10145367 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) 8070971 axis 0 8778 copy true 8778 missing_values "NaN" 8778 strategy "median" 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 "entropy" 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 13 8783 min_samples_split 9 8783 min_weight_fraction_leaf 0.0 8783 presort false 8783 random_state 14941 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 21211273 description https://api.openml.org/data/download/21211273/description.xml -1 21211274 predictions https://api.openml.org/data/download/21211274/predictions.arff area_under_roc_curve 0.9379922222222222 [0.991453,0.91016,0.967528,0.937582,0.911014,0.951433,0.888083,0.973071,0.979804,0.869794] average_cost 0 f_measure 0.7513846684110439 [0.955665,0.668224,0.895288,0.768116,0.688442,0.831169,0.49,0.835749,0.937343,0.44385] kappa 0.725 kb_relative_information_score 1522.5487550169566 mean_absolute_error 0.05782338980052011 mean_prior_absolute_error 0.18000000000000554 number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.7523396907490234 [0.941748,0.627193,0.93956,0.742991,0.691919,0.864865,0.49,0.808411,0.939698,0.477011] predictive_accuracy 0.7525 prior_entropy 3.321928094887362 recall 0.7525 [0.97,0.715,0.855,0.795,0.685,0.8,0.49,0.865,0.935,0.415] relative_absolute_error 0.3212410544473241 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.1903390059538018 root_relative_squared_error 0.6344633531793296 total_cost 0 area_under_roc_curve 0.9405138888888891 [0.999861,0.9625,0.964444,0.90625,0.933333,0.994722,0.875972,0.967639,0.9975,0.802917] area_under_roc_curve 0.9104722222222223 [0.974306,0.912222,0.918056,0.930833,0.823472,0.8975,0.842639,0.988056,0.948333,0.869306] area_under_roc_curve 0.9328888888888889 [0.973889,0.897639,0.945139,0.869167,0.972361,0.992083,0.901667,0.945972,0.997083,0.833889] area_under_roc_curve 0.9247500000000001 [0.996667,0.853056,0.971806,0.987361,0.914028,0.879444,0.832778,0.964861,0.974583,0.872917] area_under_roc_curve 0.9376666666666666 [1,0.902917,0.966111,0.936111,0.948472,0.969444,0.895278,0.928889,0.996806,0.832639] area_under_roc_curve 0.9400972222222223 [1,0.944167,0.998472,0.908333,0.885694,0.936389,0.891111,0.980556,0.99875,0.8575] area_under_roc_curve 0.9541944444444443 [0.999722,0.895694,0.9475,0.960833,0.958472,0.977083,0.944444,0.98625,0.974722,0.897222] area_under_roc_curve 0.9395555555555555 [0.973611,0.910833,0.999444,0.941667,0.839028,0.994028,0.921528,0.988194,0.945417,0.881806] area_under_roc_curve 0.9666111111111111 [0.999722,0.892083,0.998333,0.990833,0.95625,0.942778,0.956806,0.990556,1,0.93875] area_under_roc_curve 0.9374583333333333 [0.996389,0.940417,0.968333,0.940833,0.889583,0.938472,0.819861,0.995833,0.969306,0.915556] 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 0.740484085230834 [0.97561,0.652174,0.842105,0.820513,0.790698,0.923077,0.439024,0.789474,0.878049,0.294118] f_measure 0.7018356021106977 [0.974359,0.697674,0.833333,0.780488,0.585366,0.648649,0.193548,0.829268,0.947368,0.528302] f_measure 0.7328552095521478 [0.95,0.638298,0.918919,0.666667,0.755556,0.878049,0.409091,0.833333,0.97561,0.30303] f_measure 0.7555664425240027 [0.904762,0.604651,0.923077,0.826087,0.634146,0.777778,0.571429,0.810811,0.947368,0.555556] f_measure 