10317725 8323 Heinrich Peters 3481 Supervised Classification 12736 sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,histgradientboostingclassifier=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1) 8155383 l2_regularization 1e-09 12677 learning_rate 0.1 12677 loss "auto" 12677 max_bins 32 12677 max_depth 11 12677 max_iter 50 12677 max_leaf_nodes 16 12677 min_samples_leaf 8 12677 n_iter_no_change null 12677 random_state 4137 12677 scoring null 12677 tol 1e-07 12677 validation_fraction 0.1 12677 verbose 0 12677 memory null 12736 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "histgradientboostingclassifier", "step_name": "histgradientboostingclassifier"}}] 12736 verbose false 12736 add_indicator false 12737 copy true 12737 fill_value null 12737 missing_values NaN 12737 strategy "most_frequent" 12737 verbose 0 12737 openml-python Sklearn_0.21.2. 300 isolet https://www.openml.org/data/download/52405/phpB0xrNj -1 21557133 description https://api.openml.org/data/download/21557133/description.xml -1 21557134 predictions https://api.openml.org/data/download/21557134/predictions.arff area_under_roc_curve 0.9987319307814518 [0.999501,0.998274,0.999194,0.997623,0.998717,0.99884,0.998133,0.998405,0.998256,0.999277,0.999655,0.999918,0.998488,0.998555,0.999212,0.996546,0.99953,0.999859,0.99796,0.99615,0.999311,0.998279,0.999336,0.999765,0.99995,0.998296] average_cost 0 f_measure 0.9526371795718499 [0.952998,0.894309,0.986755,0.917763,0.907563,0.946844,0.954469,0.979661,0.976589,0.9699,0.958124,0.978512,0.919463,0.92257,0.972881,0.903974,0.98,0.983444,0.964587,0.928814,0.963211,0.906667,0.975124,0.983333,0.989933,0.950931] kappa 0.950647689520697 kb_relative_information_score 0.9577762276215133 mean_absolute_error 0.00476923134319116 mean_prior_absolute_error 0.07396449117237175 number_of_instances 7797 [300,300,300,300,300,298,300,300,300,300,300,300,299,300,300,300,300,300,300,300,300,300,300,300,300,300] precision 0.9529855448633676 [0.927445,0.873016,0.980263,0.905844,0.915254,0.9375,0.96587,0.996552,0.979866,0.973154,0.962963,0.970492,0.922559,0.912052,0.989655,0.898026,0.98,0.976974,0.976109,0.944828,0.966443,0.906667,0.970297,0.983333,0.996622,0.965636] predictive_accuracy 0.9525458509683211 prior_entropy 4.700438279892712 recall 0.9525458509683211 [0.98,0.916667,0.993333,0.93,0.9,0.956376,0.943333,0.963333,0.973333,0.966667,0.953333,0.986667,0.916388,0.933333,0.956667,0.91,0.98,0.99,0.953333,0.913333,0.96,0.906667,0.98,0.983333,0.983333,0.936667] relative_absolute_error 0.06448001287640345 root_mean_prior_squared_error 0.19230768465256318 root_mean_squared_error 0.05278114281546227 root_relative_squared_error 0.2744619535658206 total_cost 0 area_under_roc_curve 0.9990940170940174 [0.997867,0.999422,0.999822,0.995822,0.999511,0.999956,0.999689,1,1,0.999956,0.999422,1,0.999467,0.999422,0.993733,0.998711,0.997333,0.999867,1,0.998933,0.999911,0.9988,1,0.999022,1,0.999778] area_under_roc_curve 0.9980803418803419 [0.9984,0.998044,1,0.999556,0.998622,0.999778,0.998756,0.998,0.984222,0.999467,0.9996,1,0.997067,0.9976,1,0.986667,1,0.999511,1,0.999244,0.999378,0.9964,1,1,1,0.999778] area_under_roc_curve 0.9988393162393162 [0.999822,0.999422,1,0.998622,0.999644,0.999378,0.998889,0.991067,0.9984,0.996044,0.999911,1,0.999822,0.9992,1,0.999867,0.999956,0.9992,0.997956,0.999289,1,0.999644,0.999778,0.998622,0.999911,0.995378] area_under_roc_curve 0.9993367521367523 [0.999644,0.998933,0.999822,0.999556,0.999778,0.999867,0.999689,1,1,0.999156,1,0.999867,0.9984,0.999022,0.999956,0.992,1,1,0.999822,0.999111,1,0.998178,1,1,1,0.999956] area_under_roc_curve 