10578906 28997 Marc Boel 28 Supervised Classification 19037 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),gradientboostingclassifier=sklearn.ensemble._gb.GradientBoostingClassifier)(1) 8295188 Python_3.8.10. Sklearn_0.24.2. NumPy_1.17.4. SciPy_1.3.3. add_indicator false 18819 copy true 18819 fill_value null 18819 missing_values NaN 18819 strategy "median" 18819 verbose 0 18819 n_jobs null 18996 remainder "drop" 18996 sparse_threshold 0.3 18996 transformer_weights null 18996 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"}}}] 18996 verbose false 18996 categories "auto" 18997 drop null 18997 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 18997 handle_unknown "ignore" 18997 sparse true 18997 memory null 19037 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"}}] 19037 verbose false 19037 ccp_alpha 0.0 19038 criterion "friedman_mse" 19038 init null 19038 learning_rate 0.07443433148841704 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 947 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 113 19038 min_samples_split 2 19038 min_weight_fraction_leaf 0.0 19038 n_estimators 100 19038 n_iter_no_change 13 19038 random_state 49994 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.37147477265999673 19038 verbose 0 19038 warm_start false 19038 openml-python Sklearn_0.24.2. 28 optdigits https://www.openml.org/data/download/28/dataset_28_optdigits.arff -1 22084079 description https://api.openml.org/data/download/22084079/description.xml -1 22084080 predictions https://api.openml.org/data/download/22084080/predictions.arff area_under_roc_curve 0.9993067748284951 [0.999934,0.999291,0.999829,0.999503,0.999617,0.998829,0.999478,0.999736,0.999041,0.997808] average_cost 0 f_measure 0.9731472560072313 [0.98913,0.969592,0.986499,0.969271,0.970976,0.979335,0.983871,0.976253,0.960145,0.946809] kappa 0.9701457084464687 kb_relative_information_score 0.9633059540803156 mean_absolute_error 0.010698309007508408 mean_prior_absolute_error 0.17999735782507298 weighted_recall 0.9731316725978648 [0.98556,0.977233,0.983842,0.965035,0.971831,0.976703,0.983871,0.980565,0.956679,0.950178] number_of_instances 5620 [554,571,557,572,568,558,558,566,554,562] precision 0.9731929082136295 [0.992727,0.962069,0.98917,0.973545,0.970123,0.981982,0.983871,0.971979,0.963636,0.943463] predictive_accuracy 0.9731316725978648 prior_entropy 3.3218327251668773 relative_absolute_error 0.05943592248673649 root_mean_prior_squared_error 0.2999977942685968 root_mean_squared_error 0.06532662037584569 root_relative_squared_error 0.21775700229767975 total_cost 0 unweighted_recall 0.9731495937234289 [0.98556,0.977233,0.983842,0.965035,0.971831,0.976703,0.983871,0.980565,0.956679,0.950178] area_under_roc_curve 0.9993526527432283 [1,0.999653,0.999824,0.999453,0.999131,1,0.999047,0.999718,0.999175,0.99753] area_under_roc_curve 0.9995528091920703 [1,0.999444,1,0.999213,0.998993,0.999718,1,0.999929,0.999785,0.998482] area_under_roc_curve 0.9996798920906258 [1,0.999965,1,0.999618,0.999826,1,1,0.999965,0.999892,0.99753] area_under_roc_curve 0.9994230462408217 [1,0.999375,0.999577,0.998819,1,0.999965,1,0.999757,0.999139,0.9976] area_under_roc_curve 0.9995954320187501 [0.999892,0.999687,1,0.999965,0.999965,0.999175,0.999329,1,0.999641,0.998298] area_under_roc_curve 0.9986608051721331 [0.999928,0.999618,0.999965,0.999375,0.999097,0.99419,0.999682,0.999375,0.997669,0.997603] area_under_roc_curve 0.9996236067057682 [0.999824,0.999409,1,0.999792,1,0.999753,0.999677,0.999861,0.999294,0.998624] area_under_roc_curve 0.9990394953331673 [0.999824,0.999131,0.999857,0.999201,0.999618,0.998588,0.999964,0.999409,0.999471,0.995342] area_under_roc_curve 0.998765009653082 [1,0.998084,0.999103,0.999583,0.999859,0.997318,1,0.999682,0.997671,0.996365] area_under_roc_curve 0.9994477739588905 [0.999788,0.99934,1,1,0.999894,0.999929,0.997283,1,0.998588,0.999647] 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 