10559350 8323 Heinrich Peters 2079 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) 8276082 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 1.2019329859336583 17495 cache_size 200 17495 class_weight null 17495 coef0 -0.8056274588169823 17495 decision_function_shape "ovr" 17495 degree 2 17495 gamma 0.14660663245874161 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, true, true, true, true, false, true, true, true, true, true, true, true, true, true]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [true, false, true, true, true, false, false, false, false, true, false, false, false, false, false, false, false, false, false]}}] 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. 188 eucalyptus https://www.openml.org/data/download/3625/dataset_194_eucalyptus.arff -1 22043665 description https://api.openml.org/data/download/22043665/description.xml -1 22043666 predictions https://api.openml.org/data/download/22043666/predictions.arff area_under_roc_curve 0.9017623034532096 [0.981855,0.904031,0.861615,0.853815,0.909577] average_cost 0 f_measure 0.6178285821517111 [0.846995,0.509615,0.490119,0.644491,0.439024] kappa 0.5158890754533757 kb_relative_information_score 0.5278587310816107 mean_absolute_error 0.1831534033928644 mean_prior_absolute_error 0.313229771753801 weighted_recall 0.626358695652174 [0.861111,0.495327,0.476923,0.724299,0.342857] number_of_instances 736 [180,107,130,214,105] precision 0.6249687180489608 [0.833333,0.524752,0.504065,0.580524,0.610169] predictive_accuracy 0.626358695652174 prior_entropy 2.2620863489531073 relative_absolute_error 0.5847253994004862 root_mean_prior_squared_error 0.39571712668407916 root_mean_squared_error 0.3044139148878073 root_relative_squared_error 0.7692715183662904 total_cost 0 unweighted_recall 0.580103499823126 [0.861111,0.495327,0.476923,0.724299,0.342857] area_under_roc_curve 0.916300256444859 [0.991071,0.873016,0.862547,0.897574,0.936508] area_under_roc_curve 0.9184535768590826 [0.986111,0.903319,0.895334,0.896676,0.891775] area_under_roc_curve 0.9059358910793338 [0.996032,0.924964,0.885246,0.83479,0.90625] area_under_roc_curve 0.896748927870854 [0.975198,0.834055,0.852459,0.856643,0.970313] area_under_roc_curve 0.9102788272870239 [0.987103,0.935065,0.854981,0.861014,0.925] area_under_roc_curve 0.9068835008896485 [0.955357,0.901876,0.910467,0.863636,0.915625] area_under_roc_curve 0.8703847191253288 [0.973737,0.887097,0.788462,0.82326,0.871429] area_under_roc_curve 0.8945943755267661 [0.976768,0.892063,0.891026,0.831502,0.887097] area_under_roc_curve 0.9086112051644529 [0.99899,0.936508,0.860256,0.845238,0.91349] area_under_roc_curve 0.9027610063624205 [0.982828,0.963492,0.855128,0.826007,0.919355] 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 0.6101564722617354 [0.842105,0.315789,0.538462,0.72,0.4] f_measure 0.6449089306698003 [0.833333,0.608696,0.521739,0.72,0.375] f_measure 0.6488300244821983 [0.914286,0.608696,0.592593,0.64,0.307692] f_measure 0.5781526207058122 [0.777778,0.272727,0.518519,0.638298,0.5] f_measure 0.6006020499263743 [0.864865,0.47619,0.333333,0.625,0.555556] f_measure 0.6574834234939994 [0.810811,0.583333,0.521739,0.695652,0.555556] f_measure 0.5414481409001957 [0.777778,0.454545,0.48,0.612245,0.142857] f_measure 0.6063583616575686 [0.888889,0.6,0.47619,0.6,0.315789] f_measure 0.6651509598204058 [0.923077,0.625,0.434783,0.692308,0.5] f_measure 0.5933271058594439 [0.833333,0.555556,0.470588,0.461538,0.631579] kappa 0.5249643366619114 kappa 0.5622337908187411 kappa 0.5605700712589075 kappa 0.458834630809153 kappa 0.4925514305982502 kappa 0.5650129320479661 kappa 0.43024390243902444 kappa 0.5019493177387915 kappa 0.5859432799013563 kappa 0.4768275203057812 kb_relative_information_score 0.5402217742815387 kb_relative_information_score 0.5462275457870756 kb_relative_information_score 0.543413745824872 kb_relative_information_score 0.500056736963927 kb_relative_information_score 0.5389846135212101 kb_relative_information_score 0.5316273666851002 kb_relative_information_score 0.4706858371078198 kb_relative_information_score 0.5114575693543165 kb_relative_information_score 0.5537595515017365 kb_relative_information_score 0.5415983031786833 mean_absolute_error 0.17811161027809447 mean_absolute_error 0.17351079583110204 mean_absolute_error 0.17948373672405774 