0.9979401709401711 [1,0.998711,1,0.999111,0.997867,0.998311,0.999067,0.997911,1,0.999511,0.999867,0.999911,0.998711,0.997822,1,0.999911,1,1,0.981867,0.987733,0.999289,0.997156,0.996267,0.999911,0.999911,0.9976] area_under_roc_curve 0.9989623931623931 [1,0.9992,0.9924,0.992578,0.999778,0.998622,0.998178,1,1,0.999644,0.998756,1,0.999378,0.9996,0.999956,0.997422,0.999733,1,0.999956,0.999733,1,0.998889,1,1,1,0.9992] area_under_roc_curve 0.9988974358974357 [0.999822,0.997911,1,0.998978,0.995289,0.9992,1,0.997022,1,0.999956,1,0.999867,0.998267,0.996044,0.999778,0.993333,0.999689,1,0.999778,0.999867,0.998267,0.999733,1,1,1,0.998533] area_under_roc_curve 0.9988380022314733 [0.999911,0.99644,1,0.997063,0.998175,1,0.995639,1,0.999822,0.999866,0.999911,0.999911,0.999724,0.998932,0.998887,0.999822,0.999866,1,1,0.987672,0.999288,0.999243,0.999955,1,0.999866,0.999822] area_under_roc_curve 0.9982330341467986 [0.999911,0.996929,1,0.994482,0.999199,0.99908,0.993591,1,0.999911,0.999822,0.999243,1,0.998754,1,1,0.998576,0.998843,0.999911,1,0.989497,0.997196,0.997819,0.996751,1,0.999911,0.99466] area_under_roc_curve 0.9992204788241404 [1,0.997908,1,1,0.999466,0.994069,0.999288,1,1,0.999955,0.999777,0.999822,0.995238,0.99862,0.999777,0.999599,1,1,0.99951,1,0.999911,0.998487,0.999955,1,1,0.998175] 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 0.9462674743695005 [0.933333,0.896552,0.95082,0.892308,0.95082,0.966667,0.947368,0.983051,1,0.983051,0.90625,1,0.9,0.885246,0.965517,0.872727,0.966667,0.983607,0.983607,0.933333,0.949153,0.870968,0.983607,0.949153,1,0.949153] f_measure 0.9452116437652915 [0.875,0.888889,1,0.95082,0.885246,0.9375,0.966667,0.947368,0.983051,0.952381,0.947368,0.983607,0.918033,0.903226,0.983051,0.813559,0.983051,0.983607,0.947368,0.947368,0.947368,0.9,0.983607,1,1,0.947368] f_measure 0.9524607793666239 [0.967742,0.918033,0.983607,0.896552,0.903226,0.918033,0.947368,0.966667,0.931034,0.949153,0.966667,1,0.966667,0.933333,1,0.949153,0.983607,0.966667,0.933333,0.903226,1,0.9375,0.966667,0.983051,0.983607,0.909091] f_measure 0.959987949764523 [0.935484,0.888889,0.983607,0.95082,0.933333,0.983607,0.952381,0.965517,0.983051,0.983051,1,0.966667,0.933333,0.949153,0.983607,0.881356,1,0.967742,0.983051,0.912281,0.983607,0.888889,1,0.983607,0.983051,0.983607] f_measure 0.9448842537913962 [0.9375,0.885246,1,0.9375,0.896552,0.903226,0.966667,0.965517,0.983607,0.966667,0.947368,0.983607,0.896552,0.903226,1,0.966667,0.983051,1,0.915254,0.915254,0.95082,0.881356,0.915254,0.983051,0.983051,0.9] f_measure 0.9666919059753138 [1,0.903226,0.983051,0.847458,0.933333,0.947368,0.983051,1,1,0.983051,0.95082,1,0.966667,0.966667,0.983051,0.885246,0.983051,1,0.983607,0.983607,1,0.915254,1,0.967742,1,0.967742] f_measure 0.9470125333897145 [0.967742,0.903226,1,0.892857,0.793103,0.933333,0.952381,0.965517,0.967742,0.966667,0.983051,0.967742,0.9,0.933333,0.909091,0.9,0.966667,1,0.965517,0.967742,0.933333,0.9375,0.983607,0.983607,0.983051,0.965517] f_measure 0.9537125460431052 [0.983607,0.875,1,0.949153,0.862069,0.983051,0.949153,1,0.966667,0.966667,0.95082,0.967742,0.949153,0.915254,0.949153,0.923077,0.983607,0.983051,1,0.877193,0.949153,0.912281,0.983607,0.983051,0.983051,0.95082] f_measure 0.9488158970198964 [0.967742,0.870968,1,0.875,0.965517,0.949153,0.931034,1,0.966667,0.965517,0.965517,0.983051,0.896552,0.952381,1,0.892308,0.95082,0.966667,0.983051,0.851852,0.933333,0.903226,0.949153,1,0.983051,0.966667] f_measure 