OpenML

Sergey Redyuk 3 years ago
ran flow sklearn.ensemble.forest.RandomForestClassifier(66) on task Supervised Classification on data set PhishingWebsites

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9942, f_measure: 0.9724, kappa: 0.944, kb_relative_information_score: 0.9084, mean_absolute_error: 0.0491, mean_prior_absolute_error: 0.4935, weighted_recall: 0.9724, number_of_instances: 11055, precision: 0.9724, predictive_accuracy: 0.9724, prior_entropy: 0.9906, relative_absolute_error: 0.0995, root_mean_prior_squared_error: 0.4967, root_mean_squared_error: 0.1489, root_relative_squared_error: 0.2998, unweighted_recall: 0.9716,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(minm ... est.RandomForestClassifier)(2) on task Supervised Classification on data set balance-scale

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.963, f_measure: 0.8674, kappa: 0.7838, kb_relative_information_score: 0.6707, mean_absolute_error: 0.1255, mean_prior_absolute_error: 0.3798, weighted_recall: 0.88, number_of_instances: 625, precision: 0.8595, predictive_accuracy: 0.88, prior_entropy: 1.3181, relative_absolute_error: 0.3306, root_mean_prior_squared_error: 0.4356, root_mean_squared_error: 0.2446, root_relative_squared_error: 0.5615, unweighted_recall: 0.6874,

Sergey Redyuk 3 years ago
ran flow sklearn.naive_bayes.MultinomialNB(8) on task Supervised Classification on data set balance-scale

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9583, kappa: 0.7507, kb_relative_information_score: 0.3444, mean_absolute_error: 0.2632, mean_prior_absolute_error: 0.3798, weighted_recall: 0.8656, number_of_instances: 625, predictive_accuracy: 0.8656, prior_entropy: 1.3181, relative_absolute_error: 0.6931, root_mean_prior_squared_error: 0.4356, root_mean_squared_error: 0.3195, root_relative_squared_error: 0.7336, unweighted_recall: 0.6262,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(grad ... GradientBoostingClassifier)(4) on task Supervised Classification on data set balance-scale

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9655, f_measure: 0.8537, kappa: 0.7737, kb_relative_information_score: 0.5999, mean_absolute_error: 0.1435, mean_prior_absolute_error: 0.3798, weighted_recall: 0.8752, number_of_instances: 625, precision: 0.8332, predictive_accuracy: 0.8752, prior_entropy: 1.3181, relative_absolute_error: 0.3778, root_mean_prior_squared_error: 0.4356, root_mean_squared_error: 0.2522, root_relative_squared_error: 0.5791, unweighted_recall: 0.6331,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(2) on task Supervised Classification on data set blood-transfusion-service-center

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6636, f_measure: 0.7367, kappa: 0.2336, kb_relative_information_score: 0.0959, mean_absolute_error: 0.301, mean_prior_absolute_error: 0.363, weighted_recall: 0.758, number_of_instances: 748, precision: 0.7295, predictive_accuracy: 0.758, prior_entropy: 0.7916, relative_absolute_error: 0.829, root_mean_prior_squared_error: 0.4258, root_mean_squared_error: 0.4308, root_relative_squared_error: 1.0116, unweighted_recall: 0.6017,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(3) on task Supervised Classification on data set blood-transfusion-service-center

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6815, f_measure: 0.7208, kappa: 0.1911, kb_relative_information_score: 0.0769, mean_absolute_error: 0.3033, mean_prior_absolute_error: 0.363, weighted_recall: 0.7406, number_of_instances: 748, precision: 0.7113, predictive_accuracy: 0.7406, prior_entropy: 0.7916, relative_absolute_error: 0.8354, root_mean_prior_squared_error: 0.4258, root_mean_squared_error: 0.4361, root_relative_squared_error: 1.0241, unweighted_recall: 0.5845,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(pca= ... est.RandomForestClassifier)(4) on task Supervised Classification on data set blood-transfusion-service-center