0.9715887668495156 [1,0.973913,0.982143,0.982456,0.955752,1,0.955752,0.973451,0.938053,0.954128] f_measure 0.9805312300452792 [1,0.982143,0.99115,0.956522,0.973913,0.982143,1,0.981818,0.990826,0.948276] f_measure 0.9804014562973562 [0.981481,0.99115,0.99115,0.964912,0.965517,1,1,0.974359,0.981818,0.954128] f_measure 0.9733538372996278 [1,0.948276,0.972973,0.964286,1,0.990991,0.99115,0.973451,0.964286,0.928571] f_measure 0.9768248515310588 [0.981481,0.965517,1,0.982759,0.974359,0.990826,0.981818,0.991304,0.944444,0.955752] f_measure 0.9536843041960332 [0.981818,0.966102,0.972477,0.948276,0.93913,0.934579,0.982143,0.982456,0.915888,0.913793] f_measure 0.9769594851101855 [0.990991,0.965517,0.990991,0.982143,0.99115,0.964912,0.963636,0.982456,0.981818,0.955752] f_measure 0.9679520054710815 [0.99115,0.982143,0.981818,0.954955,0.955752,0.964286,0.990991,0.93913,0.955752,0.964912] f_measure 0.9716931971026908 [0.99115,0.965517,0.990826,0.964912,0.972477,0.981818,1,0.973451,0.946429,0.931034] f_measure 0.978655412887051 [0.972973,0.957265,0.990991,0.991304,0.982143,0.982456,0.972973,0.99115,0.981818,0.963636] kappa 0.9683668766864023 kappa 0.9782518451807186 kappa 0.9782513861135347 kappa 0.9703437382368773 kappa 0.9742963692654095 kappa 0.9485921959491551 kappa 0.9742978160531353 kappa 0.964412861464856 kappa 0.9683662089758067 kappa 0.9762747401971476 kb_relative_information_score 0.96004331249797 kb_relative_information_score 0.9682714114566879 kb_relative_information_score 0.9688571083623623 kb_relative_information_score 0.962312079765467 kb_relative_information_score 0.9685523877942768 kb_relative_information_score 0.9493997491130882 kb_relative_information_score 0.9659930660405113 kb_relative_information_score 0.9586557685287219 kb_relative_information_score 0.9605820133221442 kb_relative_information_score 0.9703924208625277 mean_absolute_error 0.011650194982424058 mean_absolute_error 0.009613552759436357 mean_absolute_error 0.009945632928826864 mean_absolute_error 0.011037350667872729 mean_absolute_error 0.009305047941168541 mean_absolute_error 0.013607840460057414 mean_absolute_error 0.010343491447397785 mean_absolute_error 0.011184427553078002 mean_absolute_error 0.011423046891495255 mean_absolute_error 0.008872504443327189 mean_prior_absolute_error 0.17999677629374952 mean_prior_absolute_error 0.17999677629374952 mean_prior_absolute_error 0.17999715555330845 mean_prior_absolute_error 0.17999715555330845 mean_prior_absolute_error 0.1799969027136025 mean_prior_absolute_error 0.1799969027136025 mean_prior_absolute_error 0.17999759802279386 mean_prior_absolute_error 0.17999759802279386 mean_prior_absolute_error 0.1799979140724263 mean_prior_absolute_error 0.17999879901139712 number_of_instances 562 [55,57,56,58,57,56,56,56,55,56] number_of_instances 562 [55,57,56,58,57,56,56,56,55,56] number_of_instances 562 [55,57,56,57,57,56,56,57,55,56] number_of_instances 562 [55,57,56,57,57,56,56,57,55,56] number_of_instances 562 [55,57,56,57,57,55,56,57,55,57] number_of_instances 562 [55,57,56,57,57,55,56,57,55,57] number_of_instances 562 [56,57,55,57,57,56,55,57,56,56] number_of_instances 562 [56,57,55,57,57,56,55,57,56,56] number_of_instances 562 [56,58,55,57,56,56,56,56,56,56] number_of_instances 562 [56,57,56,57,56,56,56,56,56,56] precision 0.972043602646303 [1,0.965517,0.982143,1,0.964286,1,0.947368,0.964912,0.913793,0.981132] precision 0.9810503064631759 [1,1,0.982456,0.964912,0.965517,0.982143,1,1,1,0.916667] precision 0.9808054003582178 [1,1,0.982456,0.964912,0.949153,1,1,0.95,0.981818,0.981132] precision 0.9736405651965839 [1,0.932203,0.981818,0.981818,1,1,0.982456,0.982143,0.947368,0.928571] precision 0.9772696564428941 [1,0.949153,1,0.966102,0.95,1,1,0.982759,0.962264,0.964286] precision 0.9544159824049726 [0.981818,0.934426,1,0.932203,0.931034,0.961538,0.982143,0.982456,0.942308,0.898305] precision 0.9773587756457667 [1,0.949153,0.982143,1,1,0.948276,0.963636,0.982456,1,0.947368] precision 