10560713 6691 Sergey Redyuk 14970 Supervised Classification 18968 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,svc=sklearn.svm.classes.SVC)(2) 8277063 Python_3.6.14. Sklearn_0.20.0. NumPy_1.19.5. SciPy_1.5.4. n_jobs null 18952 remainder "passthrough" 18952 sparse_threshold 0.3 18952 transformer_weights null 18952 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": []}}] 18952 memory null 18953 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 18953 axis 0 18954 copy true 18954 missing_values "NaN" 18954 strategy "mean" 18954 verbose 0 18954 copy true 18955 with_mean true 18955 with_std true 18955 memory null 18956 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}] 18956 copy true 18957 fill_value -1 18957 missing_values NaN 18957 strategy "constant" 18957 verbose 0 18957 categorical_features null 18958 categories null 18958 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 18958 handle_unknown "ignore" 18958 n_values null 18958 sparse true 18958 threshold 0.0 18959 memory null 18968 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variancethreshold", "step_name": "variancethreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}] 18968 C 143.11841724167172 18969 cache_size 200 18969 class_weight null 18969 coef0 0.22921525238301776 18969 decision_function_shape "ovr" 18969 degree 2 18969 gamma 0.0070192306738709525 18969 kernel "poly" 18969 max_iter -1 18969 probability false 18969 random_state 7774 18969 shrinking false 18969 tol 1.1571247532842242e-05 18969 verbose false 18969 openml-python Sklearn_0.20.0. 1478 har https://www.openml.org/data/download/1589271/php88ZB4Q -1 22047524 description https://api.openml.org/data/download/22047524/description.xml -1 22047525 predictions https://api.openml.org/data/download/22047525/predictions.arff area_under_roc_curve 0.9938553708521116 [0.999883,0.999943,0.999289,0.982658,0.983643,1] average_cost 0 f_measure 0.9899006485473122 [0.99942,0.999676,0.999288,0.9713,0.973498,1] kappa 0.9878523872750974 kb_relative_information_score 0.9891223203090024 mean_absolute_error 0.00336602259119008 mean_prior_absolute_error 0.27709458719152297 weighted_recall 0.9899019322264297 [1,1,0.998578,0.9713,0.973242,1] number_of_instances 10299 [1722,1544,1406,1777,1906,1944] precision 0.9898996718822842 [0.99884,0.999353,1,0.9713,0.973753,1] predictive_accuracy 0.9899019322264297 prior_entropy 2.575922879508845 relative_absolute_error 0.012147558078655444 root_mean_prior_squared_error 0.3722191487615371 root_mean_squared_error 0.05801743351088602 root_relative_squared_error 0.1558690188399066 total_cost 0 unweighted_recall 0.9905199768439342 [1,1,0.998578,0.9713,0.973242,1] area_under_roc_curve 0.9964515939498734 [1,1,1,0.989812,0.990359,1] area_under_roc_curve 0.9934941462371838 [0.999417,1,0.996429,0.980799,0.985953,1] area_under_roc_curve 0.9911153452299015 [1,1,1,0.971198,0.97893,1] area_under_roc_curve 0.995271629778672 [1,1,1,0.986417,0.987093,1] area_under_roc_curve 0.9941139990628705 [1,0.999429,1,0.983021,0.984461,1] area_under_roc_curve 0.9958752515090544 [1,1,1,0.991448,0.985652,1] area_under_roc_curve 0.995271629778672 [1,1,1,0.986417,0.987093,1] area_under_roc_curve 0.9905528688621943 [1,1,1,0.97495,0.972268,1] area_under_roc_curve 0.9935032633892579 [1,1,1,0.982359,0.981313,1] area_under_roc_curve 0.9929023448604655 [0.999417,1,0.996429,0.980117,0.983331,1] 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 0.9941747572815534 [1,1,1,0.983146,0.984293,1] f_measure 0.9893179128541388 [0.997101,1,0.996416,0.971751,0.973958,1] f_measure 0.9854317496909428 [1,1,1,0.957507,0.961039,1] f_measure 0.9922330097087378 [1,1,1,0.977528,0.978947,1] f_measure 0.9902813056039358 [1,0.996764,1,0.97191,0.976253,1] f_measure 0.9932052392737646 [1,1,1,0.980501,0.981432,1] f_measure 0.9922330097087378 [1,1,1,0.977528,0.978947,1] f_measure 0.984468775298123 [1,1,1,0.955056,0.957895,1] f_measure 0.9893214148176781 [1,1,1,0.969014,0.971129,1] f_measure 0.9883366732142264 [0.997101,1,0.996416,0.968839,0.971279,1] kappa 0.9929923233056276 kappa 0.9871517477251902 kappa 0.9824800334750429 kappa 0.9906574904477374 kappa 0.9883218630596718 kappa 0.9918253041417704 kappa 0.9906566429681033 kappa 0.981313328313936 kappa 0.987152709270233 kappa 0.9859691384678319 kb_relative_information_score 0.993738559768109 kb_relative_information_score 