}}] 18601 verbose false 18601 openml-python Sklearn_0.21.2. 14 mfeat-fourier https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff -1 22027071 description https://api.openml.org/data/download/22027071/description.xml -1 22027072 predictions https://api.openml.org/data/download/22027072/predictions.arff area_under_roc_curve 0.974706388888889 [0.999917,0.948644,0.994394,0.985711,0.962003,0.988694,0.944531,0.991019,0.99635,0.9358] average_cost 0 f_measure 0.8170757969074977 [0.987593,0.754011,0.923457,0.8933,0.793017,0.919192,0.552764,0.862471,0.950249,0.534704] kappa 0.7988888888888889 kb_relative_information_score 0.7949503795311176 mean_absolute_error 0.0592211308533956 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.819 [0.995,0.705,0.935,0.9,0.795,0.91,0.55,0.925,0.955,0.52] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.8168376150404169 [0.980296,0.810345,0.912195,0.8867,0.791045,0.928571,0.555556,0.80786,0.945545,0.550265] predictive_accuracy 0.8190000000000001 prior_entropy 3.3219280948872383 relative_absolute_error 0.3290062825188543 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.162118043065743 root_relative_squared_error 0.5403934768858017 total_cost 0 unweighted_recall 0.819 [0.995,0.705,0.935,0.9,0.795,0.91,0.55,0.925,0.955,0.52] area_under_roc_curve 0.976 [1,0.959722,0.999167,0.988611,0.964722,1,0.926389,0.989444,0.999722,0.932222] area_under_roc_curve 0.9702222222222222 [1,0.926667,0.998611,0.9825,0.928056,0.967222,0.950833,0.993333,0.994444,0.960556] area_under_roc_curve 0.9703888888888887 [1,0.957222,0.998056,0.949722,0.983611,0.979444,0.898333,0.9925,1,0.945] area_under_roc_curve 0.9868611111111111 [1,0.968333,0.9825,1,0.982778,0.993056,0.983611,0.9925,0.996667,0.969167] area_under_roc_curve 0.9708055555555555 [1,0.921944,0.998611,0.966667,0.978056,0.991944,0.956111,0.988056,1,0.906667] area_under_roc_curve 0.9744722222222224 [1,0.951389,0.998056,0.987222,0.933333,0.996389,0.960278,0.991667,0.999167,0.927222] area_under_roc_curve 0.9767222222222222 [1,0.949722,0.9875,0.994722,0.977778,0.99,0.954167,0.985556,0.999722,0.928056] area_under_roc_curve 0.9821666666666666 [1,0.971944,0.998889,0.995833,0.968889,0.986389,0.946389,0.995278,0.998056,0.96] area_under_roc_curve 0.9729166666666669 [1,0.921667,1,0.997778,0.978333,0.983889,0.936667,0.999167,1,0.911667] area_under_roc_curve 0.9717222222222222 [1,0.965278,0.983056,0.995833,0.942222,0.999722,0.936111,0.991111,0.974444,0.929444] 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 0.8100187032073471 [0.974359,0.857143,0.95,0.842105,0.878049,0.97561,0.410256,0.85,0.930233,0.432432] f_measure 0.8220562187043644 [0.97561,0.705882,0.952381,0.829268,0.769231,0.9,0.578947,0.837209,0.974359,0.697674] f_measure 0.7941219758611783 [1,0.761905,0.894737,0.820513,0.818182,0.878049,0.533333,0.871795,0.97561,0.387097] f_measure 0.8547533092306611 [1,0.756757,0.974359,0.97561,0.816327,0.857143,0.685714,0.820513,0.95,0.711111] f_measure 0.7810736922932044 [0.97561,0.571429,0.9,0.829268,0.756757,0.871795,0.585366,0.833333,0.974359,0.512821] f_measure 0.8150098906311404 [1,0.777778,0.904762,0.904762,0.769231,0.926829,0.512821,0.930233,0.95,0.473684] f_measure 0.8113141096067926 [1,0.756757,0.871795,0.926829,0.8,0.926829,0.55,0.844444,0.95,0.486486] f_measure 0.8432810158034805 [0.97561,0.833333,0.95,0.952381,0.789474,0.923077,0.666667,0.863636,0.923077,0.555556] f_measure 0.8363040731911078 [1,0.685714,0.97561,0.97561,0.789474,0.95,0.526316,0.888889,1,0.571429] f_measure 0.7875170492670567 [0.97561,0.8,0.863636,0.864865,0.722222,0.974359,0.473684,0.883721,0.878049,0.439024] kappa 0.7944444444444444 kappa 0.8055555555555555 kappa 0.7777777777777778 kappa 0.8388888888888889 kappa 0.7611111111111112 kappa 0.7999999999999999 kappa 0.7944444444444444 kappa 0.8277777777777777 kappa 0.8222222222222222 kappa 0.7666666666666667 kb_relative_information_score 