0.9682725561090519 [0.982456,1,0.981818,0.981481,0.964286,0.964286,0.982143,0.931034,0.947368,0.948276] precision 0.9723356433789099 [0.982456,0.965517,1,0.964912,1,1,1,0.964912,0.946429,0.9] precision 0.9790575624249114 [0.981818,0.933333,1,0.982759,0.982143,0.965517,0.981818,0.982456,1,0.981481] predictive_accuracy 0.9715302491103204 predictive_accuracy 0.9804270462633453 predictive_accuracy 0.9804270462633453 predictive_accuracy 0.9733096085409252 predictive_accuracy 0.9768683274021351 predictive_accuracy 0.9537366548042705 predictive_accuracy 0.9768683274021351 predictive_accuracy 0.9679715302491103 predictive_accuracy 0.9715302491103204 predictive_accuracy 0.9786476868327402 prior_entropy 3.3217909017967746 prior_entropy 3.3217909017967746 prior_entropy 3.321817923867619 prior_entropy 3.321817923867619 prior_entropy 3.3217996202390836 prior_entropy 3.3217996202390836 prior_entropy 3.3218501976437715 prior_entropy 3.3218501976437715 prior_entropy 3.321873176216062 prior_entropy 3.3219367883600994 relative_absolute_error 0.06472446463936264 relative_absolute_error 0.053409582979126895 relative_absolute_error 0.0552543894277337 relative_absolute_error 0.061319583823111465 relative_absolute_error 0.05169560031804565 relative_absolute_error 0.07560041453440554 relative_absolute_error 0.057464608200426905 relative_absolute_error 0.062136537797919236 relative_absolute_error 0.06346210704919018 relative_absolute_error 0.04929202023600948 root_mean_prior_squared_error 0.2999968250410308 root_mean_prior_squared_error 0.2999968250410308 root_mean_prior_squared_error 0.2999974571463194 root_mean_prior_squared_error 0.2999974571463194 root_mean_prior_squared_error 0.2999970357429417 root_mean_prior_squared_error 0.2999970357429417 root_mean_prior_squared_error 0.2999981946008062 root_mean_prior_squared_error 0.2999981946008062 root_mean_prior_squared_error 0.2999987213529011 root_mean_prior_squared_error 0.3000001962538465 root_mean_squared_error 0.06992889397163898 root_mean_squared_error 0.05688534940384161 root_mean_squared_error 0.05700813752844789 root_mean_squared_error 0.0651382297048821 root_mean_squared_error 0.059365228239800415 root_mean_squared_error 0.08098288251416572 root_mean_squared_error 0.061659094117581685 root_mean_squared_error 0.07188142804364957 root_mean_squared_error 0.06864374541104099 root_mean_squared_error 0.05738953250845109 root_relative_squared_error 0.23309878016900595 root_relative_squared_error 0.18961983813015806 root_relative_squared_error 0.19002873581239388 root_relative_squared_error 0.21712927277617514 root_relative_squared_error 0.19788604941639715 root_relative_squared_error 0.26994560900780856 root_relative_squared_error 0.20553155061359157 root_relative_squared_error 0.2396062020949789 root_relative_squared_error 0.22881345994235908 root_relative_squared_error 0.19129831655140211 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 0.9716121023562041 [1,0.982456,0.982143,0.965517,0.947368,1,0.964286,0.982143,0.963636,0.928571] unweighted_recall 0.9806033893511208 [1,0.964912,1,0.948276,0.982456,0.982143,1,0.964286,0.981818,0.982143] unweighted_recall 0.9803850535429482 [0.963636,0.982456,1,0.964912,0.982456,1,1,1,0.981818,0.928571] unweighted_recall 0.9734011164274323 [1,0.964912,0.964286,0.947368,1,0.982143,1,0.964912,0.981818,0.928571] unweighted_recall 0.9766837548416495 [0.963636,0.982456,1,1,1,0.981818,0.964286,1,0.927273,0.947368] unweighted_recall 0.9534951013898383 [0.981818,1,0.946429,0.964912,0.947368,0.909091,0.982143,0.982456,0.890909,0.929825] unweighted_recall 0.976877420824789 [0.982143,0.982456,1,0.964912,0.982456,0.982143,0.963636,0.982456,0.964286,0.964286] unweighted_recall 0.9682006151742995 [1,0.964912,0.981818,0.929825,0.947368,0.964286,1,0.947368,0.964286,0.982143] unweighted_recall 0.9715819132470674 [1,0.965517,0.981818,0.964912,0.946429,0.964286,1,0.982143,0.946429,0.964286] unweighted_recall 