10093792 1 Jan van Rijn 14 Supervised Classification 8815 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(1) 8018906 axis 0 8778 copy true 8778 missing_values "NaN" 8778 strategy "most_frequent" 8778 verbose 0 8778 copy true 8779 with_mean true 8779 with_std true 8779 memory null 8780 copy true 8781 fill_value -1 8781 missing_values NaN 8781 strategy "constant" 8781 verbose 0 8781 categorical_features null 8782 categories null 8782 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 8782 handle_unknown "ignore" 8782 n_values null 8782 sparse true 8782 class_weight null 8783 criterion "gini" 8783 max_depth null 8783 max_features 1.0 8783 max_leaf_nodes null 8783 min_impurity_decrease 0.0 8783 min_impurity_split null 8783 min_samples_leaf 14 8783 min_samples_split 9 8783 min_weight_fraction_leaf 0.0 8783 presort false 8783 random_state 41146 8783 splitter "best" 8783 n_jobs null 8812 remainder "passthrough" 8812 sparse_threshold 0.3 8812 transformer_weights null 8812 memory null 8813 memory null 8815 threshold 0.0 8816 openml-python Sklearn_0.20.0. 14 mfeat-fourier https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff -1 21108121 description https://api.openml.org/data/download/21108121/description.xml -1 21108122 predictions https://api.openml.org/data/download/21108122/predictions.arff area_under_roc_curve 0.933483611111111 [0.994307,0.904899,0.947519,0.944126,0.882567,0.959824,0.867076,0.963472,0.985171,0.885875] average_cost 0 f_measure 0.7332074905848832 [0.975369,0.64877,0.883249,0.785146,0.626632,0.781955,0.483721,0.78744,0.934726,0.425068] kappa 0.7027777777777778 kb_relative_information_score 1462.6000509651467 mean_absolute_error 0.06310436190249584 mean_prior_absolute_error 0.18000000000000554 number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.7379996395250207 [0.961165,0.587045,0.896907,0.836158,0.655738,0.78392,0.452174,0.761682,0.978142,0.467066] predictive_accuracy 0.7325 prior_entropy 3.321928094887362 recall 0.7325 [0.99,0.725,0.87,0.74,0.6,0.78,0.52,0.815,0.895,0.39] relative_absolute_error 0.35057978834718834 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.19704553083686283 root_relative_squared_error 0.656818436122866 total_cost 0 area_under_roc_curve 0.9393888888888889 [0.996528,0.94125,0.912361,0.934306,0.928472,0.996667,0.84,0.953472,0.996389,0.894444] area_under_roc_curve 0.9223472222222222 [0.974444,0.913889,0.882083,0.986389,0.850972,0.931667,0.867778,0.955694,0.946944,0.913611] area_under_roc_curve 0.9033333333333334 [1,0.875,0.96125,0.908056,0.878056,0.937778,0.792917,0.830278,0.997083,0.852917] area_under_roc_curve 0.9448611111111113 [1,0.848333,0.969722,0.983472,0.934028,0.990833,0.885417,0.980139,0.973194,0.883472] area_under_roc_curve 0.9573611111111114 [0.999444,0.902778,0.99625,0.974722,0.953889,0.956806,0.909722,0.985694,0.997917,0.896389] area_under_roc_curve 0.9432361111111112 [1,0.911667,0.9975,0.88875,0.929167,0.982361,0.805556,0.988333,0.997639,0.931389] area_under_roc_curve 0.9167222222222222 [0.999861,0.959444,0.8625,0.899583,0.789861,0.924167,0.917917,0.98,0.996667,0.837222] area_under_roc_curve 0.9297777777777779 [0.975,0.921528,0.938889,0.935278,0.823056,0.988056,0.879583,0.990278,0.954861,0.89125] area_under_roc_curve 0.9483055555555555 [1,0.871528,0.998056,0.980278,0.871111,0.934861,0.923333,0.982222,1,0.921667] area_under_roc_curve 0.9316666666666668 [0.999444,0.89875,0.961944,0.958194,0.879722,0.959861,0.8425,0.992083,0.979306,0.844861] 