0.7895658653454969 kb_relative_information_score 0.787797069052844 kb_relative_information_score 0.7810548866451056 kb_relative_information_score 0.8140488877854923 kb_relative_information_score 0.7802752860713427 kb_relative_information_score 0.8107345466825759 kb_relative_information_score 0.7908788399816506 kb_relative_information_score 0.8119712742589704 kb_relative_information_score 0.799432481523477 kb_relative_information_score 0.7837446579639453 mean_absolute_error 0.06017126425854832 mean_absolute_error 0.06139877751517318 mean_absolute_error 0.06154328612094023 mean_absolute_error 0.057275139575722986 mean_absolute_error 0.06059746625447473 mean_absolute_error 0.054946338892588695 mean_absolute_error 0.05871913858866533 mean_absolute_error 0.056344037102229586 mean_absolute_error 0.05980881948189363 mean_absolute_error 0.061407040743718805 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] precision 0.8077800600858887 [1,0.818182,0.95,0.888889,0.857143,0.952381,0.421053,0.85,0.869565,0.470588] precision 0.8263505932155817 [0.952381,0.857143,0.909091,0.809524,0.789474,0.9,0.611111,0.782609,1,0.652174] precision 0.7993537631958684 [1,0.727273,0.944444,0.842105,0.75,0.857143,0.48,0.894737,0.952381,0.545455] precision 0.8697670799717346 [1,0.823529,1,0.952381,0.689655,1,0.8,0.842105,0.95,0.64] precision 0.7858867757629368 [0.952381,0.666667,0.9,0.809524,0.823529,0.894737,0.571429,0.714286,1,0.526316] precision 0.8142389323110147 [1,0.875,0.863636,0.863636,0.789474,0.904762,0.526316,0.869565,0.95,0.5] precision 0.811720182809966 [1,0.823529,0.894737,0.904762,0.8,0.904762,0.55,0.76,0.95,0.529412] precision 0.8493708703577124 [0.952381,0.9375,0.95,0.909091,0.833333,0.947368,0.6,0.791667,0.947368,0.625] precision 0.838910533910534 [1,0.8,0.952381,0.952381,0.833333,0.95,0.555556,0.8,1,0.545455] precision 0.790952533187188 [0.952381,0.8,0.791667,0.941176,0.8125,1,0.5,0.826087,0.857143,0.428571] predictive_accuracy 0.815 predictive_accuracy 0.825 predictive_accuracy 0.8 predictive_accuracy 0.855 predictive_accuracy 0.785 predictive_accuracy 0.82 predictive_accuracy 0.815 predictive_accuracy 0.845 predictive_accuracy 0.84 predictive_accuracy 0.79 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 relative_absolute_error 0.3342848014363799 relative_absolute_error 0.3411043195287402 relative_absolute_error 0.341907145116335 relative_absolute_error 0.31819521986512805 relative_absolute_error 0.3366525903026378 relative_absolute_error 0.3052574382921598 relative_absolute_error 0.3262174366036966 relative_absolute_error 0.31302242834572025 relative_absolute_error 0.3322712193438539 relative_absolute_error 0.3411502263539938 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_squared_error 0.16313572558683448 root_mean_squared_error 0.16673008417998675 root_mean_squared_error 0.16735919855541512 root_mean_squared_error 0.1529357181199509 root_mean_squared_error 0.17067054002958826 root_mean_squared_error 0.15507833208753022 root_mean_squared_error 0.16512381922451208 root_mean_squared_error 0.15381889055017012 root_mean_squared_error 0.15795515028168894 root_mean_squared_error 0.167207353726891 root_relative_squared_error 0.5437857519561152 root_relative_squared_error 0.5557669472666228 root_relative_squared_error 0.5578639951847173 root_relative_squared_error 0.5097857270665034 root_relative_squared_error 0.5689018000986279 root_relative_squared_error 0.516927773625101 root_relative_squared_error 0.5504127307483739 root_relative_squared_error 0.5127296351672341 root_relative_squared_error 0.52651716760563 root_relative_squared_error 0.5573578457563036 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 0.8150000000000001 [0.95,0.9,0.95,0.8,0.9,1,0.4,0.85,1,0.4] unweighted_recall 0.825 [1,0.6,1,0.85,0.75,0.9,0.55,0.9,0.95,0.75] unweighted_recall 0.8 [1,0.8,0.85,0.8,0.9,0.9,0.6,0.85,1,0.3] unweighted_recall 