0.7137760664458831 [0.97561,0.595745,0.888889,0.736842,0.619048,0.864865,0.363636,0.727273,0.97561,0.390244] f_measure 0.7702847437504792 [0.97561,0.782609,0.947368,0.790698,0.628571,0.857143,0.484848,0.790698,0.904762,0.540541] f_measure 0.7810601303458446 [0.974359,0.666667,0.923077,0.761905,0.75,0.761905,0.734694,0.863636,0.974359,0.4] f_measure 0.7537603366673133 [0.95,0.651163,0.9,0.651163,0.628571,0.9,0.564103,0.863636,0.864865,0.564103] f_measure 0.8025867780160449 [0.95,0.702703,0.894737,0.826087,0.8,0.823529,0.585366,0.888889,0.97561,0.578947] f_measure 0.7326373187544306 [0.930233,0.7,0.878049,0.8,0.666667,0.864865,0.425532,0.952381,0.926829,0.181818] kappa 0.7166666666666667 kappa 0.6722222222222222 kappa 0.7055555555555556 kappa 0.7277777777777777 kappa 0.6833333333333333 kappa 0.7555555555555555 kappa 0.7666666666666667 kappa 0.7277777777777777 kappa 0.7833333333333334 kappa 0.7111111111111111 kb_relative_information_score 153.28108790125316 kb_relative_information_score 143.51378936123803 kb_relative_information_score 149.90681874429274 kb_relative_information_score 149.90967294070984 kb_relative_information_score 149.54949926759903 kb_relative_information_score 153.7072489424372 kb_relative_information_score 158.48158488355548 kb_relative_information_score 152.1525594901174 kb_relative_information_score 163.27908652950208 kb_relative_information_score 148.76740695626665 mean_absolute_error 0.055481099626282664 mean_absolute_error 0.06627355337077025 mean_absolute_error 0.059871176065450483 mean_absolute_error 0.05864199649679521 mean_absolute_error 0.060358628515447356 mean_absolute_error 0.05673687627873684 mean_absolute_error 0.0514286434021849 mean_absolute_error 0.05899971341269964 mean_absolute_error 0.048737183725885064 mean_absolute_error 0.06170502711094412 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 0.7422987513376529 [0.952381,0.576923,0.888889,0.842105,0.73913,0.947368,0.428571,0.833333,0.857143,0.357143] precision 0.7135383105811496 [1,0.652174,0.9375,0.761905,0.571429,0.705882,0.272727,0.809524,1,0.424242] precision 0.7442194749694748 [0.95,0.555556,1,0.75,0.68,0.857143,0.375,0.9375,0.952381,0.384615] precision 0.7653846512441208 [0.863636,0.565217,0.947368,0.730769,0.619048,0.875,0.545455,0.882353,1,0.625] precision 0.7242301271713036 [0.952381,0.518519,1,0.777778,0.590909,0.941176,0.461538,0.666667,0.952381,0.380952] precision 0.7741720938907639 [0.952381,0.692308,1,0.73913,0.733333,0.818182,0.615385,0.73913,0.863636,0.588235] precision 0.7914270197437167 [1,0.75,0.947368,0.727273,0.75,0.727273,0.62069,0.791667,1,0.6] precision 0.7591462511778166 [0.95,0.608696,0.9,0.608696,0.733333,0.9,0.578947,0.791667,0.941176,0.578947] precision 0.8124840192487252 [0.95,0.764706,0.944444,0.730769,0.8,1,0.571429,0.8,0.952381,0.611111] precision 0.7332876960114812 [0.869565,0.7,0.857143,0.8,0.75,0.941176,0.37037,0.909091,0.904762,0.230769] predictive_accuracy 0.745 predictive_accuracy 0.705 predictive_accuracy 0.735 predictive_accuracy 0.755 predictive_accuracy 0.715 predictive_accuracy 0.78 predictive_accuracy 0.79 predictive_accuracy 0.755 predictive_accuracy 0.805 predictive_accuracy 0.74 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 0.745 [1,0.75,0.8,0.8,0.85,0.9,0.45,0.75,0.9,0.25] recall 0.705 [0.95,0.75,0.75,0.8,0.6,0.6,0.15,0.85,0.9,0.7] recall 0.735 [0.95,0.75,0.85,0.6,0.85,0.9,0.45,0.75,1,0.25] recall 0.755 [0.95,0.65,0.9,0.95,0.65,0.7,0.6,0.75,0.9,0.5] recall 0.715 [1,0.7,0.8,0.7,0.65,0.8,0.3,0.8,1,0.4] recall 0.78 [1,0.9,0.9,0.85,0.55,0.9,0.4,0.85,0.95,0.5] recall 0.79 [0.95,0.6,0.9,0.8,0.75,0.8,0.9,0.95,0.95,0.3] recall 0.755 [0.95,0.7,0.9,0.7,0.55,0.9,0.55,0.95,0.8,0.55] recall 0.805 [0.95,0.65,0.85,0.95,0.8,0.7,0.6,1,1,0.55] recall 0.74 [1,0.7,0.9,0.8,0.6,0.8,0.5,1,0.95,0.15] relative_absolute_error 0.30822833125712623 relative_absolute_error 0.3681864076153907 relative_absolute_error 0.3326176448080586 relative_absolute_error 0.3257888694266404 relative_absolute_error 0.3353257139747079 relative_absolute_error 0.315204868215205 relative_absolute_error 0.2857146855676942 relative_absolute_error 0.32777618562610944 relative_absolute_error 0.2707621318104729 relative_absolute_error 0.34280570617191214 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 0.19060417870413382 root_mean_squared_error 0.21155737770868407 root_mean_squared_error 0.19305326339162593 root_mean_squared_error 0.19591799068317392 root_mean_squared_error 0.19666830891515447 root_mean_squared_error 0.1847087882042209 root_mean_squared_error 0.1774034655838852 root_mean_squared_error 0.18910141647346465 root_mean_squared_error 0.16357082351324367 root_mean_squared_error 0.19689327947700608 root_relative_squared_error 0.635347262347113 root_relative_squared_error 0.7051912590289473 root_relative_squared_error 0.643510877972087 root_relative_squared_error 0.6530599689439134 root_relative_squared_error 0.6555610297171819 root_relative_squared_error 0.6156959606807367 root_relative_squared_error 0.5913448852796177 root_relative_squared_error 0.6303380549115492 root_relative_squared_error 0.5452360783774793 root_relative_squared_error 0.6563109315900206 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 665.854977996787 usercpu_time_millis 501.08796000131406 usercpu_time_millis 491.19728799996665 usercpu_time_millis 490.044673999364 usercpu_time_millis 487.02474600213463 usercpu_time_millis 456.682184998499 usercpu_time_millis 476.53690399965853 usercpu_time_millis 480.5767329999071 usercpu_time_millis 451.96630300051766 usercpu_time_millis 456.4881080004852 usercpu_time_millis_testing 1.797140997950919 usercpu_time_millis_testing 1.378925000608433 usercpu_time_millis_testing 1.3692680004169233 usercpu_time_millis_testing 1.4911220023350324 usercpu_time_millis_testing 1.3844780005456414 usercpu_time_millis_testing 1.3083679987175856 usercpu_time_millis_testing 1.3151170023775194 usercpu_time_millis_testing 1.3030299996898975 usercpu_time_millis_testing 1.338281999778701 usercpu_time_millis_testing 1.3087500010442454 usercpu_time_millis_training 664.0578369988361 usercpu_time_millis_training 499.7090350007056 usercpu_time_millis_training 489.8280199995497 usercpu_time_millis_training 488.553551997029 usercpu_time_millis_training 485.640268001589 usercpu_time_millis_training 455.3738169997814 usercpu_time_millis_training 475.221786997281 usercpu_time_millis_training 479.2737030002172 usercpu_time_millis_training 450.62802100073895 usercpu_time_millis_training 455.179357999441