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6733, f_measure: 0.7312, kappa: 0.2147, kb_relative_information_score: 0.0844, mean_absolute_error: 0.3045, mean_prior_absolute_error: 0.363, weighted_recall: 0.7553, number_of_instances: 748, precision: 0.7237, predictive_accuracy: 0.7553, prior_entropy: 0.7916, relative_absolute_error: 0.8389, root_mean_prior_squared_error: 0.4258, root_mean_squared_error: 0.4287, root_relative_squared_error: 1.0068, unweighted_recall: 0.5922,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(3) on task Supervised Classification on data set breast-w

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9862, f_measure: 0.9512, kappa: 0.8915, kb_relative_information_score: 0.8636, mean_absolute_error: 0.0645, mean_prior_absolute_error: 0.4519, weighted_recall: 0.9514, number_of_instances: 699, precision: 0.9512, predictive_accuracy: 0.9514, prior_entropy: 0.9293, relative_absolute_error: 0.1428, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1841, root_relative_squared_error: 0.3873, unweighted_recall: 0.9422,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... r_perceptron.MLPClassifier)(2) on task Supervised Classification on data set diabetes

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7758, f_measure: 0.7294, kappa: 0.405, kb_relative_information_score: 0.3734, mean_absolute_error: 0.2754, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7292, number_of_instances: 768, precision: 0.7296, predictive_accuracy: 0.7292, prior_entropy: 0.9331, relative_absolute_error: 0.606, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4704, root_relative_squared_error: 0.9869, unweighted_recall: 0.7028,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... vc=sklearn.svm.classes.SVC)(8) on task Supervised Classification on data set cmc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7279, f_measure: 0.5349, kappa: 0.2789, kb_relative_information_score: 0.1969, mean_absolute_error: 0.376, mean_prior_absolute_error: 0.4308, weighted_recall: 0.5465, number_of_instances: 1473, precision: 0.5376, predictive_accuracy: 0.5465, prior_entropy: 1.539, relative_absolute_error: 0.8728, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4308, root_relative_squared_error: 0.9282, unweighted_recall: 0.5068,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... ogistic.LogisticRegression)(5) on task Supervised Classification on data set cmc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6965, f_measure: 0.5039, kappa: 0.2282, kb_relative_information_score: 0.1793, mean_absolute_error: 0.3832, mean_prior_absolute_error: 0.4308, weighted_recall: 0.5119, number_of_instances: 1473, precision: 0.5051, predictive_accuracy: 0.5119, prior_entropy: 1.539, relative_absolute_error: 0.8895, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4379, root_relative_squared_error: 0.9436, unweighted_recall: 0.4772,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... r_perceptron.MLPClassifier)(2) on task Supervised Classification on data set cmc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.689, f_measure: 0.5141, kappa: 0.2478, kb_relative_information_score: 0.2738, mean_absolute_error: 0.3407, mean_prior_absolute_error: 0.4308, weighted_recall: 0.5139, number_of_instances: 1473, precision: 0.5143, predictive_accuracy: 0.5139, prior_entropy: 1.539, relative_absolute_error: 0.7907, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4788, root_relative_squared_error: 1.0316, unweighted_recall: 0.4958,

Sergey Redyuk 3 years ago
ran flow sklearn.tree.tree.ExtraTreeClassifier(28) on task Supervised Classification on data set cmc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5826, f_measure: 0.4536, kappa: 0.1552, kb_relative_information_score: 0.2198, mean_absolute_error: 0.3647, mean_prior_absolute_error: 0.4308, weighted_recall: 0.4535, number_of_instances: 1473, precision: 0.4538, predictive_accuracy: 0.4535, prior_entropy: 1.539, relative_absolute_error: 0.8465, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.5958, root_relative_squared_error: 1.2838, unweighted_recall: 0.4349,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(3) on task Supervised Classification on data set banknote-authentication

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9991, f_measure: 0.9898, kappa: 0.9793, kb_relative_information_score: 0.9607, mean_absolute_error: 0.0223, mean_prior_absolute_error: 0.4939, weighted_recall: 0.9898, number_of_instances: 1372, precision: 0.9898, predictive_accuracy: 0.9898, prior_entropy: 0.9911, relative_absolute_error: 0.0452, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.0861, root_relative_squared_error: 0.1733, unweighted_recall: 0.9895,