0.8550000000000001 [1,0.7,0.95,1,1,0.75,0.6,0.8,0.95,0.8] unweighted_recall 0.7849999999999999 [1,0.5,0.9,0.85,0.7,0.85,0.6,1,0.95,0.5] unweighted_recall 0.82 [1,0.7,0.95,0.95,0.75,0.95,0.5,1,0.95,0.45] unweighted_recall 0.8150000000000001 [1,0.7,0.85,0.95,0.8,0.95,0.55,0.95,0.95,0.45] unweighted_recall 0.8450000000000001 [1,0.75,0.95,1,0.75,0.9,0.75,0.95,0.9,0.5] unweighted_recall 0.8400000000000001 [1,0.6,1,1,0.75,0.95,0.5,1,1,0.6] unweighted_recall 0.7900000000000001 [1,0.8,0.95,0.8,0.65,0.95,0.45,0.95,0.9,0.45] usercpu_time_millis 357.6636390062049 usercpu_time_millis 333.18508800584823 usercpu_time_millis 335.96477907849476 usercpu_time_millis 342.71742799319327 usercpu_time_millis 333.5949300089851 usercpu_time_millis 338.28313706908375 usercpu_time_millis 352.8532420168631 usercpu_time_millis 382.1320250281133 usercpu_time_millis 327.0901310024783 usercpu_time_millis 329.88246995955706 usercpu_time_millis_testing 0.7787229842506349 usercpu_time_millis_testing 0.824430026113987 usercpu_time_millis_testing 0.8248910307884216 usercpu_time_millis_testing 0.8768650004640222 usercpu_time_millis_testing 0.8495610090903938 usercpu_time_millis_testing 0.7998510263860226 usercpu_time_millis_testing 0.911083014216274 usercpu_time_millis_testing 0.917955010663718 usercpu_time_millis_testing 0.893512973561883 usercpu_time_millis_testing 0.8472710032947361 usercpu_time_millis_training 356.88491602195427 usercpu_time_millis_training 332.36065797973424 usercpu_time_millis_training 335.13988804770634 usercpu_time_millis_training 341.84056299272925 usercpu_time_millis_training 332.7453689998947 usercpu_time_millis_training 337.4832860426977 usercpu_time_millis_training 351.9421590026468 usercpu_time_millis_training 381.21407001744956 usercpu_time_millis_training 326.1966180289164 usercpu_time_millis_training 329.0351989562623 wall_clock_time_millis 358.8685989379883 wall_clock_time_millis 335.16883850097656 wall_clock_time_millis 335.97278594970703 wall_clock_time_millis 342.731237411499 wall_clock_time_millis 333.6021900177002 wall_clock_time_millis 338.2883071899414 wall_clock_time_millis 352.8742790222168 wall_clock_time_millis 382.5211524963379 wall_clock_time_millis 327.13961601257324 wall_clock_time_millis 330.244779586792 wall_clock_time_millis_testing 0.7851123809814453 wall_clock_time_millis_testing 0.8296966552734375 wall_clock_time_millis_testing 0.8301734924316406 wall_clock_time_millis_testing 0.8845329284667969 wall_clock_time_millis_testing 0.8528232574462891 wall_clock_time_millis_testing 0.8032321929931641 wall_clock_time_millis_testing 0.9143352508544922 wall_clock_time_millis_testing 0.9202957153320312 wall_clock_time_millis_testing 0.8969306945800781 wall_clock_time_millis_testing 0.8516311645507812 wall_clock_time_millis_training 358.08348655700684 wall_clock_time_millis_training 334.3391418457031 wall_clock_time_millis_training 335.1426124572754 wall_clock_time_millis_training 341.8467044830322 wall_clock_time_millis_training 332.7493667602539 wall_clock_time_millis_training 337.48507499694824 wall_clock_time_millis_training 351.9599437713623 wall_clock_time_millis_training 381.60085678100586 wall_clock_time_millis_training 326.24268531799316 wall_clock_time_millis_training 329.3931484222412 weighted_recall 0.815 [0.95,0.9,0.95,0.8,0.9,1,0.4,0.85,1,0.4] weighted_recall 0.825 [1,0.6,1,0.85,0.75,0.9,0.55,0.9,0.95,0.75] weighted_recall 0.8 [1,0.8,0.85,0.8,0.9,0.9,0.6,0.85,1,0.3] weighted_recall 0.855 [1,0.7,0.95,1,1,0.75,0.6,0.8,0.95,0.8] weighted_recall 0.785 [1,0.5,0.9,0.85,0.7,0.85,0.6,1,0.95,0.5] weighted_recall 0.82 [1,0.7,0.95,0.95,0.75,0.95,0.5,1,0.95,0.45] weighted_recall 0.815 [1,0.7,0.85,0.95,0.8,0.95,0.55,0.95,0.95,0.45] weighted_recall 0.845 [1,0.75,0.95,1,0.75,0.9,0.75,0.95,0.9,0.5] weighted_recall 0.84 [1,0.6,1,1,0.75,0.95,0.5,1,1,0.6] weighted_recall 0.79 [1,0.8,0.95,0.8,0.65,0.95,0.45,0.95,0.9,0.45]