5963443 1 Jan van Rijn 9954 Supervised Classification 6970 sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier))(1) 3998177 class_weight null 6941 criterion "gini" 6941 max_depth 4 6941 max_features null 6941 max_leaf_nodes null 6941 min_impurity_split 1e-07 6941 min_samples_leaf 1 6941 min_samples_split 2 6941 min_weight_fraction_leaf 0.0 6941 presort false 6941 random_state 11699 6941 splitter "best" 6941 axis 0 6947 categorical_features [] 6947 copy true 6947 fill_empty 0 6947 missing_values "NaN" 6947 strategy "mean" 6947 strategy_nominal "most_frequent" 6947 verbose 0 6947 categorical_features [] 6948 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 6948 handle_unknown "ignore" 6948 n_values "auto" 6948 sparse false 6948 threshold 0.0 6949 algorithm "SAMME" 6971 learning_rate 0.029511633562044875 6971 n_estimators 437 6971 random_state 30347 6971 openml-pimp openml-python Sklearn_0.18.1. study_71 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 12850290 description https://api.openml.org/data/download/12850290/description.xml -1 12850289 predictions https://api.openml.org/data/download/12850289/predictions.arff area_under_roc_curve 0.984507575757576 [0.954467,0.994437,0.998264,0.999921,0.998737,0.991319,0.994003,0.993766,0.990609,0.997475,0.985795,0.993608,0.987413,0.967724,0.999724,0.956282,0.999171,0.981455,0.972025,0.974353,0.993292,0.994831,0.975063,0.999921,0.986979,0.959399,0.954467,0.987768,0.995344,0.999211,0.993371,0.998935,0.992819,0.981731,0.993884,0.996409,0.983941,0.976405,0.993647,0.998461,0.980074,0.989307,0.999211,0.985953,0.991872,0.994358,0.996252,0.992622,0.974116,0.99199,0.980035,0.990333,0.98765,0.95715,0.979167,0.970289,1,0.996843,0.992345,0.961332,0.997948,0.997711,0.986348,0.983546,0.99637,0.987255,0.961608,0.991556,0.966225,0.96587,0.960859,0.99708,0.983152,0.995739,0.93462,0.967172,0.998382,0.942116,0.999329,0.996567,0.958649,0.98986,0.977312,0.989741,0.974195,0.970407,1,0.985046,0.993292,0.99633,0.998658,0.998185,0.980271,0.972538,0.982086,0.987571,0.984296,0.981771,0.931029,0.99274] average_cost 0 f_measure 0.6330048230982227 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[16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16] precision 0.6469897187697362 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[0.375,0.75,0.9375,1,0.875,0.8125,0.875,0.8125,0.5625,0.9375,0.375,0.875,0.875,0.375,0.9375,0.375,0.9375,0.4375,0.5625,0.1875,0.875,0.8125,0.3125,1,0.875,0.3125,0.1875,0.6875,0.875,0.9375,0.75,0.875,0.8125,0.4375,0.75,0.8125,0.3125,0.1875,0.75,0.8125,0.75,0.75,0.9375,0.75,0.6875,0.625,0.75,0.625,0.5,0.6875,0.5,0.75,0.5,0.3125,0.6875,0.375,1,0.875,0.625,0.25,0.9375,0.8125,0.25,0.5625,0.875,0.4375,0.375,0.4375,0.4375,0.25,0.5625,0.875,0.25,0.875,0.5,0.625,0.875,0.4375,1,0.875,0.125,0.625,0.625,0.625,0.3125,0.6875,1,0.625,0.6875,0.9375,0.8125,0.875,0.75,0.375,0.5,0.6875,0.3125,0.375,0.25,0.6875] relative_absolute_error 0.9999925920950503 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.09949800664372713 root_relative_squared_error 0.9999925921985799 total_cost 0 area_under_roc_curve 0.9838719548602821 