10584723 28997 Marc Boel 9960 Supervised Classification 19039 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),gradientboostingclassifier=sklearn.ensemble._gb.GradientBoostingClassifier)(2) 8301005 Python_3.7.12. Sklearn_1.0.1. NumPy_1.19.5. SciPy_1.4.1. 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 "most_frequent" 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 memory null 19039 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}] 19039 verbose false 19039 ccp_alpha 0.0 19040 criterion "friedman_mse" 19040 init null 19040 learning_rate 0.014205782498602205 19040 loss "deviance" 19040 max_depth 3 19040 max_features null 19040 max_leaf_nodes 1195 19040 min_impurity_decrease 0.0 19040 min_samples_leaf 18 19040 min_samples_split 2 19040 min_weight_fraction_leaf 0.0 19040 n_estimators 100 19040 n_iter_no_change 6 19040 random_state 51933 19040 subsample 1.0 19040 tol 0.0001 19040 validation_fraction 0.3416974827341247 19040 verbose 0 19040 warm_start false 19040 openml-python Sklearn_1.0.1. 1497 wall-robot-navigation https://www.openml.org/data/download/1592289/phpVeNa5j -1 22095714 description https://api.openml.org/data/download/22095714/description.xml -1 22095715 predictions https://api.openml.org/data/download/22095715/predictions.arff area_under_roc_curve 0.9995096703407448 [0.999473,0.999873,0.998415,0.999121] average_cost 0 f_measure 0.9847857232876658 [0.982793,0.996663,0.933549,0.980296] kappa 0.9771820768690108 kb_relative_information_score 0.8463974707989184 mean_absolute_error 0.0778281989271789 mean_prior_absolute_error 0.3312381502905654 weighted_recall 0.9849706744868035 [0.997279,0.997139,0.878049,0.96368] number_of_instances 5456 [2205,2097,328,826] precision 0.9853071002180278 [0.968722,0.996189,0.99654,0.997494] predictive_accuracy 0.9849706744868035 prior_entropy 1.7146330399083418 relative_absolute_error 0.23496145857265305 root_mean_prior_squared_error 0.40694354051108633 root_mean_squared_error 0.11530337259305859 root_relative_squared_error 0.28333997499566504 total_cost 0 unweighted_recall 0.9590367122831475 [0.997279,0.997139,0.878049,0.96368] area_under_roc_curve 0.9979379416562726 [0.998998,0.998937,0.999409,0.991931] area_under_roc_curve 0.9990752247702315 [0.998531,1,0.994536,1] area_under_roc_curve 0.9994699664839356 [0.998996,0.999915,0.998464,1] area_under_roc_curve 0.9992974340064533 [0.998745,0.999972,0.996987,0.999974] area_under_roc_curve 0.9998432735221024 [0.999735,1,0.999173,1] area_under_roc_curve 0.9998186478778137 [0.999721,1,0.999055,0.999922] area_under_roc_curve 0.9999467342393464 [0.99993,1,0.999574,1] area_under_roc_curve 0.9999654326871452 [0.999944,1,1,0.999922] area_under_roc_curve 0.9998728191385361 [0.999846,1,0.998994,0.999974] area_under_roc_curve 0.9999109185370676 [0.999916,1,0.999941,0.999658] 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 0.9832037527940201 [0.982063,0.992908,0.918033,0.987654] f_measure 0.984467741709121 [0.982222,1,0.862069,1] f_measure 0.9850510735401296 [0.982063,0.997625,0.918033,0.987805] f_measure 0.975188016578824 [0.973451,0.995215,0.827586,0.987805] f_measure 0.990731374058223 [0.99095,0.995261,0.952381,0.993939] f_measure 0.9758757515204904 [0.971175,0.997625,0.935484,0.949367] f_measure 0.9944917392388161 [0.993228,0.997613,0.984127,0.993939] f_measure 0.9908096599044303 [0.988764,0.997602,1,0.97561] f_measure 0.9869438336150963 [0.986607,0.997613,0.935484,0.981366] f_measure 0.9796284083052319 [0.977876,0.995192,0.984615,0.942675] kappa 0.9749511920357634 kappa 0.9776981282357627 kappa 0.9777640896156059 kappa 0.9637576079408521 kappa 0.9861393176279448 kappa 0.9637494637494637 kappa 0.991669935855959 kappa 