0.9883718959985324 kb_relative_information_score 0.9843017027330903 kb_relative_information_score 0.9916527932017111 kb_relative_information_score 0.9895653728861863 kb_relative_information_score 0.9927404529678726 kb_relative_information_score 0.9916517481954997 kb_relative_information_score 0.983332658201206 kb_relative_information_score 0.9885356154389495 kb_relative_information_score 0.9873295287532646 mean_absolute_error 0.0019417475728155337 mean_absolute_error 0.0035598705501618125 mean_absolute_error 0.004854368932038834 mean_absolute_error 0.0025889967637540453 mean_absolute_error 0.003236245954692557 mean_absolute_error 0.002265372168284789 mean_absolute_error 0.0025889967637540453 mean_absolute_error 0.00517799352750809 mean_absolute_error 0.0035598705501618125 mean_absolute_error 0.003887269193391642 mean_prior_absolute_error 0.27709199511972005 mean_prior_absolute_error 0.27709199511972005 mean_prior_absolute_error 0.27709199511972005 mean_prior_absolute_error 0.2771076974290587 mean_prior_absolute_error 0.27710210740693414 mean_prior_absolute_error 0.27710210740693414 mean_prior_absolute_error 0.27709513558158777 mean_prior_absolute_error 0.2770910843857784 mean_prior_absolute_error 0.2770910843857784 mean_prior_absolute_error 0.27708065643484137 number_of_instances 1030 [172,155,140,178,191,194] number_of_instances 1030 [172,155,140,178,191,194] number_of_instances 1030 [172,155,140,178,191,194] number_of_instances 1030 [172,155,141,178,190,194] number_of_instances 1030 [173,154,141,178,190,194] number_of_instances 1030 [173,154,141,178,190,194] number_of_instances 1030 [172,154,141,178,190,195] number_of_instances 1030 [172,154,141,177,191,195] number_of_instances 1030 [172,154,141,177,191,195] number_of_instances 1029 [172,154,140,177,191,195] precision 0.9941747572815534 [1,1,1,0.983146,0.984293,1] precision 0.9893422349195818 [0.99422,1,1,0.977273,0.968912,1] precision 0.9854721535095872 [1,1,1,0.965714,0.953608,1] precision 0.9922330097087378 [1,1,1,0.977528,0.978947,1] precision 0.990276978244407 [1,0.993548,1,0.97191,0.978836,1] precision 0.9932531916181354 [1,1,1,0.972376,0.989305,1] precision 0.9922330097087378 [1,1,1,0.977528,0.978947,1] precision 0.9844917326069358 [1,1,1,0.949721,0.962963,1] precision 0.9893275651220338 [1,1,1,0.966292,0.973684,1] precision 0.9883465707054536 [0.99422,1,1,0.971591,0.96875,1] predictive_accuracy 0.9941747572815534 predictive_accuracy 0.9893203883495145 predictive_accuracy 0.9854368932038835 predictive_accuracy 0.9922330097087378 predictive_accuracy 0.9902912621359223 predictive_accuracy 0.9932038834951455 predictive_accuracy 0.9922330097087378 predictive_accuracy 0.9844660194174757 predictive_accuracy 0.9893203883495145 predictive_accuracy 0.9883381924198251 prior_entropy 2.5758425283766972 prior_entropy 2.5758425283766972 prior_entropy 2.5758425283766972 prior_entropy 2.57626843373114 prior_entropy 2.5761156998831467 prior_entropy 2.5761156998831467 prior_entropy 2.575945945073779 prior_entropy 2.575847838744184 prior_entropy 2.575847838744184 prior_entropy 2.5755594010061413 relative_absolute_error 0.007007591727709725 relative_absolute_error 0.012847251500801167 relative_absolute_error 0.01751897931927431 relative_absolute_error 0.00934292618997653 relative_absolute_error 0.011678893332774321 relative_absolute_error 0.008175225332942022 relative_absolute_error 0.009343349742751951 relative_absolute_error 0.01868697269342329 relative_absolute_error 0.012847293726728517 relative_absolute_error 0.014029377739350696 root_mean_prior_squared_error 0.37221566682901186 root_mean_prior_squared_error 0.37221566682901186 root_mean_prior_squared_error 0.37221566682901186 root_mean_prior_squared_error 0.3722367592572026 root_mean_prior_squared_error 0.3722292504897755 root_mean_prior_squared_error 0.3722292504897755 root_mean_prior_squared_error 0.3722198854102689 root_mean_prior_squared_error 0.37221444343150406 root_mean_prior_squared_error 0.37221444343150406 root_mean_prior_squared_error 0.3722004351798735 root_mean_squared_error 0.04406526492392317 root_mean_squared_error 0.05966465075873496 root_mean_squared_error 0.06967330142916175 root_mean_squared_error 0.050882185131478436 root_mean_squared_error 0.05688801239885743 root_mean_squared_error 0.04759592596309887 root_mean_squared_error 0.050882185131478436 