10578792 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) 8295074 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 0.5896905561900242 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 1161 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 64 19038 min_samples_split 2 19038 min_weight_fraction_leaf 0.0 19038 n_estimators 100 19038 n_iter_no_change 5 19038 random_state 1514 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.09130627431122447 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 22083851 description https://api.openml.org/data/download/22083851/description.xml -1 22083852 predictions https://api.openml.org/data/download/22083852/predictions.arff area_under_roc_curve 0.9995683171675189 [0.999913,0.999532,0.999911,0.999672,0.999672,0.999712,0.999641,0.99975,0.999123,0.998756] average_cost 0 f_measure 0.97884088768407 [0.991855,0.973958,0.990099,0.977273,0.978836,0.982014,0.989228,0.978873,0.96745,0.959147] kappa 0.9764724250369451 kb_relative_information_score 0.978482965324468 mean_absolute_error 0.005184430784855969 mean_prior_absolute_error 0.17999735782507298 weighted_recall 0.9788256227758008 [0.98917,0.982487,0.987433,0.977273,0.977113,0.978495,0.987455,0.982332,0.965704,0.960854] number_of_instances 5620 [554,571,557,572,568,558,558,566,554,562] precision 0.9788813844631427 [0.994555,0.965577,0.99278,0.977273,0.980565,0.98556,0.991007,0.975439,0.969203,0.957447] predictive_accuracy 0.9788256227758008 prior_entropy 3.3218327251668773 relative_absolute_error 0.028802816038524078 root_mean_prior_squared_error 0.2999977942685968 root_mean_squared_error 0.057714266215319436 root_relative_squared_error 0.1923823018633469 total_cost 0 unweighted_recall 0.9788314658524448 [0.98917,0.982487,0.987433,0.977273,0.977113,0.978495,0.987455,0.982332,0.965704,0.960854] area_under_roc_curve 0.9996973839494859 [1,0.999861,0.999965,0.999966,0.998888,1,0.999718,0.999859,0.999641,0.999082] area_under_roc_curve 0.9997852058049899 [1,1,0.999965,0.999179,0.999896,1,1,0.999965,0.999641,0.999224] area_under_roc_curve 0.9995919233954913 [1,0.999965,0.999965,0.999375,0.999792,0.999965,1,1,0.999928,0.99693] area_under_roc_curve 0.9995566951615906 [1,0.999409,0.999612,0.999062,0.999965,1,1,0.999931,0.999462,0.99813] area_under_roc_curve 0.9998523612096875 [0.999785,0.999687,1,1,1,0.999964,0.999859,0.999931,0.999426,0.999861] area_under_roc_curve 0.9992017747076275 [0.999928,0.999618,0.999965,0.999444,0.999236,0.998386,0.999506,0.999479,0.997812,0.99861] area_under_roc_curve 0.9998450780626523 [1,0.999896,1,0.999653,1,1,0.999928,0.999409,0.999965,0.999612] area_under_roc_curve 0.9996094990351535 [0.999894,0.999861,0.999964,0.999479,0.999965,0.999929,0.999964,0.999792,0.999718,0.99753] area_under_roc_curve 0.9993913485880973 [1,0.999247,0.999641,0.999722,0.999718,0.9994,1,0.999824,0.998165,0.9982] area_under_roc_curve 0.9996939304018596 [0.999965,0.999375,1,0.999965,0.999859,0.999894,0.999471,0.999965,0.999047,0.9994] 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 0.9750297813172518 [1,0.957265,0.99115,0.982456,0.955752,1,0.982143,0.973451,0.964286,0.944444] f_measure 0.9786912081763545 [1,0.982143,0.982143,0.957265,0.982456,0.973913,1,0.981818,0.981818,0.946429] f_measure 0.9874941468923111 [0.990826,0.99115,0.99115,0.991304,0.982143,0.99115,1,0.982759,0.990991,0.963636] f_measure 0.9750845230160786 [1,0.965517,0.981818,0.973451,0.982759,0.981818,0.99115,0.982456,0.954955,0.936937] f_measure 0.9875743767951991 [0.981481,0.991304,1,1,0.991304,0.990826,0.990991,0.982456,0.964286,0.982456] f_measure 0.9626904319072075 [0.990826,0.941176,0.990991,0.947368,0.956522,0.943396,0.990991,0.982456,0.925926,0.957265] f_measure 0.9875583929911227 [0.990991,0.973913,1,0.982456,1,0.982456,0.972477,0.99115,0.990991,0.99115] f_measure 0.9769551648562738 [0.99115,0.982143,0.981818,0.964286,0.982143,0.990991,0.990991,0.957265,0.972973,0.956522] f_measure 0.9787315711369589 [0.99115,0.982759,0.981481,0.982759,0.981818,0.981818,1,0.973451,0.963636,0.948276] f_measure 0.978594026538418 [0.982143,0.974359,1,0.991304,0.973451,0.982143,0.972973,0.982143,0.963636,0.963636] kappa 0.9723207249802994 kappa 0.9762745732659752 kappa 0.9861602651150028 kappa 0.972320335476971 kappa 0.9861600216711405 kappa 0.9584781660310445 kappa 0.9861602164269154 