10560712 6691 Sergey Redyuk 9985 Supervised Classification 18978 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(missingindicator=sklearn.impute.MissingIndicator,imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),sgdclassifier=sklearn.linear_model.stochastic_gradient.SGDClassifier)(2) 8277062 Python_3.6.14. Sklearn_0.20.0. NumPy_1.19.5. SciPy_1.5.4. 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 n_jobs null 18962 remainder "passthrough" 18962 sparse_threshold 0.3 18962 transformer_weights null 18962 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]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": []}}] 18962 memory null 18963 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "missingindicator", "step_name": "missingindicator"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 18963 error_on_new false 18964 features "missing-only" 18964 missing_values NaN 18964 sparse "auto" 18964 memory null 18978 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "sgdclassifier", "step_name": "sgdclassifier"}}] 18978 alpha 3.8875083608209314e-05 18979 average true 18979 class_weight null 18979 early_stopping false 18979 epsilon 0.1 18979 eta0 0.0 18979 fit_intercept true 18979 l1_ratio 0.15 18979 learning_rate "optimal" 18979 loss "hinge" 18979 max_iter null 18979 n_iter null 18979 n_iter_no_change 5 18979 n_jobs null 18979 penalty "l2" 18979 power_t 0.5 18979 random_state 36822 18979 shuffle true 18979 tol 4.896672457206874e-05 18979 validation_fraction 0.1 18979 verbose 0 18979 warm_start false 18979 openml-python Sklearn_0.20.0. 1475 first-order-theorem-proving https://www.openml.org/data/download/1587932/phpPbCMyg -1 22047522 description https://api.openml.org/data/download/22047522/description.xml -1 22047523 predictions https://api.openml.org/data/download/22047523/predictions.arff area_under_roc_curve 0.6091335514437342 [0.581043,0.527679,0.563471,0.593554,0.581152,0.660585] average_cost 0 f_measure 0.41793967370100915 [0.304,0.115625,0.229167,0.287785,0.247604,0.652396] kappa 0.2202283036757331 kb_relative_information_score 0.27982698227901054 mean_absolute_error 0.1785986705895223 mean_prior_absolute_error 0.2507645736611627 weighted_recall 0.4642039882314482 [0.261708,0.076132,0.161765,0.225284,0.248397,0.823414] number_of_instances 6118 [1089,486,748,617,624,2554] precision 0.4225095621402409 [0.362595,0.24026,0.392857,0.398281,0.246815,0.5402] predictive_accuracy 0.46420398823144815 prior_entropy 2.3000072984859514 relative_absolute_error 0.7122165144062486 root_mean_prior_squared_error 0.35407492669342416 root_mean_squared_error 0.4226093593255151 root_relative_squared_error 1.1935591239744334 total_cost 0 unweighted_recall 0.2994499501044674 [0.261708,0.076132,0.161765,0.225284,0.248397,0.823414] area_under_roc_curve 0.6156906005859057 [0.558785,0.533466,0.540365,0.607214,0.625423,0.676769] area_under_roc_curve 0.5904631939924784 [0.577206,0.51906,0.549758,0.601085,0.552693,0.628291] area_under_roc_curve 0.6091112461486498 [0.571429,0.543463,0.538436,0.603578,0.567786,0.670028] area_under_roc_curve 0.585593058473008 [0.550377,0.564759,0.553929,0.548152,0.560645,0.629132] area_under_roc_curve 0.6175779745788997 [0.587986,0.514191,0.595493,0.601994,0.63434,0.656303] area_under_roc_curve 0.6132226576844935 [0.598464,0.499547,0.586034,0.595513,0.555191,0.667787] area_under_roc_curve 0.6087126925525684 [0.564521,0.540363,0.533631,0.612551,0.562551,0.673109] area_under_roc_curve 0.6113491696701677 [0.575684,0.519067,0.590056,0.593883,0.565748,0.665643] area_under_roc_curve 0.6426637748762304 [0.64847,0.505976,0.579478,0.581088,0.573741,0.715697] area_under_roc_curve 0.5970503013128088 [0.577251,0.536338,0.567354,0.590194,0.613023,0.623151] 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 0.41854771305862853 [0.256983,0.135135,0.171429,0.313725,0.316547,0.6624] f_measure 0.39727251249305084 [0.303318,0.076923,0.189474,0.314607,0.196429,0.628571] f_measure 0.40867764994702904 [0.27907,0.16,0.161616,0.301887,0.222222,0.656051] f_measure 0.38824376008115763 [0.230303,0.210526,0.208696,0.181818,0.212766,0.635569] f_measure 0.4285633808590218 [0.322581,0.068966,0.31068,0.318182,0.310559,0.633166] f_measure 0.4237627142774257 [0.336957,0.032258,0.285714,0.285714,0.2,0.664671] f_measure 0.40521174416766714 [0.259259,0.151515,0.145833,0.320755,0.21118,0.660348] f_measure 0.42156324934067113 [0.283951,0.092308,0.290598,0.285714,0.220339,0.662651] f_measure 0.45296884469696475 [0.419214,0.037037,0.267857,0.26087,0.235294,0.698052] f_measure 0.4170856626041455 [0.298969,0.137931,0.238532,0.282609,0.326923,0.625564] kappa 0.22809967894817307 kappa 0.18779192070453168 kappa 0.21398101004541079 kappa 0.1770517445015482 kappa 0.23635829020134125 kappa 0.23120741077248222 kappa 0.21244872713067256 kappa 0.22615606936416185 kappa 0.2797725670568929 kappa 0.20655022874571102 kb_relative_information_score 0.28152511466581565 kb_relative_information_score 0.262325582860823 kb_relative_information_score 0.2677085395495373 kb_relative_information_score 0.25545654135162815 kb_relative_information_score 0.2894905333511224 kb_relative_information_score 0.2901895380980285 kb_relative_information_score 0.2661519644558155 kb_relative_information_score 0.28632899672517587 kb_relative_information_score 0.31685627199019434 kb_relative_information_score 0.282411009428461 mean_absolute_error 0.1797385620915025 mean_absolute_error 0.1824618736383434 mean_absolute_error 0.18300653594771157 mean_absolute_error 0.18355119825707977 mean_absolute_error 0.18028322440087066 mean_absolute_error 0.17320261437908427 mean_absolute_error 0.18300653594771157 mean_absolute_error 0.175381263616557 mean_absolute_error 0.1669394435351876 mean_absolute_error 0.17839607201309252 mean_prior_absolute_error 0.25067495791407446 mean_prior_absolute_error 0.25083558171073006 mean_prior_absolute_error 0.25088921191526126 mean_prior_absolute_error 0.25084785528987646 mean_prior_absolute_error 0.25084785528987646 mean_prior_absolute_error 0.25084785528987646 mean_prior_absolute_error 0.25084785528987646 mean_prior_absolute_error 0.25067558048692967 mean_prior_absolute_error 0.25058368192114683 mean_prior_absolute_error 0.25059472840439195 number_of_instances 612 [109,48,74,62,63,256] number_of_instances 612 [109,48,75,62,63,255] number_of_instances 612 [108,49,75,62,63,255] number_of_instances 612 [109,49,75,62,62,255] number_of_instances 612 [109,49,75,62,62,255] number_of_instances 612 [109,49,75,62,62,255] number_of_instances 612 [109,49,75,62,62,255] number_of_instances 612 [109,49,75,61,62,256] number_of_instances 611 [109,48,75,61,62,256] number_of_instances 611 [109,48,74,61,63,256] precision 0.4136854969209494 [0.328571,0.192308,0.290323,0.4,0.289474,0.560976] precision 0.438275961765403 [0.313725,0.5,0.45,0.518519,0.22449,0.509756] precision 0.4127919779302316 [0.375,0.230769,0.333333,0.363636,0.197531,0.552279] precision 0.39449624637590003 [0.339286,0.296296,0.3,0.307692,0.3125,0.5058] precision 