root_mean_squared_error 0.07195827629611544 root_mean_squared_error 0.05966465075873496 root_mean_squared_error 0.062347968638854966 root_relative_squared_error 0.11838637878766622 root_relative_squared_error 0.16029591464279677 root_relative_squared_error 0.1871853004542343 root_relative_squared_error 0.1366930693062493 root_relative_squared_error 0.1528305804124871 root_relative_squared_error 0.1278672374631296 root_relative_squared_error 0.13669926601421356 root_relative_squared_error 0.19332478243649187 root_relative_squared_error 0.16029644150473335 root_relative_squared_error 0.16751181015874964 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 0.9945732101888347 [1,1,1,0.983146,0.984293,1] unweighted_recall 0.9897011448852734 [1,1,0.992857,0.966292,0.979058,1] unweighted_recall 0.9863374316136243 [1,1,1,0.949438,0.968586,1] unweighted_recall 0.9927459097181156 [1,1,1,0.977528,0.978947,1] unweighted_recall 0.9909323871476444 [1,1,1,0.97191,0.973684,1] unweighted_recall 0.9937413759116893 [1,1,1,0.988764,0.973684,1] unweighted_recall 0.9927459097181156 [1,1,1,0.977528,0.978947,1] unweighted_recall 0.9855552597588271 [1,1,1,0.960452,0.95288,1] unweighted_recall 0.9900562999773223 [1,1,1,0.971751,0.968586,1] unweighted_recall 0.9887968045501988 [1,1,0.992857,0.966102,0.973822,1] usercpu_time_millis 6437.5 usercpu_time_millis 6375 usercpu_time_millis 5468.75 usercpu_time_millis 6015.625 usercpu_time_millis 6203.125 usercpu_time_millis 7015.625 usercpu_time_millis 5562.5 usercpu_time_millis 5328.125 usercpu_time_millis 5656.25 usercpu_time_millis 6250 usercpu_time_millis_testing 843.75 usercpu_time_millis_testing 781.25 usercpu_time_millis_testing 609.375 usercpu_time_millis_testing 781.25 usercpu_time_millis_testing 718.75 usercpu_time_millis_testing 906.25 usercpu_time_millis_testing 593.75 usercpu_time_millis_testing 640.625 usercpu_time_millis_testing 671.875 usercpu_time_millis_testing 734.375 usercpu_time_millis_training 5593.75 usercpu_time_millis_training 5593.75 usercpu_time_millis_training 4859.375 usercpu_time_millis_training 5234.375 usercpu_time_millis_training 5484.375 usercpu_time_millis_training 6109.375 usercpu_time_millis_training 4968.75 usercpu_time_millis_training 4687.5 usercpu_time_millis_training 4984.375 usercpu_time_millis_training 5515.625 wall_clock_time_millis 6581.904888153076 wall_clock_time_millis 6396.24285697937 wall_clock_time_millis 5496.058464050293 wall_clock_time_millis 6026.663303375244 wall_clock_time_millis 6295.251369476318 wall_clock_time_millis 7180.100202560425 wall_clock_time_millis 5568.552732467651 wall_clock_time_millis 5317.663192749023 wall_clock_time_millis 5678.145170211792 wall_clock_time_millis 6280.928134918213 wall_clock_time_millis_testing 879.8716068267822 wall_clock_time_millis_testing 788.4914875030518 wall_clock_time_millis_testing 607.414722442627 wall_clock_time_millis_testing 792.0751571655273 wall_clock_time_millis_testing 716.4614200592041 wall_clock_time_millis_testing 1013.031005859375 wall_clock_time_millis_testing 608.0517768859863 wall_clock_time_millis_testing 640.0790214538574 wall_clock_time_millis_testing 671.4239120483398 wall_clock_time_millis_testing 734.6484661102295 wall_clock_time_millis_training 5702.033281326294 wall_clock_time_millis_training 5607.751369476318 wall_clock_time_millis_training 4888.643741607666 wall_clock_time_millis_training 5234.588146209717 wall_clock_time_millis_training 5578.789949417114 wall_clock_time_millis_training 6167.06919670105 wall_clock_time_millis_training 4960.500955581665 wall_clock_time_millis_training 4677.584171295166 wall_clock_time_millis_training 5006.721258163452 wall_clock_time_millis_training 5546.279668807983 weighted_recall 0.9941747572815534 [1,1,1,0.983146,0.984293,1] weighted_recall 0.9893203883495145 [1,1,0.992857,0.966292,0.979058,1] weighted_recall 0.9854368932038835 [1,1,1,0.949438,0.968586,1] weighted_recall 0.9922330097087378 [1,1,1,0.977528,0.978947,1] weighted_recall 0.9902912621359223 [1,1,1,0.97191,0.973684,1] weighted_recall 0.9932038834951457 [1,1,1,0.988764,0.973684,1] weighted_recall 0.9922330097087378 [1,1,1,0.977528,0.978947,1] weighted_recall 0.9844660194174757 [1,1,1,0.960452,0.95288,1] weighted_recall 0.9893203883495145 [1,1,1,0.971751,0.968586,1] weighted_recall 0.9883381924198251 [1,1,0.992857,0.966102,0.973822,1]