kappa 0.9742979968901491 kappa 0.9762744063324538 kappa 0.9762747401971476 kb_relative_information_score 0.9767427639015991 kb_relative_information_score 0.9806161239865996 kb_relative_information_score 0.9822004423387171 kb_relative_information_score 0.974989608735339 kb_relative_information_score 0.9861008111914655 kb_relative_information_score 0.9651749213374142 kb_relative_information_score 0.9870316074123798 kb_relative_information_score 0.9758697275501261 kb_relative_information_score 0.9752282603975925 kb_relative_information_score 0.9808752691015401 mean_absolute_error 0.005373455071969026 mean_absolute_error 0.005112855794361251 mean_absolute_error 0.0047325788664305535 mean_absolute_error 0.006621547768621796 mean_absolute_error 0.0032914400530476397 mean_absolute_error 0.007967869639914422 mean_absolute_error 0.0030999161850992288 mean_absolute_error 0.005778557398619548 mean_absolute_error 0.005501920808722725 mean_absolute_error 0.00436416626177349 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 0.975525368993247 [1,0.933333,0.982456,1,0.964286,1,0.982143,0.964912,0.947368,0.980769] precision 0.9790095904457446 [1,1,0.982143,0.949153,0.982456,0.949153,1,1,0.981818,0.946429] precision 0.9877241028729503 [1,1,0.982456,0.982759,1,0.982456,1,0.966102,0.982143,0.981481] precision 0.9753882637299676 [1,0.949153,1,0.982143,0.966102,1,0.982456,0.982456,0.946429,0.945455] precision 0.9877931422002055 [1,0.982759,1,1,0.982759,1,1,0.982456,0.947368,0.982456] precision 0.9636013455266089 [1,0.903226,1,0.947368,0.948276,0.980392,1,0.982456,0.943396,0.933333] precision 0.9877268213825493 [1,0.965517,1,0.982456,1,0.965517,0.981481,1,1,0.982456] precision 0.9775520380399808 [0.982456,1,0.981818,0.981818,1,1,0.982143,0.933333,0.981818,0.932203] precision 0.9793891894758241 [0.982456,0.982759,1,0.966102,1,1,1,0.964912,0.981481,0.916667] precision 0.9788435466305208 [0.982143,0.95,1,0.982759,0.964912,0.982143,0.981818,0.982143,0.981481,0.981481] predictive_accuracy 0.9750889679715303 predictive_accuracy 0.9786476868327402 predictive_accuracy 0.9875444839857651 predictive_accuracy 0.9750889679715303 predictive_accuracy 0.9875444839857651 predictive_accuracy 0.9626334519572954 predictive_accuracy 0.9875444839857651 predictive_accuracy 0.9768683274021351 predictive_accuracy 0.9786476868327402 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 0.029853062830412606 relative_absolute_error 0.028405263136586503 relative_absolute_error 0.026292520300571862 relative_absolute_error 0.03678695781756807 relative_absolute_error 0.018286092723966096 relative_absolute_error 0.04426670414763912 relative_absolute_error 0.017221986399544472 relative_absolute_error 0.032103525058638754 relative_absolute_error 0.0305665809355374 relative_absolute_error 0.024245529890991997 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 0.061446768908938444 root_mean_squared_error 0.051914902623196216 root_mean_squared_error 0.04858642917246733 root_mean_squared_error 0.059489565723823024 root_mean_squared_error 0.046860092627348124 root_mean_squared_error 0.07710193387369106 root_mean_squared_error 0.043912953188456706 root_mean_squared_error 0.060123809100918434 root_mean_squared_error 0.06377663336623761 root_mean_squared_error 0.056458815645473115 root_relative_squared_error 0.20482473073018131 root_relative_squared_error 0.17305150684876672 root_relative_squared_error 0.1619561366774186 root_relative_squared_error 0.19830023324100327 root_relative_squared_error 0.15620185216596977 root_relative_squared_error 0.2570089857146367 root_relative_squared_error 0.14637739152693785 root_relative_squared_error 0.2004139030933917 root_relative_squared_error 0.2125896839780676 root_relative_squared_error 0.18819592903766047 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 0.9752159984601001 [1,0.982456,1,0.965517,0.947368,1,0.982143,0.982143,0.981818,0.910714] unweighted_recall 0.9787560987107267 [1,0.964912,0.982143,0.965517,0.982456,1,1,0.964286,0.981818,0.946429] unweighted_recall 0.9875615174299386 [0.981818,0.982456,1,1,0.964912,1,1,1,1,0.946429] unweighted_recall 0.975060378218273 [1,0.982456,0.964286,0.964912,1,0.964286,1,0.982456,0.963636,0.928571] unweighted_recall 0.9874327865117338 [0.963636,1,1,1,1,0.981818,0.982143,0.982456,0.981818,0.982456] unweighted_recall 