10571910 28997 Marc Boel 9960 Supervised Classification 19030 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),decisiontreeclassifier=sklearn.tree._classes.DecisionTreeClassifier)(2) 8288192 Python_3.7.12. Sklearn_1.0.1. NumPy_1.19.5. SciPy_1.4.1. memory null 19030 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "decisiontreeclassifier", "step_name": "decisiontreeclassifier"}}] 19030 verbose false 19030 n_jobs null 19031 remainder "drop" 19031 sparse_threshold 0.3 19031 transformer_weights null 19031 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cont"}}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cat"}}}] 19031 verbose false 19031 verbose_feature_names_out true 19031 add_indicator false 19032 copy true 19032 fill_value null 19032 missing_values NaN 19032 strategy "median" 19032 verbose 0 19032 categories "auto" 19033 drop null 19033 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 19033 handle_unknown "ignore" 19033 sparse true 19033 ccp_alpha 0.0 19034 class_weight null 19034 criterion "gini" 19034 max_depth null 19034 max_features 0.791452580298306 19034 max_leaf_nodes null 19034 min_impurity_decrease 0.0 19034 min_samples_leaf 10 19034 min_samples_split 2 19034 min_weight_fraction_leaf 0.0 19034 random_state 19341 19034 splitter "random" 19034 openml-python Sklearn_1.0.1. 1497 wall-robot-navigation https://www.openml.org/data/download/1592289/phpVeNa5j -1 22070087 description https://api.openml.org/data/download/22070087/description.xml -1 22070088 predictions https://api.openml.org/data/download/22070088/predictions.arff area_under_roc_curve 0.9801314000359567 [0.972983,0.987959,0.981921,0.978632] average_cost 0 f_measure 0.9073135313836038 [0.901603,0.939314,0.850467,0.863891] kappa 0.8596419516761964 kb_relative_information_score 0.8459794836553987 mean_absolute_error 0.06131067815551185 mean_prior_absolute_error 0.3312381502905654 weighted_recall 0.9074413489736071 [0.918367,0.933715,0.832317,0.841404] number_of_instances 5456 [2205,2097,328,826] precision 0.907690205833443 [0.885439,0.944981,0.869427,0.887612] predictive_accuracy 0.9074413489736071 prior_entropy 1.7146330399083418 relative_absolute_error 0.18509546108058358 root_mean_prior_squared_error 0.40694354051108633 root_mean_squared_error 0.18467730919936284 root_relative_squared_error 0.4538155562499503 total_cost 0 unweighted_recall 0.8814509022933892 [0.918367,0.933715,0.832317,0.841404] area_under_roc_curve 0.9749103221054735 [0.967289,0.983298,0.960423,0.979802] area_under_roc_curve 0.9838453392781562 [0.973937,0.992963,0.994684,0.982837] area_under_roc_curve 0.9869321596938373 [0.980584,0.995585,0.980359,0.984478] area_under_roc_curve 0.9726944379660776 [0.967073,0.985346,0.966094,0.958209] area_under_roc_curve 0.9786917496437206 [0.970259,0.982426,0.992793,0.985987] area_under_roc_curve 0.9784718282354671 [0.970977,0.985495,0.994654,0.974134] area_under_roc_curve 0.9761235170013681 [0.970231,0.985359,0.980476,0.966698] area_under_roc_curve 0.9771918124706632 [0.967153,0.989249,0.961379,0.979659] area_under_roc_curve 0.9891552867284378 [0.984959,0.993172,0.997041,0.987054] area_under_roc_curve 0.9826799529025336 [0.977285,0.984158,0.997011,0.987686] 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 0.8934961127694192 [0.895323,0.914286,0.78125,0.880503] f_measure 0.9084145953287395 [0.902222,0.947115,0.857143,0.846626] f_measure 0.9192825206346752 [0.910755,0.950355,0.861538,0.886228] f_measure 0.905905985348565 [0.89823,0.947619,0.827586,0.851852] f_measure 0.9066526843142634 [0.900901,0.923445,0.865672,0.895706] f_measure 0.8990731992448034 [0.887892,0.945107,0.861538,0.82716] f_measure 0.9097375830614831 [0.905077,0.939759,0.895522,0.851613] f_measure 0.8995505766520133 [0.896703,0.932692,0.754717,0.879518] f_measure 0.9225467328678705 [0.915033,0.958637,0.925373,0.849673] f_measure 0.9068032545756913 [0.903803,0.934307,0.849315,0.867925] kappa 0.8386680999128845 kappa 0.861149963125906 kappa 0.878432126628141 kappa 0.8576336697444709 kappa 0.8589318824280372 kappa 0.8474806112964912 kappa 0.8634846308385178 kappa 0.8486788320041957 kappa 0.8827746908048038 kappa 0.859071019687974 kb_relative_information_score 0.836387054713155 kb_relative_information_score 0.8481500839300814 kb_relative_information_score 0.8603742136953367 kb_relative_information_score 0.8365601432131059 kb_relative_information_score 0.846011490136959 kb_relative_information_score 