Sergey Redyuk 3 years ago
ran flow sklearn.ensemble.voting_classi ... e.tree.ExtraTreeClassifier)(2) on task Supervised Classification on data set banknote-authentication

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9928, f_measure: 0.9934, kappa: 0.9867, kb_relative_information_score: 0.9866, mean_absolute_error: 0.0066, mean_prior_absolute_error: 0.4939, weighted_recall: 0.9934, number_of_instances: 1372, precision: 0.9935, predictive_accuracy: 0.9934, prior_entropy: 0.9911, relative_absolute_error: 0.0133, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.081, root_relative_squared_error: 0.163, unweighted_recall: 0.9928,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(2) on task Supervised Classification on data set banknote-authentication

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 0.9978, kappa: 0.9956, kb_relative_information_score: 0.9553, mean_absolute_error: 0.0277, mean_prior_absolute_error: 0.4939, weighted_recall: 0.9978, number_of_instances: 1372, precision: 0.9978, predictive_accuracy: 0.9978, prior_entropy: 0.9911, relative_absolute_error: 0.0561, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.0705, root_relative_squared_error: 0.1419, unweighted_recall: 0.9977,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(2) on task Supervised Classification on data set kc2

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7412, f_measure: 0.7462, kappa: 0.1677, kb_relative_information_score: 0.0229, mean_absolute_error: 0.2753, mean_prior_absolute_error: 0.3266, weighted_recall: 0.7701, number_of_instances: 522, precision: 0.7343, predictive_accuracy: 0.7701, prior_entropy: 0.7318, relative_absolute_error: 0.843, root_mean_prior_squared_error: 0.4037, root_mean_squared_error: 0.3884, root_relative_squared_error: 0.9622, unweighted_recall: 0.571,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... r_perceptron.MLPClassifier)(2) on task Supervised Classification on data set kc2

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7587, f_measure: 0.8387, kappa: 0.4934, kb_relative_information_score: 0.3351, mean_absolute_error: 0.1988, mean_prior_absolute_error: 0.3266, weighted_recall: 0.8429, number_of_instances: 522, precision: 0.8361, predictive_accuracy: 0.8429, prior_entropy: 0.7318, relative_absolute_error: 0.6088, root_mean_prior_squared_error: 0.4037, root_mean_squared_error: 0.3645, root_relative_squared_error: 0.9029, unweighted_recall: 0.7347,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(7) on task Supervised Classification on data set vehicle

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9126, f_measure: 0.734, kappa: 0.6565, kb_relative_information_score: 0.6414, mean_absolute_error: 0.1663, mean_prior_absolute_error: 0.3748, weighted_recall: 0.7423, number_of_instances: 846, precision: 0.7285, predictive_accuracy: 0.7423, prior_entropy: 1.9991, relative_absolute_error: 0.4437, root_mean_prior_squared_error: 0.4329, root_mean_squared_error: 0.2896, root_relative_squared_error: 0.669, unweighted_recall: 0.7457,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... ree.DecisionTreeClassifier)(2) on task Supervised Classification on data set vehicle

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4946, kappa: -0.0029, kb_relative_information_score: 0.0003, mean_absolute_error: 0.3748, mean_prior_absolute_error: 0.3748, weighted_recall: 0.2553, number_of_instances: 846, predictive_accuracy: 0.2553, prior_entropy: 1.9991, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4329, root_mean_squared_error: 0.4329, root_relative_squared_error: 1, unweighted_recall: 0.2479,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(grad ... GradientBoostingClassifier)(4) on task Supervised Classification on data set vehicle