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[0.679245,0.990506,0.981132,1,1,1,1,0.968553,0.993671,1,0.987421,1,0.996835,0.990506,0.996835,0.943396,1,0.981132,0.987342,0.987421,0.996835,0.993671,1,1,1,0.943396,1,1,0.993671,1,1,0.990506,1,0.981132,0.990506,0.993671,0.968354,0.993671,0.984177,1,0.987421,0.981013,1,0.984177,0.996835,1,1,0.987342,0.993711,0.987421,0.996835,1,0.993671,0.958861,0.993671,0.943396,1,1,0.996835,0.971519,1,0.996835,0.968354,0.974684,1,0.993711,0.996835,0.993711,0.996835,0.993711,0.811321,1,0.981013,0.996835,0.936709,0.981013,1,1,0.987421,0.990506,0.996835,0.993711,0.893082,0.968553,0.993671,0.996835,1,1,1,0.993671,1,0.996835,0.987342,0.990506,0.993711,0.990506,0.968553,0.996835,0.990506,0.987421] 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 kappa 0.595720320581152 kappa 0.6462971735354492 kappa 0.6463111356728378 kappa 0.608354060562991 kappa 0.621002763521516 kappa 0.6462832102956851 kappa 0.6335202590632651 kappa 0.6778141903897027 kappa 0.6588620839420382 kappa 0.6588351431391904 kb_relative_information_score 0.02505954939859066 kb_relative_information_score 0.025020666741320516 kb_relative_information_score 0.025971689902703293 kb_relative_information_score 0.025402017128545763 kb_relative_information_score 0.026093916993601276 kb_relative_information_score 0.02523281870379694 kb_relative_information_score 0.026345559745135364 kb_relative_information_score 0.02611472949888684 kb_relative_information_score 0.02516796154313837 kb_relative_information_score 0.024274303344327643 mean_absolute_error 0.01979985567857383 mean_absolute_error 0.019799855902649478 mean_absolute_error 0.01979985042370681 mean_absolute_error 0.019799853706276856 mean_absolute_error 0.019799849718158413 mean_absolute_error 0.01979985468050613 mean_absolute_error 0.019799848267631127 mean_absolute_error 0.019799849598988783 mean_absolute_error 0.019799855054536557 mean_absolute_error 0.019799860203792756 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 number_of_instances 160 [1,2,2,1,2,1,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,1,1,1,2,2,2,2,1,2,2,2,2,2,1,1,1,1,2,1,1,2,2,2,2,1,1,2,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,1,2,2,1,1,1,2,1,2,2,1,2,2,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,1,2,2,1] number_of_instances 160 [1,2,2,1,2,1,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,1,1,1,2,2,2,2,1,2,2,2,2,2,1,1,1,1,2,1,1,2,2,2,2,1,1,2,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,1,2,2,1,1,1,2,1,2,2,1,2,2,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,1,2,2,1] number_of_instances 160 [2,2,2,1,2,2,1,2,2,2,2,2,1,2,2,2,2,2,1,2,1,1,2,1,1,2,2,1,2,2,1,2,2,2,1,1,1,1,1,2,2,1,1,1,2,1,2,1,2,2,2,1,1,2,1,2,1,2,1,2,1,1,2,1,2,2,2,2,1,2,2,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,1,1,2,2,1,2,2,1,2] number_of_instances 160 [2,2,2,1,2,2,1,2,2,2,2,2,1,2,2,2,2,2,1,2,1,1,2,1,1,2,2,1,2,2,1,2,2,2,1,1,1,1,1,2,2,1,1,1,2,1,2,1,2,2,2,1,1,2,1,2,1,2,1,2,1,1,2,1,2,2,2,2,1,2,2,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,1,1,2,2,1,2,2,1,2] number_of_instances 160 [2,1,2,2,1,2,1,2,1,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,2,1,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,1,1,1,2,2,2,2,1,1,2,1,2,2,1,2,2,1,2,2,1,1,2,2,1,2,2,2,2,2,1,1,2,1,2,2,2,1,1,2,2,2,1,1,1,1,2,2,1,2,1,1,2,1,2,1,1,2] number_of_instances 160 [2,1,2,2,1,2,1,2,1,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,2,1,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,1,1,1,2,2,2,2,1,1,2,1,2,2,1,2,2,1,2,2,1,1,2,2,1,2,2,2,2,2,1,1,2,1,2,2,2,1,1,2,2,2,1,1,1,1,2,2,1,2,1,1,2,1,2,1,1,2] number_of_instances 