0.9786027568922305 [0.964286,0.982456,0.982143,1,0.982143,1,0.964286,1,0.964286,0.946429] usercpu_time_millis 10858.471133999046 usercpu_time_millis 10901.70973399836 usercpu_time_millis 10870.544438001161 usercpu_time_millis 10918.619535999824 usercpu_time_millis 10871.534834999693 usercpu_time_millis 10859.485332000986 usercpu_time_millis 10792.338036000729 usercpu_time_millis 10922.610926998459 usercpu_time_millis 10933.503832000497 usercpu_time_millis 10930.150337000669 usercpu_time_millis_testing 9.871300999293453 usercpu_time_millis_testing 9.613999998691725 usercpu_time_millis_testing 9.931901000527432 usercpu_time_millis_testing 9.59100000000035 usercpu_time_millis_testing 10.528700000577373 usercpu_time_millis_testing 9.940100000676466 usercpu_time_millis_testing 10.36740000017744 usercpu_time_millis_testing 8.447199999864097 usercpu_time_millis_testing 8.150401001330465 usercpu_time_millis_testing 8.510501000273507 usercpu_time_millis_training 10848.599832999753 usercpu_time_millis_training 10892.095733999668 usercpu_time_millis_training 10860.612537000634 usercpu_time_millis_training 10909.028535999823 usercpu_time_millis_training 10861.006134999116 usercpu_time_millis_training 10849.54523200031 usercpu_time_millis_training 10781.970636000551 usercpu_time_millis_training 10914.163726998595 usercpu_time_millis_training 10925.353430999166 usercpu_time_millis_training 10921.639836000395 wall_clock_time_millis 10861.895561218262 wall_clock_time_millis 10921.42105102539 wall_clock_time_millis 10876.709461212158 wall_clock_time_millis 10924.063205718994 wall_clock_time_millis 10898.382425308228 wall_clock_time_millis 10870.140552520752 wall_clock_time_millis 10803.423166275024 wall_clock_time_millis 10957.184076309204 wall_clock_time_millis 10988.389015197754 wall_clock_time_millis 10937.669038772583 wall_clock_time_millis_testing 9.874105453491211 wall_clock_time_millis_testing 9.617090225219727 wall_clock_time_millis_testing 9.932756423950195 wall_clock_time_millis_testing 9.596109390258789 wall_clock_time_millis_testing 10.536670684814453 wall_clock_time_millis_testing 9.943962097167969 wall_clock_time_millis_testing 10.372161865234375 wall_clock_time_millis_testing 8.450984954833984 wall_clock_time_millis_testing 8.152484893798828 wall_clock_time_millis_testing 8.513212203979492 wall_clock_time_millis_training 10852.02145576477 wall_clock_time_millis_training 10911.80396080017 wall_clock_time_millis_training 10866.776704788208 wall_clock_time_millis_training 10914.467096328735 wall_clock_time_millis_training 10887.845754623413 wall_clock_time_millis_training 10860.196590423584 wall_clock_time_millis_training 10793.05100440979 wall_clock_time_millis_training 10948.73309135437 wall_clock_time_millis_training 10980.236530303955 wall_clock_time_millis_training 10929.155826568604 weighted_recall 0.9715302491103203 [1,0.982456,0.982143,0.965517,0.947368,1,0.964286,0.982143,0.963636,0.928571] weighted_recall 0.9804270462633452 [1,0.964912,1,0.948276,0.982456,0.982143,1,0.964286,0.981818,0.982143] weighted_recall 0.9804270462633452 [0.963636,0.982456,1,0.964912,0.982456,1,1,1,0.981818,0.928571] weighted_recall 0.9733096085409253 [1,0.964912,0.964286,0.947368,1,0.982143,1,0.964912,0.981818,0.928571] weighted_recall 0.9768683274021353 [0.963636,0.982456,1,1,1,0.981818,0.964286,1,0.927273,0.947368] weighted_recall 0.9537366548042705 [0.981818,1,0.946429,0.964912,0.947368,0.909091,0.982143,0.982456,0.890909,0.929825] weighted_recall 0.9768683274021353 [0.982143,0.982456,1,0.964912,0.982456,0.982143,0.963636,0.982456,0.964286,0.964286] weighted_recall 0.9679715302491103 [1,0.964912,0.981818,0.929825,0.947368,0.964286,1,0.947368,0.964286,0.982143] weighted_recall 0.9715302491103203 [1,0.965517,0.981818,0.964912,0.946429,0.964286,1,0.982143,0.946429,0.964286] weighted_recall 0.9786476868327402 [0.964286,0.982456,0.982143,1,0.982143,1,0.964286,1,0.964286,0.946429]