10397102 8323 Heinrich Peters 9977 Supervised Classification 16374 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)(2) 8235634 add_indicator false 12737 copy true 12737 fill_value null 12737 missing_values NaN 12737 strategy "most_frequent" 12737 verbose 0 12737 copy true 13294 with_mean true 13294 with_std true 13294 C 7.65379401334981 13389 cache_size 200 13389 class_weight null 13389 coef0 -0.6640332784499212 13389 decision_function_shape "ovr" 13389 degree 1 13389 gamma 0.03151623852349776 13389 kernel "rbf" 13389 max_iter -1 13389 probability false 13389 random_state 1 13389 shrinking true 13389 tol 0.001 13389 verbose false 13389 categorical_features null 16348 categories null 16348 drop null 16348 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 16348 handle_unknown "ignore" 16348 n_values null 16348 sparse true 16348 memory null 16374 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"}}] 16374 verbose false 16374 n_jobs null 16375 remainder "drop" 16375 sparse_threshold 0.3 16375 transformer_weights null 16375 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "num", "step_name": "num", "argument_1": [true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false]}}] 16375 verbose false 16375 memory null 16376 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 16376 verbose false 16376 memory null 16377 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}] 16377 verbose false 16377 openml-python Sklearn_0.21.2. 1486 nomao https://www.openml.org/data/download/1592278/phpDYCOet -1 21715947 description https://api.openml.org/data/download/21715947/description.xml -1 21715948 predictions https://api.openml.org/data/download/21715948/predictions.arff area_under_roc_curve 0.9536014455372626 [0.953601,0.953601] average_cost 0 f_measure 0.9631877605798451 [0.935354,0.974316] kappa 0.9096709374218043 kb_relative_information_score 0.9023222925236999 mean_absolute_error 0.03676193239518352 mean_prior_absolute_error 0.4080904194746198 number_of_instances 34465 [9844,24621] precision 0.9631530030534408 [0.939621,0.972562] predictive_accuracy 0.9632380676048165 prior_entropy 0.8629999933345911 recall 0.9632380676048165 [0.931126,0.976077] relative_absolute_error 0.09008281165363119 root_mean_prior_squared_error 0.4517106852187937 root_mean_squared_error 0.19173401470574677 root_relative_squared_error 0.4244619863549988 total_cost 0 area_under_roc_curve 0.9536741332699563 [0.953674,0.953674] area_under_roc_curve 0.9523832301747992 [0.952383,0.952383] area_under_roc_curve 0.9543118342975668 [0.954312,0.954312] area_under_roc_curve 0.9569519642731964 [0.956952,0.956952] area_under_roc_curve 0.9509622402652295 [0.950962,0.950962] area_under_roc_curve 0.9522440279236261 [0.952244,0.952244] area_under_roc_curve 0.9535686334726873 [0.953569,0.953569] area_under_roc_curve 0.9573261542932245 [0.957326,0.957326] area_under_roc_curve 0.955700633367016 [0.955701,0.955701] area_under_roc_curve 0.9488902042757227 [0.94889,0.94889] 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 0.9625589742307603 [0.934351,0.973828] f_measure 0.9619551529164542 [0.933265,0.973433] f_measure 0.9617521125342257 [0.933266,0.973149] f_measure 0.9654508144993634 [0.93944,0.975857] f_measure 0.962454000946643 [0.933812,0.973913] f_measure 0.9638813974079885 [0.936214,0.974939] f_measure 0.9611614112964632 [0.932186,0.972742] f_measure 0.9660110922825623 [0.940337,0.976273] f_measure 0.9645640438213596 [0.937819,0.975254] f_measure 0.9620851169865816 [0.932851,0.973769] kappa 0.9081795931110999 kappa 0.906699263048212 kappa 0.9064154426736893 kappa 0.9152975940348004 kappa 0.9077294769193481 kappa 0.911158681210476 kappa 0.9049289279067086 kappa 0.91660954689578 kappa 0.91307242572288 kappa 0.9066303731617034 kb_relative_information_score 0.9005395618426729 kb_relative_information_score 0.8990424329271517 kb_relative_information_score 0.8982717644762122 