10578706 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) 8294988 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 "mean" 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 0.5260667032632056 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 1100 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 58 19038 min_samples_split 2 19038 min_weight_fraction_leaf 0.0 19038 n_estimators 100 19038 n_iter_no_change 17 19038 random_state 56901 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.06474124040417588 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 22083679 description https://api.openml.org/data/download/22083679/description.xml -1 22083680 predictions https://api.openml.org/data/download/22083680/predictions.arff area_under_roc_curve 0.9996980953994263 [0.99998,0.999658,0.999979,0.999736,0.999601,0.999705,0.999825,0.999888,0.999379,0.999233] average_cost 0 f_measure 0.9820363613413894 [0.993677,0.97561,0.9955,0.979807,0.986831,0.980251,0.984726,0.988546,0.972924,0.9627] kappa 0.980031285328138 kb_relative_information_score 0.9818760695979408 mean_absolute_error 0.004063321046846526 mean_prior_absolute_error 0.17999735782507298 weighted_recall 0.9820284697508896 [0.99278,0.980736,0.992819,0.975524,0.989437,0.978495,0.982079,0.991166,0.972924,0.964413] number_of_instances 5620 [554,571,557,572,568,558,558,566,554,562] precision 0.9820605411179174 [0.994575,0.970537,0.998195,0.984127,0.984238,0.982014,0.987387,0.98594,0.972924,0.960993] predictive_accuracy 0.9820284697508898 prior_entropy 3.3218327251668773 relative_absolute_error 0.022574337178856742 root_mean_prior_squared_error 0.2999977942685968 root_mean_squared_error 0.05449903176978288 root_relative_squared_error 0.18166477491160585 total_cost 0 unweighted_recall 0.9820371655308809 [0.99278,0.980736,0.992819,0.975524,0.989437,0.978495,0.982079,0.991166,0.972924,0.964413] area_under_roc_curve 0.9994365973601222 [1,0.999514,1,0.999863,0.9967,1,0.999682,0.999682,0.999713,0.999259] area_under_roc_curve 0.9999084378556727 [1,0.999896,1,0.999692,1,0.999965,1,1,0.999928,0.999612] area_under_roc_curve 0.9998698260116853 [1,0.999965,0.999965,0.999722,0.999931,1,1,1,0.999928,0.999188] area_under_roc_curve 0.9997958050485539 [1,0.999722,0.999965,0.999097,1,1,1,1,1,0.999188] area_under_roc_curve 0.9998311578546494 [1,0.999722,1,1,1,0.999713,0.999612,1,0.999749,0.999514] area_under_roc_curve 0.9994198832058289 [0.999928,0.999826,1,0.999722,0.99927,0.998781,0.999541,0.999826,0.998279,0.998993] area_under_roc_curve 0.9998029075865077 [0.999965,0.999792,1,0.999757,1,0.999894,0.999821,0.999444,1,0.999365] area_under_roc_curve 0.9997677215725551 [1,0.999653,0.999928,0.999687,0.999896,0.999612,1,0.999757,0.999859,0.999294] area_under_roc_curve 0.9994440966999553 [1,0.99935,0.999928,0.999792,1,0.998694,1,1,0.9982,0.998482] area_under_roc_curve 0.9998417287187483 [0.999965,0.999861,1,1,1,1,0.999753,1,0.998941,0.999894] 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 0.9715032894409232 [1,0.964912,1,0.974359,0.955752,1,0.964286,0.964286,0.947368,0.944444] f_measure 0.9875748791292329 [1,0.973451,1,0.982456,1,0.973913,1,0.990991,0.981818,0.973451] f_measure 0.9874751204532267 [1,0.99115,0.99115,0.973913,0.991304,0.990991,1,0.991304,0.982143,0.962963] f_measure 0.991133441587687 [1,0.991304,0.990991,0.982143,1,0.990991,0.99115,1,1,0.964912] f_measure 0.9821545109097318 [0.990826,0.982759,1,1,0.982759,0.981818,0.972477,0.991304,0.963636,0.955752] f_measure 0.9680124251350453 [0.990826,0.966102,0.990991,0.964912,0.948276,0.952381,0.982143,0.982456,0.953271,0.949153] f_measure 0.9786935377215285 [0.990991,0.955752,1,0.973451,1,0.964912,0.963636,0.982456,0.990991,0.964912] f_measure 0.9839845223932283 [0.99115,0.982143,0.990826,0.973451,0.99115,0.982143,0.990991,0.982759,0.982143,0.973451] f_measure 0.982266190141703 [0.99115,0.982759,0.990826,0.973451,1,0.981818,1,1,0.946429,0.956522] f_measure 0.9875992793866071 [0.982143,0.966102,1,1,1,0.982456,0.981818,1,0.981818,0.981818] kappa 0.9683664315491372 kappa 0.9861604111772093 kappa 0.9861602651150028 kappa 0.9901145098591053 kappa 0.9802284632731392 kappa 0.964409480954006 kappa 0.9762749071259709 kappa 0.9822061803444783 