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 0.7574599177165307 [0.97561,0.68,0.829268,0.823529,0.666667,0.871795,0.55814,0.722222,0.947368,0.5] f_measure 0.7226329599873967 [0.926829,0.744186,0.8,0.8,0.628571,0.790698,0.530612,0.8,0.947368,0.258065] f_measure 0.6865309936238917 [1,0.571429,0.918919,0.722222,0.608696,0.820513,0.391304,0.5625,0.97561,0.294118] f_measure 0.7340023327802829 [1,0.585366,0.883721,0.780488,0.651163,0.777778,0.55,0.731707,0.947368,0.432432] f_measure 0.7049616200780697 [0.97561,0.55,0.894737,0.789474,0.628571,0.714286,0.428571,0.77551,0.95,0.342857] f_measure 0.7545163614451909 [0.97561,0.717949,0.952381,0.722222,0.65,0.837209,0.454545,0.863636,0.947368,0.424242] f_measure 0.7299919110500441 [0.97561,0.653061,0.833333,0.789474,0.606061,0.666667,0.540541,0.8,0.947368,0.487805] f_measure 0.7440428688059102 [0.974359,0.565217,0.894737,0.809524,0.588235,0.756757,0.5,0.909091,0.857143,0.585366] f_measure 0.7614289444724227 [1,0.756757,0.952381,0.810811,0.628571,0.761905,0.388889,0.826087,1,0.488889] f_measure 0.7194183150057576 [0.952381,0.679245,0.864865,0.8,0.6,0.833333,0.489796,0.810811,0.810811,0.352941] kappa 0.7277777777777777 kappa 0.7 kappa 0.65 kappa 0.7055555555555556 kappa 0.6777777777777777 kappa 0.7333333333333334 kappa 0.7 kappa 0.7111111111111111 kappa 0.7388888888888889 kappa 0.6833333333333333 kb_relative_information_score 149.0507915420916 kb_relative_information_score 143.37606066951378 kb_relative_information_score 141.17485245456265 kb_relative_information_score 147.81442495013852 kb_relative_information_score 147.73505592791722 kb_relative_information_score 149.1174994230174 kb_relative_information_score 144.18380760984485 kb_relative_information_score 146.46055996722683 kb_relative_information_score 153.32190524460472 kb_relative_information_score 140.36509317624143 mean_absolute_error 0.05940985809757409 mean_absolute_error 0.06676974603802639 mean_absolute_error 0.06648189454769811 mean_absolute_error 0.061896158934219195 mean_absolute_error 0.06222001479518369 mean_absolute_error 0.060613783831980426 mean_absolute_error 0.06465704992625064 mean_absolute_error 0.062300848261931795 mean_absolute_error 0.05700293909307061 mean_absolute_error 0.06969132549901993 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] precision 0.775641103747511 [0.952381,0.566667,0.809524,1,0.636364,0.894737,0.521739,0.8125,1,0.5625] precision 0.728479007249622 [0.904762,0.695652,0.8,0.8,0.733333,0.73913,0.448276,0.8,1,0.363636] precision 0.7081503077986744 [1,0.482759,1,0.8125,0.538462,0.842105,0.346154,0.75,0.952381,0.357143] precision 0.7377989891608818 [1,0.571429,0.826087,0.761905,0.608696,0.875,0.55,0.714286,1,0.470588] precision 0.7109573568194258 [0.952381,0.55,0.944444,0.833333,0.733333,0.681818,0.409091,0.655172,0.95,0.4] precision 0.7590217534182065 [0.952381,0.736842,0.909091,0.8125,0.65,0.782609,0.416667,0.791667,1,0.538462] precision 0.7464958599547848 [0.952381,0.551724,0.9375,0.833333,0.769231,0.636364,0.588235,0.72,1,0.47619] precision 0.7618082081317376 [1,0.5,0.944444,0.772727,0.714286,0.823529,0.458333,0.833333,1,0.571429] precision 0.7683848553407379 [1,0.823529,0.909091,0.882353,0.733333,0.727273,0.4375,0.730769,1,0.44] precision 0.747362567283967 [0.909091,0.545455,0.941176,0.933333,0.6,0.9375,0.413793,0.882353,0.882353,0.428571] predictive_accuracy 0.755 predictive_accuracy 0.73 predictive_accuracy 0.685 predictive_accuracy 0.735 predictive_accuracy 0.71 predictive_accuracy 0.76 