mean_absolute_error 0.19183589538381374 mean_absolute_error 0.18333152414657067 mean_absolute_error 0.18363471658503636 mean_absolute_error 0.19576967566495848 mean_absolute_error 0.19068927751927756 mean_absolute_error 0.17213011988443874 mean_absolute_error 0.183160135903193 mean_prior_absolute_error 0.3137031768610717 mean_prior_absolute_error 0.3137031768610717 mean_prior_absolute_error 0.3129080497501551 mean_prior_absolute_error 0.3129080497501551 mean_prior_absolute_error 0.3129080497501551 mean_prior_absolute_error 0.3129080497501551 mean_prior_absolute_error 0.31330486384559936 mean_prior_absolute_error 0.3133196531898768 mean_prior_absolute_error 0.3133196531898768 mean_prior_absolute_error 0.3133196531898768 number_of_instances 74 [18,11,13,21,11] number_of_instances 74 [18,11,13,21,11] number_of_instances 74 [18,11,13,22,10] number_of_instances 74 [18,11,13,22,10] number_of_instances 74 [18,11,13,22,10] number_of_instances 74 [18,11,13,22,10] number_of_instances 73 [18,11,13,21,10] number_of_instances 73 [18,10,13,21,11] number_of_instances 73 [18,10,13,21,11] number_of_instances 73 [18,10,13,21,11] precision 0.6325605778191985 [0.8,0.375,0.538462,0.62069,0.75] precision 0.6601506679092887 [0.833333,0.583333,0.6,0.62069,0.6] precision 0.6760068892421833 [0.941176,0.583333,0.571429,0.571429,0.666667] precision 0.586036036036036 [0.777778,0.272727,0.5,0.6,0.666667] precision 0.5990199345462504 [0.842105,0.5,0.363636,0.576923,0.625] precision 0.6601387825072035 [0.789474,0.538462,0.6,0.666667,0.625] precision 0.5376712328767124 [0.777778,0.454545,0.5,0.535714,0.25] precision 0.6179735474728388 [0.888889,0.6,0.625,0.517241,0.375] precision 0.7021294951918019 [0.857143,0.833333,0.5,0.580645,0.8] precision 0.6157860404435747 [0.833333,0.625,0.380952,0.5,0.75] predictive_accuracy 0.6351351351351352 predictive_accuracy 0.6621621621621621 predictive_accuracy 0.6621621621621621 predictive_accuracy 0.581081081081081 predictive_accuracy 0.6081081081081081 predictive_accuracy 0.6621621621621621 predictive_accuracy 0.5616438356164384 predictive_accuracy 0.6164383561643836 predictive_accuracy 0.684931506849315 predictive_accuracy 0.589041095890411 prior_entropy 2.270428889699664 prior_entropy 2.270428889699664 prior_entropy 2.2566414249020115 prior_entropy 2.2566414249020115 prior_entropy 2.2566414249020115 prior_entropy 2.2566414249020115 prior_entropy 2.2631003912333214 prior_entropy 2.263469802844284 prior_entropy 2.263469802844284 prior_entropy 2.263469802844284 relative_absolute_error 0.5677711397770573 relative_absolute_error 0.5531050006163757 relative_absolute_error 0.5735989753774902 relative_absolute_error 0.6130743377710711 relative_absolute_error 0.5858958383875191 relative_absolute_error 0.5868647889744655 relative_absolute_error 0.6248536114697418 relative_absolute_error 0.6086093724983053 relative_absolute_error 0.5493754321888167 relative_absolute_error 0.5845791479674433 root_mean_prior_squared_error 0.39631483628344655 root_mean_prior_squared_error 0.39631483628344655 root_mean_prior_squared_error 0.395310412647401 root_mean_prior_squared_error 0.395310412647401 root_mean_prior_squared_error 0.395310412647401 root_mean_prior_squared_error 0.395310412647401 root_mean_prior_squared_error 0.3958119963352585 root_mean_prior_squared_error 0.3958306781784102 root_mean_prior_squared_error 0.3958306781784102 root_mean_prior_squared_error 0.3958306781784102 root_mean_squared_error 0.2993136822518457 root_mean_squared_error 0.29940022092683505 root_mean_squared_error 0.2966625334134576 root_mean_squared_error 0.31267102064205576 root_mean_squared_error 0.3013551787992268 root_mean_squared_error 0.3050419663248318 root_mean_squared_error 0.32893020991121114 root_mean_squared_error 0.30996091468904163 root_mean_squared_error 0.29113090683065623 root_mean_squared_error 0.2981300555096898 root_relative_squared_error 0.7552421833579172 root_relative_squared_error 0.7554605417615563 root_relative_squared_error 0.7504546400048084 root_relative_squared_error 0.7909506318037319 root_relative_squared_error 0.7623254261911435 root_relative_squared_error 0.7716517363708186 root_relative_squared_error 0.831026378575455 root_relative_squared_error 0.783064405506576 root_relative_squared_error 0.7354935402440854 root_relative_squared_error 0.7531757186726077 