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9338, f_measure: 0.764, kappa: 0.6911, kb_relative_information_score: 0.6608, mean_absolute_error: 0.1565, mean_prior_absolute_error: 0.3748, weighted_recall: 0.7683, number_of_instances: 846, precision: 0.7611, predictive_accuracy: 0.7683, prior_entropy: 1.9991, relative_absolute_error: 0.4174, root_mean_prior_squared_error: 0.4329, root_mean_squared_error: 0.2711, root_relative_squared_error: 0.6263, unweighted_recall: 0.7712,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... r_perceptron.MLPClassifier)(2) on task Supervised Classification on data set wdbc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.992, f_measure: 0.9736, kappa: 0.9433, kb_relative_information_score: 0.9409, mean_absolute_error: 0.0273, mean_prior_absolute_error: 0.4676, weighted_recall: 0.9736, number_of_instances: 569, precision: 0.9737, predictive_accuracy: 0.9736, prior_entropy: 0.9526, relative_absolute_error: 0.0583, root_mean_prior_squared_error: 0.4835, root_mean_squared_error: 0.1525, root_relative_squared_error: 0.3154, unweighted_recall: 0.9694,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(pca= ... est.RandomForestClassifier)(4) on task Supervised Classification on data set analcatdata_authorship

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9867, f_measure: 0.9452, kappa: 0.9201, kb_relative_information_score: 0.7275, mean_absolute_error: 0.1317, mean_prior_absolute_error: 0.3439, weighted_recall: 0.9453, number_of_instances: 841, precision: 0.9457, predictive_accuracy: 0.9453, prior_entropy: 1.7874, relative_absolute_error: 0.3831, root_mean_prior_squared_error: 0.4146, root_mean_squared_error: 0.2042, root_relative_squared_error: 0.4925, unweighted_recall: 0.9312,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(grad ... GradientBoostingClassifier)(4) on task Supervised Classification on data set qsar-biodeg

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.927, f_measure: 0.8702, kappa: 0.7063, kb_relative_information_score: 0.5574, mean_absolute_error: 0.2095, mean_prior_absolute_error: 0.4472, weighted_recall: 0.872, number_of_instances: 1055, precision: 0.8707, predictive_accuracy: 0.872, prior_entropy: 0.9223, relative_absolute_error: 0.4684, root_mean_prior_squared_error: 0.4728, root_mean_squared_error: 0.3106, root_relative_squared_error: 0.657, unweighted_recall: 0.8442,

Sergey Redyuk 3 years ago
ran flow sklearn.model_selection._searc ... orest.ExtraTreesClassifier)(2) on task Supervised Classification on data set qsar-biodeg

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9302, f_measure: 0.8635, kappa: 0.6913, kb_relative_information_score: 0.5635, mean_absolute_error: 0.2049, mean_prior_absolute_error: 0.4472, weighted_recall: 0.8654, number_of_instances: 1055, precision: 0.8639, predictive_accuracy: 0.8654, prior_entropy: 0.9223, relative_absolute_error: 0.4581, root_mean_prior_squared_error: 0.4728, root_mean_squared_error: 0.3072, root_relative_squared_error: 0.6497, unweighted_recall: 0.8371,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... GradientBoostingClassifier)(2) on task Supervised Classification on data set climate-model-simulation-crashes

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8606, f_measure: 0.8889, kappa: 0.1528, kb_relative_information_score: 0.1713, mean_absolute_error: 0.1016, mean_prior_absolute_error: 0.1571, weighted_recall: 0.9148, number_of_instances: 540, precision: 0.8866, predictive_accuracy: 0.9148, prior_entropy: 0.4202, relative_absolute_error: 0.6467, root_mean_prior_squared_error: 0.2792, root_mean_squared_error: 0.2585, root_relative_squared_error: 0.9259, unweighted_recall: 0.5493,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(2) on task Supervised Classification on data set wilt

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5219, f_measure: 0.9233, kappa: 0.0496, kb_relative_information_score: 0.0975, mean_absolute_error: 0.0636, mean_prior_absolute_error: 0.1022, weighted_recall: 0.9475, number_of_instances: 4839, precision: 0.9503, predictive_accuracy: 0.9475, prior_entropy: 0.3029, relative_absolute_error: 0.6223, root_mean_prior_squared_error: 0.2259, root_mean_squared_error: 0.2275, root_relative_squared_error: 1.0073, unweighted_recall: 0.5134,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(minm ... est.RandomForestClassifier)(2) on task Supervised Classification on data set balance-scale