predictive_accuracy 0.73 predictive_accuracy 0.74 predictive_accuracy 0.765 predictive_accuracy 0.715 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 prior_entropy 3.321928094887362 recall 0.755 [1,0.85,0.85,0.7,0.7,0.85,0.6,0.65,0.9,0.45] recall 0.73 [0.95,0.8,0.8,0.8,0.55,0.85,0.65,0.8,0.9,0.2] recall 0.685 [1,0.7,0.85,0.65,0.7,0.8,0.45,0.45,1,0.25] recall 0.735 [1,0.6,0.95,0.8,0.7,0.7,0.55,0.75,0.9,0.4] recall 0.71 [1,0.55,0.85,0.75,0.55,0.75,0.45,0.95,0.95,0.3] recall 0.76 [1,0.7,1,0.65,0.65,0.9,0.5,0.95,0.9,0.35] recall 0.73 [1,0.8,0.75,0.75,0.5,0.7,0.5,0.9,0.9,0.5] recall 0.74 [0.95,0.65,0.85,0.85,0.5,0.7,0.55,1,0.75,0.6] recall 0.765 [1,0.7,1,0.75,0.55,0.8,0.35,0.95,1,0.55] recall 0.715 [1,0.9,0.8,0.7,0.6,0.75,0.6,0.75,0.75,0.3] relative_absolute_error 0.3300547672087453 relative_absolute_error 0.3709430335445915 relative_absolute_error 0.36934385859832325 relative_absolute_error 0.34386754963455146 relative_absolute_error 0.345666748862132 relative_absolute_error 0.33674324351100277 relative_absolute_error 0.3592058329236151 relative_absolute_error 0.3461158236773992 relative_absolute_error 0.31668299496150376 relative_absolute_error 0.3871740305501112 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_squared_error 0.19147449577707298 root_mean_squared_error 0.20668060556651532 root_mean_squared_error 0.21223105298480893 root_mean_squared_error 0.19310190759592188 root_mean_squared_error 0.19350360186772195 root_mean_squared_error 0.1882701803341725 root_mean_squared_error 0.202536249872959 root_mean_squared_error 0.19569811049797042 root_mean_squared_error 0.1792400610963254 root_mean_squared_error 0.20548650370139718 root_relative_squared_error 0.6382483192569104 root_relative_squared_error 0.6889353518883848 root_relative_squared_error 0.7074368432826968 root_relative_squared_error 0.64367302531974 root_relative_squared_error 0.6450120062257403 root_relative_squared_error 0.6275672677805754 root_relative_squared_error 0.6751208329098637 root_relative_squared_error 0.6523270349932352 root_relative_squared_error 0.597466870321085 root_relative_squared_error 0.684955012337991 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 2227.8369740006383 usercpu_time_millis 2049.436379999861 usercpu_time_millis 2000.1053639998645 usercpu_time_millis 2027.4175069998819 usercpu_time_millis 1967.8871070009336 usercpu_time_millis 1939.6451510001498 usercpu_time_millis 1995.3504160002922 usercpu_time_millis 2043.36200599937 usercpu_time_millis 2010.3130079996845 usercpu_time_millis 2011.869884000589 usercpu_time_millis_testing 1.503563999904145 usercpu_time_millis_testing 1.4608399997086963 usercpu_time_millis_testing 1.4598249999835389 usercpu_time_millis_testing 1.4257610000640852 usercpu_time_millis_testing 1.3653310006702668 usercpu_time_millis_testing 1.329740000073798 usercpu_time_millis_testing 1.4024499996594386 usercpu_time_millis_testing 1.5407749997393694 usercpu_time_millis_testing 1.6425839994553826 usercpu_time_millis_testing 1.4740500000698376 usercpu_time_millis_training 2226.333410000734 usercpu_time_millis_training 2047.9755400001523 usercpu_time_millis_training 1998.645538999881 usercpu_time_millis_training 2025.9917459998178 usercpu_time_millis_training 1966.5217760002633 usercpu_time_millis_training 1938.315411000076 usercpu_time_millis_training 1993.9479660006327 usercpu_time_millis_training 2041.8212309996306 usercpu_time_millis_training 2008.670424000229 usercpu_time_millis_training 2010.3958340005192