0.9600846054965955 [0.966667,0.915254,0.967742,0.983607,0.949153,0.949153,0.947368,1,0.983051,0.983607,0.966667,0.933333,0.866667,0.885246,0.949153,0.95082,1,0.983607,0.949153,0.983607,0.983607,0.915254,0.983607,1,1,0.965517] kappa 0.944 kappa 0.9426666666666667 kappa 0.9506666666666667 kappa 0.9586666666666667 kappa 0.9426666666666667 kappa 0.9653333333333334 kappa 0.9453333333333332 kappa 0.9519383857097075 kappa 0.9465982063441194 kappa 0.9586136099166925 kb_relative_information_score 0.9583259477211028 kb_relative_information_score 0.9515560383848056 kb_relative_information_score 0.9588629688164256 kb_relative_information_score 0.964395884840456 kb_relative_information_score 0.9504970296622054 kb_relative_information_score 0.964589863506285 kb_relative_information_score 0.9555118550202107 kb_relative_information_score 0.9610096837843123 kb_relative_information_score 0.9496142230660165 kb_relative_information_score 0.9633996697728594 mean_absolute_error 0.0050107040405738615 mean_absolute_error 0.005329447404185284 mean_absolute_error 0.004671554939534775 mean_absolute_error 0.004181661677465696 mean_absolute_error 0.005387078894384346 mean_absolute_error 0.004076207596028717 mean_absolute_error 0.004912458071125277 mean_absolute_error 0.0043736976722839995 mean_absolute_error 0.005451120735902236 mean_absolute_error 0.004298145567024529 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396448587535052 mean_prior_absolute_error 0.07396447325283656 mean_prior_absolute_error 0.07396447325283656 number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 779 [30,30,30,30,30,30,30,30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 779 [30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 779 [30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] precision 0.9482902710797675 [0.933333,0.928571,0.935484,0.828571,0.935484,0.966667,1,1,1,1,0.852941,1,0.9,0.870968,1,0.96,0.966667,0.967742,0.967742,0.933333,0.965517,0.84375,0.967742,0.965517,1,0.965517] precision 0.9479082388417925 [0.823529,0.848485,1,0.935484,0.870968,0.882353,0.966667,1,1,0.909091,1,0.967742,0.903226,0.875,1,0.827586,1,0.967742,1,1,1,0.9,0.967742,1,1,1] precision 0.9539777686979644 [0.9375,0.903226,0.967742,0.928571,0.875,0.903226,1,0.966667,0.964286,0.965517,0.966667,1,0.966667,0.933333,1,0.965517,0.967742,0.966667,0.933333,0.875,1,0.882353,0.966667,1,0.967742,1] precision 0.9616010193561638 [0.90625,0.848485,0.967742,0.935484,0.933333,0.967742,0.909091,1,1,1,1,0.966667,0.933333,0.965517,0.967742,0.896552,1,0.9375,1,0.962963,0.967742,1,1,0.967742,1,0.967742] precision 0.9462861306069443 [0.882353,0.870968,1,0.882353,0.928571,0.875,0.966667,1,0.967742,0.966667,1,0.967742,0.928571,0.875,1,0.966667,1,1,0.931034,0.931034,0.935484,0.896552,0.931034,1,1,0.9] precision 0.9673732922620575 [1,0.875,1,0.862069,0.933333,1,1,1,1,1,0.935484,1,0.966667,0.966667,1,0.870968,1,1,0.967742,0.967742,1,0.931034,1,0.9375,1,0.9375] precision 0.9487780033667496 [0.9375,0.875,1,0.961538,0.821429,0.933333,0.909091,1,0.9375,0.966667,1,0.9375,0.9,0.933333,1,0.9,0.966667,1,1,0.9375,0.933333,0.882353,0.967742,0.967742,1,1] precision 0.9551773114071416 [0.967742,0.823529,1,0.965517,0.892857,1,0.965517,1,0.966667,0.966667,0.935484,0.9375,0.933333,0.931034,0.965517,0.857143,0.967742,1,1,0.925926,0.965517,0.962963,0.967742,1,1,0.935484] precision 0.9514193412138686 [0.9375,0.84375,1,0.823529,1,0.933333,0.964286,1,0.966667,1,1,1,0.928571,0.909091,1,0.828571,0.935484,0.966667,1,0.958333,0.933333,0.875,0.965517,1,1,0.966667] precision 