10100363 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) 8025535 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 "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 11 8783 min_samples_split 2 8783 min_weight_fraction_leaf 0.0 8783 presort false 8783 random_state 21087 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 21121264 description https://api.openml.org/data/download/21121264/description.xml -1 21121265 predictions https://api.openml.org/data/download/21121265/predictions.arff area_under_roc_curve 0.9336388888888888 [0.988282,0.880599,0.967389,0.942475,0.917372,0.948074,0.867079,0.975665,0.975165,0.874289] average_cost 0 f_measure 0.7588298294313683 [0.957179,0.685579,0.898172,0.80292,0.691358,0.841026,0.471795,0.836983,0.933002,0.470284] kappa 0.7327777777777778 kb_relative_information_score 1534.7056915324583 mean_absolute_error 0.05554578850844741 mean_prior_absolute_error 0.18000000000000554 number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.75947729695575 [0.964467,0.650224,0.939891,0.781991,0.682927,0.863158,0.484211,0.815166,0.926108,0.486631] predictive_accuracy 0.7595000000000001 prior_entropy 3.321928094887362 recall 0.7595 [0.95,0.725,0.86,0.825,0.7,0.82,0.46,0.86,0.94,0.455] relative_absolute_error 0.3085877139358094 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.18949185074640765 root_relative_squared_error 0.6316395024880158 total_cost 0 area_under_roc_curve 0.9361111111111111 [0.996944,0.919167,0.965694,0.912361,0.933472,0.968056,0.860417,0.989583,0.997917,0.8175] area_under_roc_curve 0.9099861111111112 [0.971389,0.912361,0.917778,0.903194,0.820694,0.895833,0.876111,0.988472,0.948056,0.865972] area_under_roc_curve 0.9462222222222223 [0.998611,0.875417,0.945972,0.933611,0.983472,0.99125,0.891111,0.946806,0.999722,0.89625] area_under_roc_curve 0.9294444444444445 [0.97375,0.873472,0.968889,0.986806,0.942917,0.884028,0.837639,0.968333,0.949444,0.909167] area_under_roc_curve 0.9206111111111112 [0.997083,0.846111,0.967222,0.911111,0.924167,0.945278,0.870972,0.929028,0.996667,0.818472] area_under_roc_curve 0.9518055555555556 [1,0.939167,0.998472,0.963333,0.938056,0.937222,0.878333,0.990417,0.999028,0.874028] area_under_roc_curve 0.9413611111111112 [0.999583,0.896944,0.947639,0.938056,0.959167,0.980972,0.883333,0.989028,0.974583,0.844306] area_under_roc_curve 0.9205277777777777 [0.97125,0.807083,0.999444,0.947361,0.818889,0.994306,0.875694,0.985556,0.919583,0.886111] area_under_roc_curve 0.9477500000000001 [0.974444,0.813889,0.995972,0.985,0.953056,0.915972,0.911528,0.984167,1,0.943472] area_under_roc_curve 0.9342777777777779 [0.999583,0.927361,0.969028,0.941389,0.900278,0.97,0.783611,0.991389,0.969444,0.890694] 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 0.7551648389774193 [0.97561,0.666667,0.842105,0.820513,0.731707,0.923077,0.439024,0.820513,0.9,0.432432] f_measure 0.6974408861219312 [0.894737,0.697674,0.864865,0.761905,0.571429,0.648649,0.206897,0.871795,0.947368,0.509091] f_measure 0.744211302078162 [0.918919,0.666667,0.918919,0.820513,0.791667,0.837209,0.454545,0.8,0.97561,0.258065] f_measure 0.7861223918112533 [0.974359,0.682927,0.923077,0.851064,0.711111,0.777778,0.604651,0.833333,0.947368,0.555556] f_measure 0.7320009509255354 [0.97561,0.615385,0.888889,0.756757,0.615385,0.9,0.461538,0.765957,0.930233,0.410256] f_measure 0.7458942592317119 [1,0.708333,0.947368,0.837209,0.647059,0.857143,0.275862,0.844444,0.909091,0.432432] f_measure 0.795165278348847 [0.974359,0.736842,0.923077,0.810811,0.761905,0.829268,0.590909,0.863636,0.974359,0.486486] f_measure 0.7450470374444165 [0.95,0.636364,0.9,0.682927,0.628571,0.926829,0.424242,0.837209,0.842105,0.622222] f_measure 0.8071880621631269 [0.974359,0.684211,0.894737,0.826087,0.731707,0.764706,0.682927,0.888889,0.97561,0.648649] f_measure 0.7460206234535246 [0.930233,0.761905,0.878049,0.85,0.684211,0.918919,0.425532,0.842105,0.926829,0.242424] kappa 0.7277777777777777 kappa 0.6666666666666666 kappa 0.7222222222222222 kappa 0.7611111111111112 kappa 0.7055555555555556 kappa 0.7388888888888889 kappa 0.7722222222222223 kappa 0.7222222222222222 kappa 0.788888888888889 kappa 0.7222222222222222 kb_relative_information_score 154.01215083289352 kb_relative_information_score 142.74632318166124 kb_relative_information_score 155.8176214251169 kb_relative_information_score 155.75369699334652 kb_relative_information_score 151.7255553036208 kb_relative_information_score 152.89690887140142 kb_relative_information_score 157.0509563551225 kb_relative_information_score 151.35278166563842 kb_relative_information_score 160.262120500095 kb_relative_information_score 153.0875764035838 mean_absolute_error 0.05374903795035371 mean_absolute_error 0.06603429417160062 mean_absolute_error 0.05316039197730373 mean_absolute_error 0.053122223815915776 mean_absolute_error 0.05648762434675745 mean_absolute_error 0.056718533676505756 mean_absolute_error 0.0519740711086299 mean_absolute_error 0.05786460032485571 mean_absolute_error 0.04974679666738489 mean_absolute_error 0.056600311045163984 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 0.7586294166789521 [0.952381,0.6,0.888889,0.842105,0.714286,0.947368,0.428571,0.842105,0.9,0.470588] precision 0.7144474629183205 [0.944444,0.652174,0.941176,0.727273,0.545455,0.705882,0.333333,0.894737,1,0.4] precision 0.7569302703398813 [1,0.6,1,0.842105,0.678571,0.782609,0.416667,0.933333,0.952381,0.363636] precision 0.7997493219764386 [1,0.666667,0.947368,0.740741,0.64,0.875,0.565217,0.9375,1,0.625] precision 0.7370036985045735 [0.952381,0.631579,1,0.823529,0.631579,0.9,0.473684,0.666667,0.869565,0.421053] precision 0.7502013669763029 [1,0.607143,1,0.782609,0.785714,0.818182,0.444444,0.76,0.833333,0.470588] precision 0.8007040774842632 [1,0.777778,0.947368,0.882353,0.727273,0.809524,0.541667,0.791667,1,0.529412] precision 0.750805436109784 [0.95,0.583333,0.9,0.666667,0.733333,0.904762,0.538462,0.782609,0.888889,0.56] precision 0.8165223012281835 [1,0.722222,0.944444,0.730769,0.714286,0.928571,0.666667,0.8,0.952381,0.705882] precision 0.7497916495742584 [0.869565,0.727273,0.857143,0.85,0.722222,1,0.37037,0.888889,0.904762,0.307692] predictive_accuracy 0.755 predictive_accuracy 0.7 predictive_accuracy 0.75 predictive_accuracy 0.785 predictive_accuracy 0.735 predictive_accuracy 0.765 predictive_accuracy 0.795 predictive_accuracy 0.75 predictive_accuracy 0.81 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 0.755 [1,0.75,0.8,0.8,0.75,0.9,0.45,0.8,0.9,0.4] recall 