160 [2,1,1,2,1,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,2,1,1,2,1,2,2,1,1,1,2,2,2,2,2,1,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,2,1,1,1,1,1,2,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,1,2,2] number_of_instances 160 [2,1,1,2,1,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,2,1,1,2,1,2,2,1,1,1,2,2,2,2,2,1,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,2,1,1,1,1,1,2,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,1,2,2] number_of_instances 160 [1,2,1,2,2,1,2,1,2,1,1,1,2,2,2,1,1,1,2,1,2,2,1,2,2,1,1,2,2,1,2,2,1,1,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,2,2,1,1,2,1,2,1,1,1,2,2,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,2,2,2,2,1,2,1,2,2,1] number_of_instances 160 [1,2,1,2,2,1,2,1,2,1,1,1,2,2,2,1,1,1,2,1,2,2,1,2,2,1,1,2,2,1,2,2,1,1,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,2,2,1,1,2,1,2,1,1,1,2,2,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,2,2,2,2,1,2,1,2,2,1] predictive_accuracy 0.6 predictive_accuracy 0.65 predictive_accuracy 0.65 predictive_accuracy 0.6125 predictive_accuracy 0.625 predictive_accuracy 0.65 predictive_accuracy 0.6375 predictive_accuracy 0.68125 predictive_accuracy 0.6625 predictive_accuracy 0.6625 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 recall 0.6 [0,1,1,1,1,1,1,1,0,1,0,0.5,1,0,1,0,1,0,0.5,1,1,0,0,1,1,0.5,0,0.5,0.5,0,0.5,1,0.5,0,0.5,0,0,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,0,1,0,1,1,0,0,1,1,0,0.5,1,1,0.5,1,0,0,0,1,0,1,0,0.5,1,0.5,1,1,0,1,0,1,0,0.5,1,1,0.5,1,1,1,1,0.5,0.5,0.5,0,0,0,1] recall 0.65 [0,0,1,1,1,1,0.5,1,1,1,0.5,1,0.5,0.5,1,1,0.5,0,0,0,1,1,0,1,1,0.5,0,1,1,1,1,1,1,1,0.5,1,0,0,0,0.5,1,1,1,0.5,1,1,0,1,0,1,1,0,1,0.5,0,0,1,1,1,0.5,1,1,0,0.5,1,0.5,0,0,0,0,1,1,1,1,1,0.5,0.5,0.5,1,1,0,0.5,1,1,0.5,1,1,0.5,1,1,0.5,1,1,0.5,0.5,1,1,0,0,1] recall 0.65 [0,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,0,1,0.5,1,0,0,0,0,1,0,0.5,1,1,1,1,0,1,1,0,1,1,1,0,1,1,1,0,1,1,0,0,0.5,1,0.5,1,1,1,0,0.5,1,0,1,1,1,0,1,1,0,1,1,0.5,0.5,0.5,1,0.5,0.5,1,0,0.5,1,1,1,0.5,1,1,0,0.5,0.5,0.5,0,1,1,0.5,1,1,1,1,1,0.5,1,0,0,0,0,1] recall 0.6125 [0,1,1,1,0.5,0,1,0.5,0.5,1,0.5,0.5,0,0.5,1,0.5,1,1,0,0,1,1,0.5,1,0,0,0,0,1,1,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,1,1,1,1,0,0,1,0,1,1,0.5,1,0.5,1,0,0.5,0.5,0.5,0,1,0,0.5,1,0.5,1,1,0,0.5,1,0.5,0,1,1,0.5,1,1,1,1,0,0,0.5,0,0,0.5,0,0] recall 0.625 [0.5,1,1,1,1,1,1,0.5,1,1,0.5,1,1,0,1,0.5,1,0.5,1,0.5,0.5,1,0.5,1,1,0.5,0,1,1,1,0,1,1,0,1,1,0.5,0,0.5,1,1,0.5,1,1,1,0,1,0.5,0.5,0.5,0,0,0.5,1,0.5,0.5,1,0.5,0.5,0,0.5,1,0,0,0.5,0,0,0,0.5,0,1,1,0,0,0.5,1,1,0,1,1,1,1,1,0.5,0,0,1,0,1,1,1,0.5,1,0,0.5,1,0.5,0,0,0.5] recall 0.65 [0.5,0,1,1,1,1,1,1,1,0.5,0,1,1,1,1,0.5,1,0,1,0.5,1,0.5,0.5,1,1,0.5,0,1,1,1,1,1,0.5,0.5,1,0.5,0.5,0.5,0.5,1,0.5,0.5,0,1,1,1,1,0,0,0.5,1,1,0.5,0,0.5,0.5,1,1,0.5,1,1,0.5,0,1,1,0.5,0,1,0.5,0.5,0.5,1,1,1,0.5,1,0.5,0.5,1,1,0,0.5,1,0.5,0,1,1,0,0,0.5,1,1,0,1,0.5,1,0.5,0,0,1] recall 0.6375 [1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,0.5,1,1,0.5,0,1,1,0.5,1,1,0,0,0.5,1,1,0.5,0,1,0,1,1,0,0.5,1,0,0.5,0.5,1,1,0,0.5,0,0.5,1,1,0,1,1,0,0.5,0.5,1,0.5,0.5,0,1,1,0,0.5,1,0,0,0,0.5,0,1,1,0.5,1,0.5,1,1,0,1,1,0,1,0.5,1,0.5,0.5,1,0,0,1,1,1,0,0,0,0.5,0.5,1,0,1] recall 0.68125 [1,1,1,1,1,0.5,1,1,0,1,0,1,1,0,1,0.5,1,1,0.5,0,1,1,0,1,1,0,0,0.5,0,1,1,1,1,1,1,1,0.5,0,1,1,1,1,1,0,0,0.5,1,1,1,1,0,1,0,1,1,0.5,1,1,1,1,1,1,1,0,1,0,1,0.5,0,0.5,0,1,0,1,1,0,1,1,1,1,0,0,0,0.5,0,0.5,1,1,1,1,0,1,1,0,1,1,0,0,0.5,1] recall 0.6625 [0,1,1,1,1,1,1,1,0,1,0,1,1,0.5,1,0,1,1,1,0,1,1,0,1,1,0,0,1,1,1,1,1,0,1,0.5,1,0,0,1,0,0,1,1,0.5,1,1,1,0.5,0,1,0.5,0.5,0,0.5,0.5,0,1,1,0.5,0,1,1,0.5,1,1,0,0.5,0,1,0,1,0,0,1,0.5,0,1,0,1,0.5,0,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0,0.5,0,1,0.5,0] recall 0.6625 [0,1,0,1,1,1,0.5,0,1,1,1,1,1,0.5,0.5,0,1,0,0.5,0,1,1,1,1,1,0,1,0.5,1,1,1,0.5,1,1,1,0.5,0,0,0.5,1,0,1,1,1,0.5,0.5,1,0.5,0,1,0.5,1,1,0,1,0,1,1,1,0.5,1,0.5,0,0.5,1,0,0.5,0,0.5,0,0,1,0,1,0,1,1,1,1,0.5,0.5,0,0,0,0.5,0.5,1,1,1,1,0.5,1,1,0.5,0,1,1,1,1,0] relative_absolute_error 0.9999927110390807 relative_absolute_error 0.9999927223560325 relative_absolute_error 0.9999924456417564 relative_absolute_error 0.9999926114281223 relative_absolute_error 0.999992410007999 relative_absolute_error 0.9999926606316211 relative_absolute_error 0.9999923367490452 relative_absolute_error 0.9999924039893309 relative_absolute_error 0.9999926795220466 relative_absolute_error 0.9999929395854911 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_squared_error 0.099498018478403 root_mean_squared_error 0.09949801960438079 root_mean_squared_error 0.0994979920717561 root_mean_squared_error 0.09949800856739444 root_mean_squared_error 0.09949798852695926 root_mean_squared_error 0.09949801346302477 root_mean_squared_error 0.09949798123704534 root_mean_squared_error 0.09949798792745336 root_mean_squared_error 0.09949801534256722 root_mean_squared_error 0.09949804121827117 root_relative_squared_error 0.9999927111415481 root_relative_squared_error 0.9999927224580506 root_relative_squared_error 0.9999924457447608 root_relative_squared_error 0.9999926115321641 root_relative_squared_error 0.9999924101182122 root_relative_squared_error 0.9999926607351003 root_relative_squared_error 0.9999923368518207 root_relative_squared_error 0.9999924040929511 root_relative_squared_error 0.9999926796252125 root_relative_squared_error 0.9999929396858224 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 6588.338081999999 usercpu_time_millis 6508.274877 usercpu_time_millis 6499.5767319999995 usercpu_time_millis 6540.688597999999 usercpu_time_millis 6522.636812000002 usercpu_time_millis 6564.0784150000045 usercpu_time_millis 6520.362044999999 usercpu_time_millis 6507.040665999994 usercpu_time_millis 6357.688644 usercpu_time_millis 6471.551223999995 usercpu_time_millis_testing 119.26122399999883 usercpu_time_millis_testing 120.28717499999964 usercpu_time_millis_testing 118.89368399999967 usercpu_time_millis_testing 115.14319200000145 usercpu_time_millis_testing 123.53164299999975 usercpu_time_millis_testing 115.88005300000503 usercpu_time_millis_testing 115.17252699999858 usercpu_time_millis_testing 118.27155399999612 usercpu_time_millis_testing 118.53223600000007 usercpu_time_millis_testing 126.80702100000474 usercpu_time_millis_training 6469.076858 usercpu_time_millis_training 6387.987702 usercpu_time_millis_training 6380.683048 usercpu_time_millis_training 6425.5454059999975 usercpu_time_millis_training 6399.105169000002 usercpu_time_millis_training 6448.198361999999 usercpu_time_millis_training 6405.189518 usercpu_time_millis_training 6388.769111999998 usercpu_time_millis_training 6239.156408 usercpu_time_millis_training 6344.74420299999