kappa 0.9802289501642896 kappa 0.9861602651150028 kb_relative_information_score 0.9724470339866113 kb_relative_information_score 0.9851893805335032 kb_relative_information_score 0.9873889262101035 kb_relative_information_score 0.9902865239464742 kb_relative_information_score 0.984357429261111 kb_relative_information_score 0.969608067355191 kb_relative_information_score 0.9817301480921325 kb_relative_information_score 0.9799804315105501 kb_relative_information_score 0.9803705097224245 kb_relative_information_score 0.9874019888290332 mean_absolute_error 0.005798852691284966 mean_absolute_error 0.0033426885803235417 mean_absolute_error 0.003060599143044274 mean_absolute_error 0.002381821185879325 mean_absolute_error 0.0035638466071348297 mean_absolute_error 0.006429764266426861 mean_absolute_error 0.003968280060448719 mean_absolute_error 0.004532661163589731 mean_absolute_error 0.00481034119101237 mean_absolute_error 0.0027443555793206413 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 0.9719933167140477 [1,0.964912,1,0.966102,0.964286,1,0.964286,0.964286,0.915254,0.980769] precision 0.9878465710842039 [1,0.982143,1,1,1,0.949153,1,1,0.981818,0.964912] precision 0.9878232825898345 [1,1,0.982456,0.965517,0.982759,1,1,0.982759,0.964912,1] precision 0.9913491699551985 [1,0.982759,1,1,1,1,0.982456,1,1,0.948276] precision 0.982414804829066 [1,0.966102,1,1,0.966102,0.981818,1,0.982759,0.963636,0.964286] precision 0.969160257735005 [1,0.934426,1,0.964912,0.932203,1,0.982143,0.982456,0.980769,0.918033] precision 0.9789205073365708 [1,0.964286,1,0.982143,1,0.948276,0.963636,0.982456,1,0.948276] precision 0.9842000501585709 [0.982456,1,1,0.982143,1,0.982143,0.982143,0.966102,0.982143,0.964912] precision 0.982567751863524 [0.982456,0.982759,1,0.982143,1,1,1,1,0.946429,0.932203] precision 0.9881339156569547 [0.982143,0.934426,1,1,1,0.965517,1,1,1,1] predictive_accuracy 0.9715302491103204 predictive_accuracy 0.9875444839857651 predictive_accuracy 0.9875444839857651 predictive_accuracy 0.9911032028469751 predictive_accuracy 0.9822064056939501 predictive_accuracy 0.9679715302491103 predictive_accuracy 0.9786476868327402 predictive_accuracy 0.9839857651245552 predictive_accuracy 0.9822064056939501 predictive_accuracy 0.9875444839857651 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 0.032216425264313654 relative_absolute_error 0.018570824706706807 relative_absolute_error 0.017003597271501542 relative_absolute_error 0.013232549028664614 relative_absolute_error 0.019799488510118163 relative_absolute_error 0.03572152725681851 relative_absolute_error 0.022046294528586984 relative_absolute_error 0.02518178694259987 relative_absolute_error 0.02672442742351347 relative_absolute_error 0.01524652161232962 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 0.06846263912130551 root_mean_squared_error 0.04671191042028913 root_mean_squared_error 0.04335194251993804 root_mean_squared_error 0.03986621142576647 root_mean_squared_error 0.05075725312409547 root_mean_squared_error 0.07256421789534408 root_mean_squared_error 0.05279433892444426 root_mean_squared_error 0.05840643982121891 root_mean_squared_error 0.056198606897339555 root_mean_squared_error 0.04652849727261792 root_relative_squared_error 0.22821121227513597 root_relative_squared_error 0.15570801595616987 root_relative_squared_error 0.14450769993958235 root_relative_squared_error 0.1328884978059074 root_relative_squared_error 0.16919251551401268 root_relative_squared_error 0.24188311633026316 root_relative_squared_error 0.17598218880848687 root_relative_squared_error 0.19468930437710694 root_relative_squared_error 0.18732948808548677 root_relative_squared_error 0.15509488944883099 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 0.9716143218547938 [1,0.964912,1,0.982759,0.947368,1,0.964286,0.964286,0.981818,0.910714] unweighted_recall 0.9876533418184961 [1,0.964912,1,0.965517,1,1,1,0.982143,0.981818,0.982143] unweighted_recall 0.987562656641604 [1,0.982456,1,0.982456,1,0.982143,1,1,1,0.928571] unweighted_recall 0.9911340852130326 [1,1,0.982143,0.964912,1,0.982143,1,1,1,0.982143] unweighted_recall 0.9821069719753931 [0.981818,1,1,1,1,0.981818,0.946429,1,0.963636,0.947368] unweighted_recall 