0.9606384905398142 [0.966667,0.931034,0.9375,0.967742,0.965517,0.933333,1,1,1,0.967742,0.966667,0.933333,0.866667,0.870968,0.965517,0.935484,1,0.967742,0.965517,0.967742,0.967742,0.931034,0.967742,1,1,1] predictive_accuracy 0.9461538461538461 predictive_accuracy 0.9448717948717948 predictive_accuracy 0.9525641025641026 predictive_accuracy 0.9602564102564102 predictive_accuracy 0.9448717948717948 predictive_accuracy 0.9666666666666667 predictive_accuracy 0.9474358974358974 predictive_accuracy 0.9537869062901155 predictive_accuracy 0.9486521181001284 predictive_accuracy 0.9602053915275995 prior_entropy 4.700441149362989 prior_entropy 4.700441149362989 prior_entropy 4.700441149362989 prior_entropy 4.700441149362989 prior_entropy 4.700441149362989 prior_entropy 4.700441149362989 prior_entropy 4.700441149362989 prior_entropy 4.700435698259304 prior_entropy 4.700429514669705 prior_entropy 4.700429514669705 recall 0.9461538461538461 [0.933333,0.866667,0.966667,0.966667,0.966667,0.966667,0.9,0.966667,1,0.966667,0.966667,1,0.9,0.9,0.933333,0.8,0.966667,1,1,0.933333,0.933333,0.9,1,0.933333,1,0.933333] recall 0.9448717948717948 [0.933333,0.933333,1,0.966667,0.9,1,0.966667,0.9,0.966667,1,0.9,1,0.933333,0.933333,0.966667,0.8,0.966667,1,0.9,0.9,0.9,0.9,1,1,1,0.9] recall 0.9525641025641025 [1,0.933333,1,0.866667,0.933333,0.933333,0.9,0.966667,0.9,0.933333,0.966667,1,0.966667,0.933333,1,0.933333,1,0.966667,0.933333,0.933333,1,1,0.966667,0.966667,1,0.833333] recall 0.9602564102564103 [0.966667,0.933333,1,0.966667,0.933333,1,1,0.933333,0.966667,0.966667,1,0.966667,0.933333,0.933333,1,0.866667,1,1,0.966667,0.866667,1,0.8,1,1,0.966667,1] recall 0.9448717948717948 [1,0.9,1,1,0.866667,0.933333,0.966667,0.933333,1,0.966667,0.9,1,0.866667,0.933333,1,0.966667,0.966667,1,0.9,0.9,0.966667,0.866667,0.9,0.966667,0.966667,0.9] recall 0.9666666666666667 [1,0.933333,0.966667,0.833333,0.933333,0.9,0.966667,1,1,0.966667,0.966667,1,0.966667,0.966667,0.966667,0.9,0.966667,1,1,1,1,0.9,1,1,1,1] recall 0.9474358974358974 [1,0.933333,1,0.833333,0.766667,0.933333,1,0.933333,1,0.966667,0.966667,1,0.9,0.933333,0.833333,0.9,0.966667,1,0.933333,1,0.933333,1,1,1,0.966667,0.933333] recall 0.9537869062901155 [1,0.933333,1,0.933333,0.833333,0.966667,0.933333,1,0.966667,0.966667,0.966667,1,0.965517,0.9,0.933333,1,1,0.966667,1,0.833333,0.933333,0.866667,1,0.966667,0.966667,0.966667] recall 0.9486521181001284 [1,0.9,1,0.933333,0.933333,0.965517,0.9,1,0.966667,0.933333,0.933333,0.966667,0.866667,1,1,0.966667,0.966667,0.966667,0.966667,0.766667,0.933333,0.933333,0.933333,1,0.966667,0.966667] recall 0.9602053915275995 [0.966667,0.9,1,1,0.933333,0.965517,0.9,1,0.966667,1,0.966667,0.933333,0.866667,0.9,0.933333,0.966667,1,1,0.933333,1,1,0.9,1,1,1,0.933333] relative_absolute_error 0.0677447186285582 relative_absolute_error 0.07205412890458461 relative_absolute_error 0.06315942278250977 relative_absolute_error 0.05653606587933587 relative_absolute_error 0.07283330665207592 relative_absolute_error 0.05511032669830792 relative_absolute_error 0.06641643312161336 relative_absolute_error 0.05913240145621809 relative_absolute_error 0.07369917605264882 relative_absolute_error 0.05811094675591019 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230767088031558 root_mean_prior_squared_error 0.19230763806177284 root_mean_prior_squared_error 0.19230763806177284 root_mean_squared_error 0.0528364865531693 root_mean_squared_error 0.057621169477297667 root_mean_squared_error 0.05124426078951404 root_mean_squared_error 