0.8334441200800379 kb_relative_information_score 0.8462006590701143 kb_relative_information_score 0.8263097767586065 kb_relative_information_score 0.8816147072002962 kb_relative_information_score 0.8447483734699894 mean_absolute_error 0.06295319465674651 mean_absolute_error 0.060431342075568606 mean_absolute_error 0.05648110057463198 mean_absolute_error 0.06121317594149139 mean_absolute_error 0.062256142129552765 mean_absolute_error 0.06837339563908537 mean_absolute_error 0.062155650773831034 mean_absolute_error 0.06475362206207329 mean_absolute_error 0.04954004364057798 mean_absolute_error 0.06494206033296585 mean_prior_absolute_error 0.3311434139730841 mean_prior_absolute_error 0.3311434139730841 mean_prior_absolute_error 0.33137469978129297 mean_prior_absolute_error 0.33137469978129297 mean_prior_absolute_error 0.33137469978129297 mean_prior_absolute_error 0.33137469978129297 mean_prior_absolute_error 0.3311205766710351 mean_prior_absolute_error 0.3311024296804111 mean_prior_absolute_error 0.3311861074705109 mean_prior_absolute_error 0.3311861074705109 number_of_instances 546 [221,210,33,82] number_of_instances 546 [221,210,33,82] number_of_instances 546 [220,210,33,83] number_of_instances 546 [220,210,33,83] number_of_instances 546 [220,210,33,83] number_of_instances 546 [220,210,33,83] number_of_instances 545 [220,210,32,83] number_of_instances 545 [221,209,32,83] number_of_instances 545 [221,209,33,82] number_of_instances 545 [221,209,33,82] precision 0.8937496431129708 [0.881579,0.914286,0.806452,0.909091] precision 0.9089476035046334 [0.886463,0.956311,0.9,0.851852] precision 0.9192568017899037 [0.917051,0.943662,0.875,0.880952] precision 0.9078272360550842 [0.875,0.947619,0.96,0.873418] precision 0.9069027463056228 [0.892857,0.927885,0.852941,0.9125] precision 0.8991907258538502 [0.876106,0.947368,0.875,0.848101] precision 0.9116151084083249 [0.879828,0.95122,0.857143,0.916667] precision 0.9027839509690327 [0.871795,0.937198,0.952381,0.879518] precision 0.9247438357845802 [0.882353,0.975248,0.911765,0.915493] precision 0.9086971711529936 [0.893805,0.950495,0.775,0.896104] predictive_accuracy 0.8937728937728937 predictive_accuracy 0.9084249084249084 predictive_accuracy 0.9194139194139194 predictive_accuracy 0.9065934065934066 predictive_accuracy 0.9065934065934066 predictive_accuracy 0.8992673992673993 predictive_accuracy 0.910091743119266 predictive_accuracy 0.9009174311926605 predictive_accuracy 0.9229357798165139 predictive_accuracy 0.9064220183486239 prior_entropy 1.7138246699606299 prior_entropy 1.7138246699606299 prior_entropy 1.7164171123716554 prior_entropy 1.7164171123716554 prior_entropy 1.7164171123716554 prior_entropy 1.7164171123716554 prior_entropy 1.7121302787024806 prior_entropy 1.711997401430895 prior_entropy 1.714437400963805 prior_entropy 1.714437400963805 relative_absolute_error 0.19010855116044512 relative_absolute_error 0.18249296083080357 relative_absolute_error 0.17044481854501703 relative_absolute_error 0.18472495329876432 relative_absolute_error 0.18787234562759852 relative_absolute_error 0.20633257663971252 relative_absolute_error 0.18771304217551552 relative_absolute_error 0.19556975804911858 relative_absolute_error 0.14958370089539177 relative_absolute_error 0.1960893252104433 root_mean_prior_squared_error 0.4068271240296317 root_mean_prior_squared_error 0.4068271240296317 root_mean_prior_squared_error 0.40711128043132166 root_mean_prior_squared_error 0.40711128043132166 root_mean_prior_squared_error 0.40711128043132166 root_mean_prior_squared_error 0.40711128043132166 root_mean_prior_squared_error 0.4067990554858411 root_mean_prior_squared_error 0.40677675026179705 root_mean_prior_squared_error 0.4068795919478491 root_mean_prior_squared_error 0.4068795919478491 root_mean_squared_error 0.19434024644000722 root_mean_squared_error 0.18014180750643385 root_mean_squared_error 0.1719394889048534 root_mean_squared_error 0.19331215740170116 root_mean_squared_error 0.18801881550758034 root_mean_squared_error 0.19358966397924895 root_mean_squared_error 0.1861451408875478 root_mean_squared_error 0.19325886279760437 root_mean_squared_error 0.15711934597538155 root_mean_squared_error 0.18542322659587135 root_relative_squared_error 0.4776973681475875 root_relative_squared_error 0.44279694461402985 root_relative_squared_error 0.4223402719833478 root_relative_squared_error 0.47483861708988506 root_relative_squared_error 0.46183641806333703 