0.9861183278825484 kappa 0.9804892268824187 kappa 0.9693358226132327 kb_relative_information_score 0.843004190516632 kb_relative_information_score 0.8354057937071666 kb_relative_information_score 0.8445068916885152 kb_relative_information_score 0.8339305084130341 kb_relative_information_score 0.8520127443546406 kb_relative_information_score 0.8407033932416066 kb_relative_information_score 0.8543652298223776 kb_relative_information_score 0.8604667097125025 kb_relative_information_score 0.8507793580931705 kb_relative_information_score 0.8488950673552516 mean_absolute_error 0.07927359640206579 mean_absolute_error 0.07898311697525648 mean_absolute_error 0.07786016494650436 mean_absolute_error 0.08043512476107786 mean_absolute_error 0.07688997441757804 mean_absolute_error 0.08029320473162993 mean_absolute_error 0.07640058526198996 mean_absolute_error 0.07365370457710317 mean_absolute_error 0.07694695687127537 mean_absolute_error 0.07753314566918604 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 0.9837892311131748 [0.973333,0.985915,1,1] precision 0.9858598461218548 [0.965066,1,1,1] precision 0.9856970330484568 [0.969027,0.995261,1,1] precision 0.9767411898446381 [0.948276,1,0.96,1] precision 0.9909265475303211 [0.986486,0.990566,1,1] precision 0.9772457287690869 [0.948052,0.995261,1,1] precision 0.9945694655860451 [0.986547,1,1,1] precision 0.9908786790285261 [0.982143,1,1,0.987654] precision 0.987455692134187 [0.973568,0.995238,1,1] precision 0.980439572659756 [0.95671,1,1,0.986667] predictive_accuracy 0.9835164835164835 predictive_accuracy 0.9853479853479854 predictive_accuracy 0.9853479853479854 predictive_accuracy 0.9761904761904762 predictive_accuracy 0.9908424908424908 predictive_accuracy 0.9761904761904762 predictive_accuracy 0.9944954128440366 predictive_accuracy 0.9908256880733946 predictive_accuracy 0.9871559633027523 predictive_accuracy 0.9798165137614678 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 0.23939354689539222 relative_absolute_error 0.23851634561476243 relative_absolute_error 0.23496110293843192 relative_absolute_error 0.24273164129357183 relative_absolute_error 0.23203332803718982 relative_absolute_error 0.24230336469447844 relative_absolute_error 0.23073342656651977 relative_absolute_error 0.2224499066593854 relative_absolute_error 0.23233751397053026 relative_absolute_error 0.23410748192718095 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 0.12074731544307922 root_mean_squared_error 0.1221262987023144 root_mean_squared_error 0.11660414391662247 root_mean_squared_error 0.12486595133758878 root_mean_squared_error 0.10979907359770931 root_mean_squared_error 0.11964611227545927 root_mean_squared_error 0.10714445354537062 root_mean_squared_error 0.10425233727074157 root_mean_squared_error 0.1116455107190489 root_mean_squared_error 0.11433271199482115 root_relative_squared_error 0.2968025195740991 root_relative_squared_error 0.3001921245875906 root_relative_squared_error 0.28641835665443616 root_relative_squared_error 0.30671208914991793 root_relative_squared_error 0.2697028524519896 root_relative_squared_error 0.29389043739760284 root_relative_squared_error 0.2633842239810703 root_relative_squared_error 0.25628882969256706 root_relative_squared_error 0.27439447180078474 root_relative_squared_error 0.28099888580667737 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 0.9537612077066884 [0.99095,1,0.848485,0.97561] unweighted_recall 0.9393939393939394 [1,1,0.757576,1] unweighted_recall 0.9549607520993064 [0.995455,1,0.848485,0.975904] unweighted_recall 0.9234131330516874 [1,0.990476,0.727273,0.975904] unweighted_recall 0.9731243154435926 [0.995455,1,0.909091,0.987952] unweighted_recall 0.9444642205184375 [0.995455,1,0.878788,0.903614] unweighted_recall 0.9879849756167527 [1,0.995238,0.96875,0.987952] unweighted_recall 0.9886364614534259 [0.995475,0.995215,1,0.963855] unweighted_recall 0.9605506282335551 [1,1,0.878788,0.963415] unweighted_recall 0.9656416540241957 [1,0.990431,0.969697,0.902439] usercpu_time_millis 11615.241111000614 usercpu_time_millis 11599.575598999763 usercpu_time_millis 11578.643402001035 usercpu_time_millis 11573.544177999793 usercpu_time_millis 11571.834209000372 usercpu_time_millis 11597.035388999757 usercpu_time_millis 11636.241893999795 usercpu_time_millis 11631.829469999502 usercpu_time_millis 11633.992258000035 usercpu_time_millis 11598.364660000698 usercpu_time_millis_testing 9.68031700085703 usercpu_time_millis_testing 10.681769999791868 usercpu_time_millis_testing 10.323655000320286 usercpu_time_millis_testing 10.253888000079314 usercpu_time_millis_testing 9.982403999856615 usercpu_time_millis_testing 10.552792999988014 usercpu_time_millis_testing 10.549616999924183 usercpu_time_millis_testing 10.357838999880187 usercpu_time_millis_testing 9.792825999284105 usercpu_time_millis_testing 6.403157000022475 usercpu_time_millis_training 11605.560793999757 usercpu_time_millis_training 11588.893828999971 usercpu_time_millis_training 11568.319747000714 usercpu_time_millis_training 11563.290289999713 usercpu_time_millis_training 11561.851805000515 usercpu_time_millis_training 11586.482595999769 usercpu_time_millis_training 11625.692276999871 usercpu_time_millis_training 11621.471630999622 usercpu_time_millis_training 11624.19943200075 usercpu_time_millis_training 11591.961503000675 wall_clock_time_millis 11767.590522766113 wall_clock_time_millis 11863.603591918945 wall_clock_time_millis 11784.138202667236 wall_clock_time_millis 11779.003381729126 wall_clock_time_millis 11767.903566360474 wall_clock_time_millis 11835.21580696106 wall_clock_time_millis 11862.471342086792 wall_clock_time_millis 11885.424137115479 wall_clock_time_millis 11873.384237289429 wall_clock_time_millis 11763.696670532227 wall_clock_time_millis_testing 9.687423706054688 wall_clock_time_millis_testing 10.68878173828125 wall_clock_time_millis_testing 10.391712188720703 wall_clock_time_millis_testing 10.260820388793945 wall_clock_time_millis_testing 9.98997688293457 wall_clock_time_millis_testing 10.559558868408203 wall_clock_time_millis_testing 10.621309280395508 wall_clock_time_millis_testing 10.487556457519531 wall_clock_time_millis_testing 9.79924201965332 wall_clock_time_millis_testing 6.407976150512695 wall_clock_time_millis_training 11757.903099060059 wall_clock_time_millis_training 11852.914810180664 wall_clock_time_millis_training 11773.746490478516 wall_clock_time_millis_training 11768.742561340332 wall_clock_time_millis_training 11757.913589477539 wall_clock_time_millis_training 11824.656248092651 wall_clock_time_millis_training 11851.850032806396 wall_clock_time_millis_training 11874.936580657959 wall_clock_time_millis_training 11863.584995269775 wall_clock_time_millis_training 11757.288694381714 weighted_recall 0.9835164835164835 [0.99095,1,0.848485,0.97561] weighted_recall 0.9853479853479854 [1,1,0.757576,1] weighted_recall 0.9853479853479854 [0.995455,1,0.848485,0.975904] weighted_recall 0.9761904761904762 [1,0.990476,0.727273,0.975904] weighted_recall 0.9908424908424909 [0.995455,1,0.909091,0.987952] weighted_recall 0.9761904761904762 [0.995455,1,0.878788,0.903614] weighted_recall 0.9944954128440368 [1,0.995238,0.96875,0.987952] weighted_recall 0.9908256880733946 [0.995475,0.995215,1,0.963855] weighted_recall 0.9871559633027523 [1,1,0.878788,0.963415] weighted_recall 0.9798165137614679 [1,0.990431,0.969697,0.902439]