kb_relative_information_score 0.9082904543384049 kb_relative_information_score 0.900583769829027 kb_relative_information_score 0.9043790153289624 kb_relative_information_score 0.8966676455974277 kb_relative_information_score 0.9097769741410382 kb_relative_information_score 0.9059212892752697 kb_relative_information_score 0.8997521934900415 mean_absolute_error 0.03742384682332463 mean_absolute_error 0.03800406150275602 mean_absolute_error 0.038294168842471714 mean_absolute_error 0.034522773426167684 mean_absolute_error 0.03742384682332463 mean_absolute_error 0.035983749274521186 mean_absolute_error 0.038885664538595474 mean_absolute_error 0.033952408589669185 mean_absolute_error 0.035403366221706326 mean_absolute_error 0.03772489843296576 mean_prior_absolute_error 0.4080229059806574 mean_prior_absolute_error 0.4081472833897437 mean_prior_absolute_error 0.4081472833897437 mean_prior_absolute_error 0.4081472833897437 mean_prior_absolute_error 0.4081472833897437 mean_prior_absolute_error 0.40805842175852763 mean_prior_absolute_error 0.40805842175852763 mean_prior_absolute_error 0.40805842175852763 mean_prior_absolute_error 0.40805842175852763 mean_prior_absolute_error 0.40805842175852763 number_of_instances 3447 [984,2463] number_of_instances 3447 [985,2462] number_of_instances 3447 [985,2462] number_of_instances 3447 [985,2462] number_of_instances 3447 [985,2462] number_of_instances 3446 [984,2462] number_of_instances 3446 [984,2462] number_of_instances 3446 [984,2462] number_of_instances 3446 [984,2462] number_of_instances 3446 [984,2462] precision 0.9625435542269638 [0.93578,0.973236] precision 0.9619239521259734 [0.936605,0.972053] precision 0.9618108003028806 [0.929507,0.974735] precision 0.9654293131326488 [0.941837,0.974868] precision 0.9624189047818191 [0.943983,0.969795] precision 0.9638608243307035 [0.947917,0.970233] precision 0.9612208942751178 [0.928427,0.974328] precision 0.9659842473036307 [0.943705,0.974889] precision 0.9645385267995543 [0.940695,0.974068] precision 0.9620987334540932 [0.948529,0.967522] predictive_accuracy 0.9625761531766754 predictive_accuracy 0.961995938497244 predictive_accuracy 0.9617058311575284 predictive_accuracy 0.9654772265738323 predictive_accuracy 0.9625761531766754 predictive_accuracy 0.9640162507254789 predictive_accuracy 0.9611143354614045 predictive_accuracy 0.9660475914103308 predictive_accuracy 0.9645966337782937 predictive_accuracy 0.9622751015670343 prior_entropy 0.862791736866817 prior_entropy 0.863175399426382 prior_entropy 0.863175399426382 prior_entropy 0.863175399426382 prior_entropy 0.863175399426382 prior_entropy 0.862901291120622 prior_entropy 0.862901291120622 prior_entropy 0.862901291120622 prior_entropy 0.862901291120622 prior_entropy 0.862901291120622 recall 0.9625761531766753 [0.932927,0.974421] recall 0.961995938497244 [0.929949,0.974817] recall 0.9617058311575283 [0.937056,0.971568] recall 0.9654772265738323 [0.937056,0.976848] recall 0.9625761531766753 [0.923858,0.978067] recall 0.9640162507254788 [0.924797,0.979691] recall 0.9611143354614046 [0.935976,0.971162] recall 0.9660475914103308 [0.936992,0.97766] recall 0.9645966337782936 [0.934959,0.976442] recall 0.9622751015670342 [0.917683,0.980097] relative_absolute_error 0.09171996541071331 relative_absolute_error 0.09311359660935337 relative_absolute_error 0.09382438742316519 relative_absolute_error 0.08458410684361105 relative_absolute_error 0.09169201498172963 relative_absolute_error 0.08818283695616237 relative_absolute_error 0.09529435606553031 relative_absolute_error 0.08320477357960483 relative_absolute_error 0.08676053313428879 relative_absolute_error 0.09244974842178313 root_mean_prior_squared_error 0.4516359481339797 root_mean_prior_squared_error 0.45177362368332785 root_mean_prior_squared_error 0.45177362368332785 root_mean_prior_squared_error 0.45177362368332785 root_mean_prior_squared_error 0.45177362368332785 