root_relative_squared_error 0.47552026505909334 root_relative_squared_error 0.4575849879130968 root_relative_squared_error 0.47509810399248503 root_relative_squared_error 0.3861568608619721 root_relative_squared_error 0.45572014489150775 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 0.8587555677225691 [0.909502,0.914286,0.757576,0.853659] unweighted_recall 0.8790731267775744 [0.918552,0.938095,0.818182,0.841463] unweighted_recall 0.9004348563083503 [0.904545,0.957143,0.848485,0.891566] unweighted_recall 0.8572360872059667 [0.922727,0.947619,0.727273,0.831325] unweighted_recall 0.8966111198038909 [0.909091,0.919048,0.878788,0.879518] unweighted_recall 0.8746427267511605 [0.9,0.942857,0.848485,0.807229] unweighted_recall 0.8982675833202942 [0.931818,0.928571,0.9375,0.795181] unweighted_recall 0.8389561651094625 [0.923077,0.92823,0.625,0.879518] unweighted_recall 0.9062217106561288 [0.950226,0.942584,0.939394,0.792683] unweighted_recall 0.903386197607673 [0.914027,0.91866,0.939394,0.841463] usercpu_time_millis 56.158780999965074 usercpu_time_millis 56.804031000012856 usercpu_time_millis 55.57688200002531 usercpu_time_millis 56.090743999959614 usercpu_time_millis 54.76354799998262 usercpu_time_millis 54.29831200001445 usercpu_time_millis 55.465721000018675 usercpu_time_millis 54.234660000020085 usercpu_time_millis 57.631995000008374 usercpu_time_millis 57.88814099997808 usercpu_time_millis_testing 6.408681999971577 usercpu_time_millis_testing 6.913225000005241 usercpu_time_millis_testing 6.599099000027309 usercpu_time_millis_testing 7.723599999962971 usercpu_time_millis_testing 5.732476999980918 usercpu_time_millis_testing 5.711699000016779 usercpu_time_millis_testing 6.412026000020887 usercpu_time_millis_testing 6.335113000034198 usercpu_time_millis_testing 6.5119039999785855 usercpu_time_millis_testing 6.503609999981563 usercpu_time_millis_training 49.7500989999935 usercpu_time_millis_training 49.890806000007615 usercpu_time_millis_training 48.977782999998 usercpu_time_millis_training 48.36714399999664 usercpu_time_millis_training 49.0310710000017 usercpu_time_millis_training 48.58661299999767 usercpu_time_millis_training 49.05369499999779 usercpu_time_millis_training 47.89954699998589 usercpu_time_millis_training 51.12009100002979 usercpu_time_millis_training 51.384530999996514 wall_clock_time_millis 59.984683990478516 wall_clock_time_millis 59.32497978210449 wall_clock_time_millis 55.98640441894531 wall_clock_time_millis 57.00063705444336 wall_clock_time_millis 55.371999740600586 wall_clock_time_millis 54.57115173339844 wall_clock_time_millis 55.58037757873535 wall_clock_time_millis 54.44788932800293 wall_clock_time_millis 57.868242263793945 wall_clock_time_millis 58.02154541015625 wall_clock_time_millis_testing 6.981611251831055 wall_clock_time_millis_testing 8.036375045776367 wall_clock_time_millis_testing 6.66046142578125 wall_clock_time_millis_testing 8.446931838989258 wall_clock_time_millis_testing 5.7506561279296875 wall_clock_time_millis_testing 5.719661712646484 wall_clock_time_millis_testing 6.428718566894531 wall_clock_time_millis_testing 6.384372711181641 wall_clock_time_millis_testing 6.530284881591797 wall_clock_time_millis_testing 6.530523300170898 wall_clock_time_millis_training 53.00307273864746 wall_clock_time_millis_training 51.288604736328125 wall_clock_time_millis_training 49.32594299316406 wall_clock_time_millis_training 48.5537052154541 wall_clock_time_millis_training 49.6213436126709 wall_clock_time_millis_training 48.85149002075195 wall_clock_time_millis_training 49.15165901184082 wall_clock_time_millis_training 48.06351661682129 wall_clock_time_millis_training 51.33795738220215 wall_clock_time_millis_training 51.49102210998535 weighted_recall 0.8937728937728938 [0.909502,0.914286,0.757576,0.853659] weighted_recall 0.9084249084249084 [0.918552,0.938095,0.818182,0.841463] weighted_recall 0.9194139194139194 [0.904545,0.957143,0.848485,0.891566] weighted_recall 0.9065934065934066 [0.922727,0.947619,0.727273,0.831325] weighted_recall 0.9065934065934066 [0.909091,0.919048,0.878788,0.879518] weighted_recall 0.8992673992673993 [0.9,0.942857,0.848485,0.807229] weighted_recall 0.9100917431192661 [0.931818,0.928571,0.9375,0.795181] weighted_recall 0.9009174311926605 [0.923077,0.92823,0.625,0.879518] weighted_recall 0.9229357798165138 [0.950226,0.942584,0.939394,0.792683] weighted_recall 0.9064220183486239 [0.914027,0.91866,0.939394,0.841463]