0.9677204374572795 [0.981818,1,0.982143,0.964912,0.964912,0.909091,0.982143,0.982456,0.927273,0.982456] unweighted_recall 0.9786944634313055 [0.982143,0.947368,1,0.964912,1,0.982143,0.963636,0.982456,0.982143,0.982143] unweighted_recall 0.9840527455001139 [1,0.964912,0.981818,0.964912,0.982456,0.982143,1,1,0.982143,0.982143] unweighted_recall 0.9822346226066735 [1,0.982759,0.981818,0.964912,1,0.964286,1,1,0.946429,0.982143] unweighted_recall 0.9875 [0.982143,1,1,1,1,1,0.964286,1,0.964286,0.964286] usercpu_time_millis 8258.212202999857 usercpu_time_millis 7786.879593000776 usercpu_time_millis 8336.39510499961 usercpu_time_millis 9001.078909999706 usercpu_time_millis 8327.151113000582 usercpu_time_millis 9454.242018000514 usercpu_time_millis 7975.301497001055 usercpu_time_millis 10096.355525000035 usercpu_time_millis 7606.885092000084 usercpu_time_millis 9946.915423999599 usercpu_time_millis_testing 6.504999999378924 usercpu_time_millis_testing 6.522600000607781 usercpu_time_millis_testing 6.827600000178791 usercpu_time_millis_testing 5.66880000042147 usercpu_time_millis_testing 5.694299999959185 usercpu_time_millis_testing 5.934799999522511 usercpu_time_millis_testing 6.464699999924051 usercpu_time_millis_testing 5.90840000040771 usercpu_time_millis_testing 6.721599998854799 usercpu_time_millis_testing 6.1332999994192505 usercpu_time_millis_training 8251.707203000478 usercpu_time_millis_training 7780.356993000169 usercpu_time_millis_training 8329.567504999432 usercpu_time_millis_training 8995.410109999284 usercpu_time_millis_training 8321.456813000623 usercpu_time_millis_training 9448.307218000991 usercpu_time_millis_training 7968.836797001131 usercpu_time_millis_training 10090.447124999628 usercpu_time_millis_training 7600.163492001229 usercpu_time_millis_training 9940.78212400018 wall_clock_time_millis 8262.702703475952 wall_clock_time_millis 7790.034770965576 wall_clock_time_millis 8342.128992080688 wall_clock_time_millis 9016.889333724976 wall_clock_time_millis 8379.305839538574 wall_clock_time_millis 9464.694738388062 wall_clock_time_millis 7987.241744995117 wall_clock_time_millis 10099.377155303955 wall_clock_time_millis 7615.233659744263 wall_clock_time_millis 9949.33009147644 wall_clock_time_millis_testing 6.508827209472656 wall_clock_time_millis_testing 6.526470184326172 wall_clock_time_millis_testing 6.83283805847168 wall_clock_time_millis_testing 5.668401718139648 wall_clock_time_millis_testing 5.698680877685547 wall_clock_time_millis_testing 5.938291549682617 wall_clock_time_millis_testing 6.4678192138671875 wall_clock_time_millis_testing 5.912065505981445 wall_clock_time_millis_testing 6.725788116455078 wall_clock_time_millis_testing 6.136417388916016 wall_clock_time_millis_training 8256.19387626648 wall_clock_time_millis_training 7783.50830078125 wall_clock_time_millis_training 8335.296154022217 wall_clock_time_millis_training 9011.220932006836 wall_clock_time_millis_training 8373.607158660889 wall_clock_time_millis_training 9458.756446838379 wall_clock_time_millis_training 7980.77392578125 wall_clock_time_millis_training 10093.465089797974 wall_clock_time_millis_training 7608.507871627808 wall_clock_time_millis_training 9943.193674087524 weighted_recall 0.9715302491103203 [1,0.964912,1,0.982759,0.947368,1,0.964286,0.964286,0.981818,0.910714] weighted_recall 0.9875444839857651 [1,0.964912,1,0.965517,1,1,1,0.982143,0.981818,0.982143] weighted_recall 0.9875444839857651 [1,0.982456,1,0.982456,1,0.982143,1,1,1,0.928571] weighted_recall 0.9911032028469751 [1,1,0.982143,0.964912,1,0.982143,1,1,1,0.982143] weighted_recall 0.9822064056939501 [0.981818,1,1,1,1,0.981818,0.946429,1,0.963636,0.947368] weighted_recall 0.9679715302491103 [0.981818,1,0.982143,0.964912,0.964912,0.909091,0.982143,0.982456,0.927273,0.982456] weighted_recall 0.9786476868327402 [0.982143,0.947368,1,0.964912,1,0.982143,0.963636,0.982456,0.982143,0.982143] weighted_recall 0.9839857651245552 [1,0.964912,0.981818,0.964912,0.982456,0.982143,1,1,0.982143,0.982143] weighted_recall 0.9822064056939501 [1,0.982759,0.981818,0.964912,1,0.964286,1,1,0.946429,0.982143] weighted_recall 0.9875444839857651 [0.982143,1,1,1,1,1,0.964286,1,0.964286,0.964286]