0.45593519524978077 [0.324074,0.222222,0.571429,0.538462,0.252525,0.552632] precision 0.42702038965795425 [0.413333,0.076923,0.5,0.348837,0.263158,0.53753] precision 0.42188483258862575 [0.396226,0.294118,0.333333,0.386364,0.171717,0.55291] precision 0.42869229339837983 [0.433962,0.1875,0.404762,0.378378,0.232143,0.539216] precision 0.4480118947553835 [0.4,0.166667,0.405405,0.387097,0.245614,0.597222] precision 0.43497095745841113 [0.341176,0.4,0.371429,0.419355,0.414634,0.508557] predictive_accuracy 0.46078431372549017 predictive_accuracy 0.4526143790849673 predictive_accuracy 0.45098039215686275 predictive_accuracy 0.4493464052287582 predictive_accuracy 0.4591503267973856 predictive_accuracy 0.4803921568627451 predictive_accuracy 0.45098039215686275 predictive_accuracy 0.47385620915032683 predictive_accuracy 0.49918166939443537 predictive_accuracy 0.4648117839607201 prior_entropy 2.2982053906988225 prior_entropy 2.3010980143383097 prior_entropy 2.3029972536480843 prior_entropy 2.301686142471426 prior_entropy 2.301686142471426 prior_entropy 2.301686142471426 prior_entropy 2.301686142471426 prior_entropy 2.2983403180467192 prior_entropy 2.2961240491639523 prior_entropy 2.2965513970017746 relative_absolute_error 0.717018419339329 relative_absolute_error 0.7274162317559997 relative_absolute_error 0.7294316664740559 relative_absolute_error 0.7317232114461192 relative_absolute_error 0.7186954984826869 relative_absolute_error 0.690468787061917 relative_absolute_error 0.7295519259522137 relative_absolute_error 0.6996344170257199 relative_absolute_error 0.66620237301693 relative_absolute_error 0.7118907614257936 root_mean_prior_squared_error 0.35394835494159665 root_mean_prior_squared_error 0.3541751851309153 root_mean_prior_squared_error 0.3542508884492025 root_mean_prior_squared_error 0.3541925116962025 root_mean_prior_squared_error 0.3541925116962025 root_mean_prior_squared_error 0.3541925116962025 root_mean_prior_squared_error 0.3541925116962025 root_mean_prior_squared_error 0.3539492344090008 root_mean_prior_squared_error 0.3538193917423618 root_mean_prior_squared_error 0.35383500173976573 root_mean_squared_error 0.423955849224306 root_mean_squared_error 0.42715556140397304 root_mean_squared_error 0.42779263194649764 root_mean_squared_error 0.4284287551706582 root_mean_squared_error 0.4245977206731928 root_mean_squared_error 0.4161761818978643 root_mean_squared_error 0.42779263194649764 root_mean_squared_error 0.41878546251816934 root_mean_squared_error 0.4085822359515739 root_mean_squared_error 0.42236959172399297 root_relative_squared_error 1.1977901388869598 root_relative_squared_error 1.2060572827711848 root_relative_squared_error 1.2075979084180635 root_relative_squared_error 1.2095929219930246 root_relative_squared_error 1.198776672719095 root_relative_squared_error 1.174999945382319 root_relative_squared_error 1.2077969404204212 root_relative_squared_error 1.1831794557132678 root_relative_squared_error 1.154776265765242 root_relative_squared_error 1.1936908153440178 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 0.308777012989266 [0.211009,0.104167,0.121622,0.258065,0.349206,0.808594] unweighted_recall 0.2792103529452293 [0.293578,0.041667,0.12,0.225806,0.174603,0.819608] unweighted_recall 0.2952022959721523 [0.222222,0.122449,0.106667,0.258065,0.253968,0.807843] unweighted_recall 0.27380029569290476 [0.174312,0.163265,0.16,0.129032,0.16129,0.854902] unweighted_recall 0.32424321765798164 [0.321101,0.040816,0.213333,0.225806,0.403226,0.741176] unweighted_recall 0.2964376457893012 [0.284404,0.020408,0.2,0.241935,0.16129,0.870588] unweighted_recall 0.2926716066716713 [0.192661,0.102041,0.093333,0.274194,0.274194,0.819608] unweighted_recall 0.2995768244751103 [0.211009,0.061224,0.226667,0.229508,0.209677,0.859375] unweighted_recall 0.32059530314978507 [0.440367,0.020833,0.2,0.196721,0.225806,0.839844] unweighted_recall 0.30342001313669986 [0.266055,0.083333,0.175676,0.213115,0.269841,0.8125] usercpu_time_millis 437.5 usercpu_time_millis 406.25 usercpu_time_millis 359.375 usercpu_time_millis 359.375 usercpu_time_millis 359.375 usercpu_time_millis 359.375 usercpu_time_millis 390.625 usercpu_time_millis 421.875 usercpu_time_millis 375 usercpu_time_millis 375 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_testing 0 usercpu_time_millis_training 437.5 usercpu_time_millis_training 406.25 usercpu_time_millis_training 359.375 usercpu_time_millis_training 359.375 usercpu_time_millis_training 359.375 usercpu_time_millis_training 359.375 usercpu_time_millis_training 390.625 usercpu_time_millis_training 421.875 usercpu_time_millis_training 375 usercpu_time_millis_training 375 wall_clock_time_millis 426.14054679870605 wall_clock_time_millis 408.9550971984863 wall_clock_time_millis 354.5713424682617 wall_clock_time_millis 367.54679679870605 wall_clock_time_millis 364.4289970397949 wall_clock_time_millis 359.5871925354004 wall_clock_time_millis 401.8442630767822 wall_clock_time_millis 429.87966537475586 wall_clock_time_millis 375.69332122802734 wall_clock_time_millis 391.0212516784668 wall_clock_time_millis_testing 2.044200897216797 wall_clock_time_millis_testing 2.1734237670898438 wall_clock_time_millis_testing 2.1491050720214844 wall_clock_time_millis_testing 2.093076705932617 wall_clock_time_millis_testing 2.315521240234375 wall_clock_time_millis_testing 2.284526824951172 wall_clock_time_millis_testing 2.156972885131836 wall_clock_time_millis_testing 2.1774768829345703 wall_clock_time_millis_testing 2.012491226196289 wall_clock_time_millis_testing 2.1033287048339844 wall_clock_time_millis_training 424.09634590148926 wall_clock_time_millis_training 406.7816734313965 wall_clock_time_millis_training 352.42223739624023 wall_clock_time_millis_training 365.45372009277344 wall_clock_time_millis_training 362.11347579956055 wall_clock_time_millis_training 357.3026657104492 wall_clock_time_millis_training 399.6872901916504 wall_clock_time_millis_training 427.7021884918213 wall_clock_time_millis_training 373.68083000183105 wall_clock_time_millis_training 388.9179229736328 weighted_recall 0.46078431372549017 [0.211009,0.104167,0.121622,0.258065,0.349206,0.808594] weighted_recall 0.4526143790849673 [0.293578,0.041667,0.12,0.225806,0.174603,0.819608] weighted_recall 0.45098039215686275 [0.222222,0.122449,0.106667,0.258065,0.253968,0.807843] weighted_recall 0.4493464052287582 [0.174312,0.163265,0.16,0.129032,0.16129,0.854902] weighted_recall 0.4591503267973856 [0.321101,0.040816,0.213333,0.225806,0.403226,0.741176] weighted_recall 0.4803921568627451 [0.284404,0.020408,0.2,0.241935,0.16129,0.870588] weighted_recall 0.45098039215686275 [0.192661,0.102041,0.093333,0.274194,0.274194,0.819608] weighted_recall 0.4738562091503268 [0.211009,0.061224,0.226667,0.229508,0.209677,0.859375] weighted_recall 0.49918166939443537 [0.440367,0.020833,0.2,0.196721,0.225806,0.839844] weighted_recall 0.46481178396072015 [0.266055,0.083333,0.175676,0.213115,0.269841,0.8125]