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 0.5659895659895661 [0.888889,0.272727,0.538462,0.857143,0.272727] unweighted_recall 0.6122211122211123 [0.833333,0.636364,0.461538,0.857143,0.272727] unweighted_recall 0.6135819735819735 [0.888889,0.636364,0.615385,0.727273,0.2] unweighted_recall 0.5341569541569541 [0.777778,0.272727,0.538462,0.681818,0.4] unweighted_recall 0.5665889665889666 [0.888889,0.454545,0.307692,0.681818,0.5] unweighted_recall 0.6317016317016317 [0.833333,0.636364,0.461538,0.727273,0.5] unweighted_recall 0.5016294816294817 [0.777778,0.454545,0.461538,0.714286,0.1] unweighted_recall 0.5721034521034521 [0.888889,0.6,0.384615,0.714286,0.272727] unweighted_recall 0.6210789210789212 [1,0.5,0.384615,0.857143,0.363636] unweighted_recall 0.5845487845487846 [0.833333,0.5,0.615385,0.428571,0.545455] usercpu_time_millis 354.5599999999993 usercpu_time_millis 365.5339999999967 usercpu_time_millis 358.1999999999965 usercpu_time_millis 376.36799999999937 usercpu_time_millis 353.84400000000227 usercpu_time_millis 342.0060000000049 usercpu_time_millis 342.3580000000044 usercpu_time_millis 343.9819999999969 usercpu_time_millis 351.85999999999495 usercpu_time_millis 388.3900000000011 usercpu_time_millis_testing 9.26199999999966 usercpu_time_millis_testing 8.761999999997272 usercpu_time_millis_testing 8.48999999999478 usercpu_time_millis_testing 8.592000000000155 usercpu_time_millis_testing 8.538000000001489 usercpu_time_millis_testing 8.316000000000656 usercpu_time_millis_testing 8.484000000002823 usercpu_time_millis_testing 8.545999999995502 usercpu_time_millis_testing 8.615999999996404 usercpu_time_millis_testing 9.154000000002327 usercpu_time_millis_training 345.29799999999966 usercpu_time_millis_training 356.7719999999994 usercpu_time_millis_training 349.71000000000174 usercpu_time_millis_training 367.7759999999992 usercpu_time_millis_training 345.3060000000008 usercpu_time_millis_training 333.69000000000426 usercpu_time_millis_training 333.87400000000156 usercpu_time_millis_training 335.4360000000014 usercpu_time_millis_training 343.24399999999855 usercpu_time_millis_training 379.2359999999988 wall_clock_time_millis 178.2996654510498 wall_clock_time_millis 184.97490882873535 wall_clock_time_millis 181.44893646240234 wall_clock_time_millis 194.75817680358887 wall_clock_time_millis 178.5256862640381 wall_clock_time_millis 172.49774932861328 wall_clock_time_millis 172.60289192199707 wall_clock_time_millis 173.30694198608398 wall_clock_time_millis 178.9572238922119 wall_clock_time_millis 200.84691047668457 wall_clock_time_millis_testing 4.654645919799805 wall_clock_time_millis_testing 4.44793701171875 wall_clock_time_millis_testing 4.298925399780273 wall_clock_time_millis_testing 4.308938980102539 wall_clock_time_millis_testing 4.275798797607422 wall_clock_time_millis_testing 4.20379638671875 wall_clock_time_millis_testing 4.3468475341796875 wall_clock_time_millis_testing 4.318952560424805 wall_clock_time_millis_testing 4.558086395263672 wall_clock_time_millis_testing 4.728078842163086 wall_clock_time_millis_training 173.64501953125 wall_clock_time_millis_training 180.5269718170166 wall_clock_time_millis_training 177.15001106262207 wall_clock_time_millis_training 190.44923782348633 wall_clock_time_millis_training 174.24988746643066 wall_clock_time_millis_training 168.29395294189453 wall_clock_time_millis_training 168.25604438781738 wall_clock_time_millis_training 168.98798942565918 wall_clock_time_millis_training 174.39913749694824 wall_clock_time_millis_training 196.11883163452148 weighted_recall 0.6351351351351351 [0.888889,0.272727,0.538462,0.857143,0.272727] weighted_recall 0.6621621621621622 [0.833333,0.636364,0.461538,0.857143,0.272727] weighted_recall 0.6621621621621622 [0.888889,0.636364,0.615385,0.727273,0.2] weighted_recall 0.581081081081081 [0.777778,0.272727,0.538462,0.681818,0.4] weighted_recall 0.6081081081081081 [0.888889,0.454545,0.307692,0.681818,0.5] weighted_recall 0.6621621621621622 [0.833333,0.636364,0.461538,0.727273,0.5] weighted_recall 0.5616438356164384 [0.777778,0.454545,0.461538,0.714286,0.1] weighted_recall 0.6164383561643836 [0.888889,0.6,0.384615,0.714286,0.272727] weighted_recall 0.684931506849315 [1,0.5,0.384615,0.857143,0.363636] weighted_recall 0.589041095890411 [0.833333,0.5,0.615385,0.428571,0.545455]