0.048586216958312604 root_mean_squared_error 0.057917176608690654 root_mean_squared_error 0.04757237384769428 root_mean_squared_error 0.05341219234787121 root_mean_squared_error 0.05163842692021438 root_mean_squared_error 0.05649327271248823 root_mean_squared_error 0.04931029856817292 root_relative_squared_error 0.27474971921207597 root_relative_squared_error 0.2996300694337019 root_relative_squared_error 0.26647014556846704 root_relative_squared_error 0.25264831819277495 root_relative_squared_error 0.30116930645607953 root_relative_squared_error 0.24737633422602925 root_relative_squared_error 0.27774338922614744 root_relative_squared_error 0.2685198499042299 root_relative_squared_error 0.29376510096984043 root_relative_squared_error 0.25641362488334196 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 usercpu_time_millis 49693.07847300661 usercpu_time_millis 50435.67921700742 usercpu_time_millis 51942.11111799814 usercpu_time_millis 50741.53730100079 usercpu_time_millis 53630.23960300052 usercpu_time_millis 53378.05616998958 usercpu_time_millis 50576.6362669965 usercpu_time_millis 49948.2387839962 usercpu_time_millis 50421.0582079977 usercpu_time_millis 49929.63895700086 usercpu_time_millis_testing 61.42494500090834 usercpu_time_millis_testing 70.01284500438487 usercpu_time_millis_testing 72.71136499912245 usercpu_time_millis_testing 67.64019499678398 usercpu_time_millis_testing 68.09027700364823 usercpu_time_millis_testing 68.25024399586255 usercpu_time_millis_testing 65.86278399481671 usercpu_time_millis_testing 69.79230599972652 usercpu_time_millis_testing 65.20384299801663 usercpu_time_millis_testing 75.45042599667795 usercpu_time_millis_training 49631.6535280057 usercpu_time_millis_training 50365.666372003034 usercpu_time_millis_training 51869.399752999016 usercpu_time_millis_training 50673.897106004006 usercpu_time_millis_training 53562.14932599687 usercpu_time_millis_training 53309.805925993714 usercpu_time_millis_training 50510.773483001685 usercpu_time_millis_training 49878.44647799648 usercpu_time_millis_training 50355.85436499969 usercpu_time_millis_training 49854.18853100418 wall_clock_time_millis 49694.34642791748 wall_clock_time_millis 50438.57288360596 wall_clock_time_millis 51943.40252876282 wall_clock_time_millis 50791.73684120178 wall_clock_time_millis 53643.39733123779 wall_clock_time_millis 53395.851612091064 wall_clock_time_millis 50578.315019607544 wall_clock_time_millis 49949.37586784363 wall_clock_time_millis 50424.67641830444 wall_clock_time_millis 49946.59662246704 wall_clock_time_millis_testing 61.43307685852051 wall_clock_time_millis_testing 70.02115249633789 wall_clock_time_millis_testing 72.72005081176758 wall_clock_time_millis_testing 67.64912605285645 wall_clock_time_millis_testing 68.13287734985352 wall_clock_time_millis_testing 68.25828552246094 wall_clock_time_millis_testing 65.86980819702148 wall_clock_time_millis_testing 69.80133056640625 wall_clock_time_millis_testing 65.21224975585938 wall_clock_time_millis_testing 75.47926902770996 wall_clock_time_millis_training 49632.91335105896 wall_clock_time_millis_training 50368.55173110962 wall_clock_time_millis_training 51870.68247795105 wall_clock_time_millis_training 50724.087715148926 wall_clock_time_millis_training 53575.26445388794 wall_clock_time_millis_training 53327.5933265686 wall_clock_time_millis_training 50512.44521141052 wall_clock_time_millis_training 49879.57453727722 wall_clock_time_millis_training 50359.464168548584 wall_clock_time_millis_training 49871.11735343933