0.7 [0.85,0.75,0.8,0.8,0.6,0.6,0.15,0.85,0.9,0.7] recall 0.75 [0.85,0.75,0.85,0.8,0.95,0.9,0.5,0.7,1,0.2] recall 0.785 [0.95,0.7,0.9,1,0.8,0.7,0.65,0.75,0.9,0.5] recall 0.735 [1,0.6,0.8,0.7,0.6,0.9,0.45,0.9,1,0.4] recall 0.765 [1,0.85,0.9,0.9,0.55,0.9,0.2,0.95,1,0.4] recall 0.795 [0.95,0.7,0.9,0.75,0.8,0.85,0.65,0.95,0.95,0.45] recall 0.75 [0.95,0.7,0.9,0.7,0.55,0.95,0.35,0.9,0.8,0.7] recall 0.81 [0.95,0.65,0.85,0.95,0.75,0.65,0.7,1,1,0.6] recall 0.75 [1,0.8,0.9,0.85,0.65,0.85,0.5,0.8,0.95,0.2] relative_absolute_error 0.2986057663908543 relative_absolute_error 0.36685718984222604 relative_absolute_error 0.2953355109850211 relative_absolute_error 0.29512346564397685 relative_absolute_error 0.31382013525976393 relative_absolute_error 0.31510296486947675 relative_absolute_error 0.28874483949238866 relative_absolute_error 0.3214700018047543 relative_absolute_error 0.27637109259658305 relative_absolute_error 0.3144461724731336 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 0.19080724079128847 root_mean_squared_error 0.21364845673691585 root_mean_squared_error 0.18160582864019592 root_mean_squared_error 0.18569963441261028 root_mean_squared_error 0.1953371162780934 root_mean_squared_error 0.18452305838207972 root_mean_squared_error 0.1820409198392481 root_mean_squared_error 0.1956053715600381 root_mean_squared_error 0.17348412980621924 root_mean_squared_error 0.18934378343972474 root_relative_squared_error 0.6360241359709619 root_relative_squared_error 0.7121615224563865 root_relative_squared_error 0.6053527621339867 root_relative_squared_error 0.6189987813753679 root_relative_squared_error 0.6511237209269783 root_relative_squared_error 0.6150768612735995 root_relative_squared_error 0.6068030661308275 root_relative_squared_error 0.6520179052001274 root_relative_squared_error 0.5782804326873978 root_relative_squared_error 0.6311459447990829 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 2545.5319040001996 usercpu_time_millis 2269.3275789997642 usercpu_time_millis 2314.1698839999663 usercpu_time_millis 2544.1870940003355 usercpu_time_millis 2563.0373350004447 usercpu_time_millis 2364.109274999464 usercpu_time_millis 2307.6736630000596 usercpu_time_millis 2303.8753470009397 usercpu_time_millis 2281.4533450000454 usercpu_time_millis 2271.6795890000867 usercpu_time_millis_testing 1.3102169996273005 usercpu_time_millis_testing 1.3091860000713496 usercpu_time_millis_testing 1.3013859997954569 usercpu_time_millis_testing 1.654656999562576 usercpu_time_millis_testing 1.4375159998962772 usercpu_time_millis_testing 1.3014460000704275 usercpu_time_millis_testing 1.3091000000713393 usercpu_time_millis_testing 1.2947080003868905 usercpu_time_millis_testing 1.3468739998643287 usercpu_time_millis_testing 1.306434999605699 usercpu_time_millis_training 2544.2216870005723 usercpu_time_millis_training 2268.018392999693 usercpu_time_millis_training 2312.868498000171 usercpu_time_millis_training 2542.532437000773 usercpu_time_millis_training 2561.5998190005485 usercpu_time_millis_training 2362.8078289993937 usercpu_time_millis_training 2306.3645629999883 usercpu_time_millis_training 2302.5806390005528 usercpu_time_millis_training 2280.106471000181 usercpu_time_millis_training 2270.373154000481