root_mean_prior_squared_error 0.4516752654560011 root_mean_prior_squared_error 0.4516752654560011 root_mean_prior_squared_error 0.4516752654560011 root_mean_prior_squared_error 0.4516752654560011 root_mean_prior_squared_error 0.4516752654560011 root_mean_squared_error 0.19345244072723566 root_mean_squared_error 0.19494630415259487 root_mean_squared_error 0.19568895942917094 root_mean_squared_error 0.185803050099205 root_mean_squared_error 0.19345244072723566 root_mean_squared_error 0.18969383035439288 root_mean_squared_error 0.1971944840470835 root_mean_squared_error 0.184261793624368 root_mean_squared_error 0.1881578226428716 root_mean_squared_error 0.19422898453363174 root_relative_squared_error 0.4283371187048361 root_relative_squared_error 0.43151324896568793 root_relative_squared_error 0.43315711491457004 root_relative_squared_error 0.41127467465750994 root_relative_squared_error 0.4282065853026355 root_relative_squared_error 0.4199783447581135 root_relative_squared_error 0.43658464195067315 root_relative_squared_error 0.40795192412925574 root_relative_squared_error 0.416577654419291 root_relative_squared_error 0.43001908536555034 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 215820.38454599387 usercpu_time_millis 216448.2546250074 usercpu_time_millis 215662.6558509961 usercpu_time_millis 184008.1079599986 usercpu_time_millis 192113.14031499933 usercpu_time_millis 216464.5646729914 usercpu_time_millis 211010.20034999965 usercpu_time_millis 216703.7380729962 usercpu_time_millis 210311.03169699782 usercpu_time_millis 216757.30724399182 usercpu_time_millis_testing 7288.933808995353 usercpu_time_millis_testing 7374.557441005891 usercpu_time_millis_testing 7514.2113429974415 usercpu_time_millis_testing 5248.759643000085 usercpu_time_millis_testing 7392.890998999064 usercpu_time_millis_testing 7351.802039993345 usercpu_time_millis_testing 7204.128197998216 usercpu_time_millis_testing 7206.348223997338 usercpu_time_millis_testing 5241.5037499959 usercpu_time_millis_testing 7269.71214099467 usercpu_time_millis_training 208531.45073699852 usercpu_time_millis_training 209073.6971840015 usercpu_time_millis_training 208148.44450799865 usercpu_time_millis_training 178759.3483169985 usercpu_time_millis_training 184720.24931600026 usercpu_time_millis_training 209112.76263299806 usercpu_time_millis_training 203806.07215200143 usercpu_time_millis_training 209497.38984899886 usercpu_time_millis_training 205069.52794700192 usercpu_time_millis_training 209487.59510299715 wall_clock_time_millis 215821.14148139954 wall_clock_time_millis 216451.49898529053 wall_clock_time_millis 215671.1905002594 wall_clock_time_millis 184010.4479789734 wall_clock_time_millis 192113.7535572052 wall_clock_time_millis 216469.83885765076 wall_clock_time_millis 211013.2429599762 wall_clock_time_millis 216705.83319664001 wall_clock_time_millis 210325.28352737427 wall_clock_time_millis 216758.69846343994 wall_clock_time_millis_testing 7288.973808288574 wall_clock_time_millis_testing 7374.6020793914795 wall_clock_time_millis_testing 7514.246225357056 wall_clock_time_millis_testing 5248.8038539886475 wall_clock_time_millis_testing 7392.930030822754 wall_clock_time_millis_testing 7351.839303970337 wall_clock_time_millis_testing 7204.304218292236 wall_clock_time_millis_testing 7206.382274627686 wall_clock_time_millis_testing 5241.749048233032 wall_clock_time_millis_testing 7269.741535186768 wall_clock_time_millis_training 208532.16767311096 wall_clock_time_millis_training 209076.89690589905 wall_clock_time_millis_training 208156.94427490234 wall_clock_time_millis_training 178761.64412498474 wall_clock_time_millis_training 184720.82352638245 wall_clock_time_millis_training 209117.99955368042 wall_clock_time_millis_training 203808.93874168396 wall_clock_time_millis_training 209499.45092201233 wall_clock_time_millis_training 205083.53447914124 wall_clock_time_millis_training 209488.95692825317