0.9623934837092729 [0.981818,0.982456,0.982143,0.947368,0.964912,0.909091,0.982143,0.982456,0.909091,0.982456] unweighted_recall 0.987529049897471 [0.982143,0.982456,1,0.982456,1,1,0.963636,0.982456,0.982143,1] unweighted_recall 0.9770038733196627 [1,0.964912,0.981818,0.947368,0.964912,0.982143,1,0.982456,0.964286,0.982143] unweighted_recall 0.9785680698611733 [1,0.982759,0.963636,1,0.964286,0.964286,1,0.982143,0.946429,0.982143] unweighted_recall 0.9785714285714284 [0.982143,1,1,1,0.982143,0.982143,0.964286,0.982143,0.946429,0.946429] usercpu_time_millis 5506.577666001249 usercpu_time_millis 3644.0831380004965 usercpu_time_millis 4117.592250999223 usercpu_time_millis 3808.6286460002157 usercpu_time_millis 5812.15467200127 usercpu_time_millis 5246.690866999415 usercpu_time_millis 5927.674372002002 usercpu_time_millis 4262.740952999593 usercpu_time_millis 5132.206864998807 usercpu_time_millis 6132.546373000878 usercpu_time_millis_testing 5.327000000761473 usercpu_time_millis_testing 5.1069000001007225 usercpu_time_millis_testing 3.982000000178232 usercpu_time_millis_testing 4.845699999350472 usercpu_time_millis_testing 4.435800001374446 usercpu_time_millis_testing 4.363699999885284 usercpu_time_millis_testing 4.478201000893023 usercpu_time_millis_testing 4.685500000050524 usercpu_time_millis_testing 4.41809999938414 usercpu_time_millis_testing 4.59930000033637 usercpu_time_millis_training 5501.250666000487 usercpu_time_millis_training 3638.976238000396 usercpu_time_millis_training 4113.610250999045 usercpu_time_millis_training 3803.782946000865 usercpu_time_millis_training 5807.718871999896 usercpu_time_millis_training 5242.32716699953 usercpu_time_millis_training 5923.196171001109 usercpu_time_millis_training 4258.0554529995425 usercpu_time_millis_training 5127.788764999423 usercpu_time_millis_training 6127.947073000541 wall_clock_time_millis 5509.066581726074 wall_clock_time_millis 3651.7794132232666 wall_clock_time_millis 4120.997428894043 wall_clock_time_millis 3809.2925548553467 wall_clock_time_millis 5827.622652053833 wall_clock_time_millis 5251.644849777222 wall_clock_time_millis 5935.320138931274 wall_clock_time_millis 4267.510175704956 wall_clock_time_millis 5135.741233825684 wall_clock_time_millis 6142.062187194824 wall_clock_time_millis_testing 5.32984733581543 wall_clock_time_millis_testing 5.2700042724609375 wall_clock_time_millis_testing 3.9870738983154297 wall_clock_time_millis_testing 4.851579666137695 wall_clock_time_millis_testing 4.439592361450195 wall_clock_time_millis_testing 4.367589950561523 wall_clock_time_millis_testing 4.481077194213867 wall_clock_time_millis_testing 4.688501358032227 wall_clock_time_millis_testing 4.42194938659668 wall_clock_time_millis_testing 4.602909088134766 wall_clock_time_millis_training 5503.736734390259 wall_clock_time_millis_training 3646.5094089508057 wall_clock_time_millis_training 4117.0103549957275 wall_clock_time_millis_training 3804.440975189209 wall_clock_time_millis_training 5823.183059692383 wall_clock_time_millis_training 5247.27725982666 wall_clock_time_millis_training 5930.839061737061 wall_clock_time_millis_training 4262.821674346924 wall_clock_time_millis_training 5131.319284439087 wall_clock_time_millis_training 6137.459278106689 weighted_recall 0.9750889679715302 [1,0.982456,1,0.965517,0.947368,1,0.982143,0.982143,0.981818,0.910714] weighted_recall 0.9786476868327402 [1,0.964912,0.982143,0.965517,0.982456,1,1,0.964286,0.981818,0.946429] weighted_recall 0.9875444839857651 [0.981818,0.982456,1,1,0.964912,1,1,1,1,0.946429] weighted_recall 0.9750889679715302 [1,0.982456,0.964286,0.964912,1,0.964286,1,0.982456,0.963636,0.928571] weighted_recall 0.9875444839857651 [0.963636,1,1,1,1,0.981818,0.982143,0.982456,0.981818,0.982456] weighted_recall 0.9626334519572953 [0.981818,0.982456,0.982143,0.947368,0.964912,0.909091,0.982143,0.982456,0.909091,0.982456] weighted_recall 0.9875444839857651 [0.982143,0.982456,1,0.982456,1,1,0.963636,0.982456,0.982143,1] weighted_recall 0.9768683274021353 [1,0.964912,0.981818,0.947368,0.964912,0.982143,1,0.982456,0.964286,0.982143] weighted_recall 0.9786476868327402 [1,0.982759,0.963636,1,0.964286,0.964286,1,0.982143,0.946429,0.982143] weighted_recall 0.9786476868327402 [0.982143,1,1,1,0.982143,0.982143,0.964286,0.982143,0.946429,0.946429]