10153029 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) 8078694 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 10 8783 min_samples_split 11 8783 min_weight_fraction_leaf 0.0 8783 presort false 8783 random_state 27575 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 21226597 description https://api.openml.org/data/download/21226597/description.xml -1 21226598 predictions https://api.openml.org/data/download/21226598/predictions.arff area_under_roc_curve 0.93180375 [0.991724,0.883893,0.970237,0.937993,0.923051,0.950243,0.853418,0.975799,0.975136,0.856543] average_cost 0 f_measure 0.7644913063833804 [0.962406,0.692494,0.908629,0.809756,0.71066,0.842377,0.509615,0.833333,0.935323,0.440318] kappa 0.7388888888888889 kb_relative_information_score 1535.7827727032009 mean_absolute_error 0.054422021768221716 mean_prior_absolute_error 0.18000000000000554 number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.7650317520372215 [0.964824,0.671362,0.92268,0.790476,0.721649,0.871658,0.490741,0.817308,0.930693,0.468927] predictive_accuracy 0.765 prior_entropy 3.321928094887362 recall 0.765 [0.96,0.715,0.895,0.83,0.7,0.815,0.53,0.85,0.94,0.415] relative_absolute_error 0.30234456537900023 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.1901404114404126 root_relative_squared_error 0.6338013714680324 total_cost 0 area_under_roc_curve 0.9431666666666666 [0.999861,0.942083,0.992222,0.939583,0.955556,0.995278,0.808333,0.990694,0.998333,0.809722] area_under_roc_curve 0.9057638888888888 [0.971528,0.915,0.919722,0.906667,0.823333,0.894167,0.86375,0.989444,0.948333,0.825694] area_under_roc_curve 0.9342638888888888 [0.999583,0.874444,0.945417,0.902639,0.985694,0.993194,0.883333,0.943056,0.999861,0.815417] area_under_roc_curve 0.9207777777777778 [0.973889,0.86625,0.994028,0.983472,0.944167,0.879028,0.792639,0.968472,0.949167,0.856667] area_under_roc_curve 0.9248194444444444 [1,0.841111,0.946528,0.940972,0.928611,0.945833,0.874861,0.928611,0.996806,0.844861] area_under_roc_curve 0.9398611111111111 [1,0.914444,0.998611,0.940417,0.924028,0.936111,0.853056,0.986667,0.998194,0.847083] area_under_roc_curve 0.9482222222222222 [0.999583,0.895556,0.947639,0.912639,0.975556,0.983472,0.946389,0.985417,0.974444,0.861528] area_under_roc_curve 0.9193888888888889 [0.974444,0.818472,0.996944,0.923333,0.845694,0.989583,0.834861,0.985694,0.920278,0.904583] area_under_roc_curve 0.958777777777778 [0.999722,0.891806,0.998056,0.988056,0.953472,0.917222,0.913056,0.988333,0.999722,0.938333] area_under_roc_curve 0.9234444444444446 [1,0.879583,0.962917,0.941111,0.900972,0.969722,0.761389,0.99375,0.969583,0.855417] 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 0.7497275442028704 [0.97561,0.682927,0.9,0.820513,0.731707,0.923077,0.418605,0.820513,0.9,0.324324] f_measure 0.7307764841364864 [0.923077,0.697674,0.864865,0.780488,0.585366,0.684211,0.487805,0.871795,0.947368,0.465116] f_measure 0.7445658101145906 [0.974359,0.666667,0.918919,0.769231,0.791667,0.857143,0.5,0.777778,0.97561,0.214286] f_measure 0.7854730046611346 [0.974359,0.666667,0.95,0.851064,0.711111,0.777778,0.578947,0.833333,0.947368,0.564103] f_measure 0.7494632608788128 [0.97561,0.564103,0.894737,0.8,0.685714,0.9,0.511628,0.782609,0.930233,0.45] f_measure 0.7417876547896708 [1,0.711111,0.95,0.837209,0.647059,0.8,0.30303,0.818182,0.930233,0.421053] f_measure 0.8141471442434215 [0.974359,0.780488,0.923077,0.810811,0.769231,0.829268,0.714286,0.863636,0.95,0.526316] f_measure 0.7690216919661782 [0.95,0.65,0.930233,0.727273,0.709677,0.95,0.512821,0.837209,0.864865,0.55814] f_measure 0.7909709274339645 [0.947368,0.736842,0.871795,0.844444,0.780488,0.764706,0.622222,0.909091,0.97561,0.457143] f_measure 0.7485836007645423 [0.930233,0.761905,0.878049,0.85,0.666667,0.918919,0.409091,0.810811,0.926829,0.333333] kappa 0.7222222222222222 kappa 0.6944444444444444 kappa 0.7277777777777777 kappa 0.7611111111111112 kappa 0.7222222222222222 kappa 0.7277777777777777 kappa 0.7944444444444444 kappa 0.7444444444444445 kappa 0.7722222222222223 kappa 0.7222222222222222 kb_relative_information_score 152.57109105945673 kb_relative_information_score 144.6299202700278 kb_relative_information_score 154.216174038698 kb_relative_information_score 153.14852479753415 kb_relative_information_score 153.32876768599107 kb_relative_information_score 151.7011350022051 kb_relative_information_score 158.91267236996336 kb_relative_information_score 151.8984795903434 kb_relative_information_score 162.2453333403067 kb_relative_information_score 153.130674548696 mean_absolute_error 0.054656270913469036 mean_absolute_error 0.06289681106647045 mean_absolute_error 0.05378762307953483 mean_absolute_error 0.05449610018464508 mean_absolute_error 0.05452817268730579 mean_absolute_error 0.05595733507118952 mean_absolute_error 0.04936977010347751 mean_absolute_error 0.05526459877841455 mean_absolute_error 0.04675218579150463 mean_absolute_error 0.056511350006202915 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 0.750915780499843 [0.952381,0.666667,0.9,0.842105,0.714286,0.947368,0.391304,0.842105,0.9,0.352941] precision 0.740198428723129 [0.947368,0.652174,0.941176,0.761905,0.571429,0.722222,0.47619,0.894737,1,0.434783] precision 0.755354294827979 [1,0.636364,1,0.789474,0.678571,0.818182,0.428571,0.875,0.952381,0.375] precision 0.796966285663654 [1,0.636364,0.95,0.740741,0.64,0.875,0.611111,0.9375,1,0.578947] precision 0.7599239877843997 [0.952381,0.578947,0.944444,0.933333,0.8,0.9,0.478261,0.692308,0.869565,0.45] precision 0.7406948027817593 [1,0.64,0.95,0.782609,0.785714,0.8,0.384615,0.75,0.869565,0.444444] precision 0.8169664021908605 [1,0.761905,0.947368,0.882353,0.789474,0.809524,0.681818,0.791667,0.95,0.555556] precision 0.7858071970206848 [0.95,0.65,0.869565,0.666667,1,0.95,0.526316,0.782609,0.941176,0.521739] precision 0.8002038429406849 [1,0.777778,0.894737,0.76,0.761905,0.928571,0.56,0.833333,0.952381,0.533333] precision 0.7525306174061055 [0.869565,0.727273,0.857143,0.85,0.684211,1,0.375,0.882353,0.904762,0.375] predictive_accuracy 0.75 predictive_accuracy 0.725 predictive_accuracy 0.755 predictive_accuracy 0.785 predictive_accuracy 0.75 predictive_accuracy 0.755 predictive_accuracy 0.815 predictive_accuracy 0.77 predictive_accuracy 0.795 predictive_accuracy 0.75 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 0.75 [1,0.7,0.9,0.8,0.75,0.9,0.45,0.8,0.9,0.3] recall 0.725 [0.9,0.75,0.8,0.8,0.6,0.65,0.5,0.85,0.9,0.5] recall 0.755 [0.95,0.7,0.85,0.75,0.95,0.9,0.6,0.7,1,0.15] recall 0.785 [0.95,0.7,0.95,1,0.8,0.7,0.55,0.75,0.9,0.55] recall 0.75 [1,0.55,0.85,0.7,0.6,0.9,0.55,0.9,1,0.45] recall 0.755 [1,0.8,0.95,0.9,0.55,0.8,0.25,0.9,1,0.4] recall 0.815 [0.95,0.8,0.9,0.75,0.75,0.85,0.75,0.95,0.95,0.5] recall 0.77 [0.95,0.65,1,0.8,0.55,0.95,0.5,0.9,0.8,0.6] recall 0.795 [0.9,0.7,0.85,0.95,0.8,0.65,0.7,1,1,0.4] recall 0.75 [1,0.8,0.9,0.85,0.65,0.85,0.45,0.75,0.95,0.3] relative_absolute_error 0.30364594951927276 relative_absolute_error 0.34942672814705844 relative_absolute_error 0.2988201282196383 relative_absolute_error 0.30275611213691744 relative_absolute_error 0.3029342927072547 relative_absolute_error 0.310874083728831 relative_absolute_error 0.27427650057487535 relative_absolute_error 0.3070255487689701 relative_absolute_error 0.2597343655083593 relative_absolute_error 0.3139519444789054 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 0.19283102441208627 root_mean_squared_error 0.21026476824800003 root_mean_squared_error 0.18800254214658255 root_mean_squared_error 0.19124249725580467 root_mean_squared_error 0.19306940955712687 root_mean_squared_error 0.19057878612418852 root_mean_squared_error 0.17760623922548402 root_mean_squared_error 0.19455568850396987 root_mean_squared_error 0.16772200510314186 root_mean_squared_error 0.19260685738228664 root_relative_squared_error 0.6427700813736213 root_relative_squared_error 0.7008825608266672 root_relative_squared_error 0.626675140488609 root_relative_squared_error 0.6374749908526826 root_relative_squared_error 0.6435646985237566 root_relative_squared_error 0.6352626204139621 root_relative_squared_error 0.5920207974182804 root_relative_squared_error 0.6485189616798999 root_relative_squared_error 0.5590733503438066 root_relative_squared_error 0.6420228579409559 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 691.9782569984818 usercpu_time_millis 494.5453330001328 usercpu_time_millis 470.95287399861263 usercpu_time_millis 465.0270240017562 usercpu_time_millis 467.3484449976968 usercpu_time_millis 463.44275400042534 usercpu_time_millis 487.7711589997489 usercpu_time_millis 493.19139100043685 usercpu_time_millis 462.22109900008945 usercpu_time_millis 465.6830499989155 usercpu_time_millis_testing 1.8515979991207132 usercpu_time_millis_testing 1.3315390006027883 usercpu_time_millis_testing 1.3305309985298663 usercpu_time_millis_testing 1.328427000771626 usercpu_time_millis_testing 1.321464998909505 usercpu_time_millis_testing 1.3301119997777278 usercpu_time_millis_testing 1.3308670004335 usercpu_time_millis_testing 1.3394710003922228 usercpu_time_millis_testing 1.3298590001795674 usercpu_time_millis_testing 1.3301740000315476 usercpu_time_millis_training 690.1266589993611 usercpu_time_millis_training 493.21379399953 usercpu_time_millis_training 469.62234300008276 usercpu_time_millis_training 463.6985970009846 usercpu_time_millis_training 466.0269799987873 usercpu_time_millis_training 462.1126420006476 usercpu_time_millis_training 486.4402919993154 usercpu_time_millis_training 491.85192000004463 usercpu_time_millis_training 460.8912399999099 usercpu_time_millis_training 464.352875998884