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9846, f_measure: 0.932, kappa: 0.8877, kb_relative_information_score: 0.7167, mean_absolute_error: 0.1242, mean_prior_absolute_error: 0.3798, weighted_recall: 0.9376, number_of_instances: 625, precision: 0.9365, predictive_accuracy: 0.9376, prior_entropy: 1.3181, relative_absolute_error: 0.3269, root_mean_prior_squared_error: 0.4356, root_mean_squared_error: 0.2131, root_relative_squared_error: 0.4892, unweighted_recall: 0.8137,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... est.RandomForestClassifier)(3) on task Supervised Classification on data set balance-scale

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9605, f_measure: 0.8726, kappa: 0.7944, kb_relative_information_score: 0.6743, mean_absolute_error: 0.1241, mean_prior_absolute_error: 0.3798, weighted_recall: 0.8864, number_of_instances: 625, precision: 0.8671, predictive_accuracy: 0.8864, prior_entropy: 1.3181, relative_absolute_error: 0.3267, root_mean_prior_squared_error: 0.4356, root_mean_squared_error: 0.2437, root_relative_squared_error: 0.5594, unweighted_recall: 0.6977,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(2) on task Supervised Classification on data set blood-transfusion-service-center

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5866, f_measure: 0.6794, kappa: 0.0664, kb_relative_information_score: -0.1536, mean_absolute_error: 0.3715, mean_prior_absolute_error: 0.363, weighted_recall: 0.7059, number_of_instances: 748, precision: 0.6636, predictive_accuracy: 0.7059, prior_entropy: 0.7916, relative_absolute_error: 1.0233, root_mean_prior_squared_error: 0.4258, root_mean_squared_error: 0.4484, root_relative_squared_error: 1.0529, unweighted_recall: 0.5288,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(feat ... ogistic.LogisticRegression)(2) on task Supervised Classification on data set blood-transfusion-service-center

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6521, f_measure: 0.7175, kappa: 0.1985, kb_relative_information_score: 0.0687, mean_absolute_error: 0.3103, mean_prior_absolute_error: 0.363, weighted_recall: 0.7273, number_of_instances: 748, precision: 0.7105, predictive_accuracy: 0.7273, prior_entropy: 0.7916, relative_absolute_error: 0.8549, root_mean_prior_squared_error: 0.4258, root_mean_squared_error: 0.4745, root_relative_squared_error: 1.1143, unweighted_recall: 0.5931,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... vc=sklearn.svm.classes.SVC)(8) on task Supervised Classification on data set blood-transfusion-service-center

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6955, f_measure: 0.7161, kappa: 0.1545, kb_relative_information_score: 0.0979, mean_absolute_error: 0.3292, mean_prior_absolute_error: 0.363, weighted_recall: 0.7727, number_of_instances: 748, precision: 0.7381, predictive_accuracy: 0.7727, prior_entropy: 0.7916, relative_absolute_error: 0.9067, root_mean_prior_squared_error: 0.4258, root_mean_squared_error: 0.4023, root_relative_squared_error: 0.9448, unweighted_recall: 0.5572,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(voti ... st.RandomForestClassifier))(2) on task Supervised Classification on data set blood-transfusion-service-center

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6538, f_measure: 0.7106, kappa: 0.1816, kb_relative_information_score: 0.0378, mean_absolute_error: 0.3097, mean_prior_absolute_error: 0.363, weighted_recall: 0.7193, number_of_instances: 748, precision: 0.704, predictive_accuracy: 0.7193, prior_entropy: 0.7916, relative_absolute_error: 0.853, root_mean_prior_squared_error: 0.4258, root_mean_squared_error: 0.4635, root_relative_squared_error: 1.0885, unweighted_recall: 0.5859,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... .tree.ExtraTreeClassifier))(2) on task Supervised Classification on data set blood-transfusion-service-center

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5557, f_measure: 0.7054, kappa: 0.1336, kb_relative_information_score: 0.1856, mean_absolute_error: 0.262, mean_prior_absolute_error: 0.363, weighted_recall: 0.738, number_of_instances: 748, precision: 0.6939, predictive_accuracy: 0.738, prior_entropy: 0.7916, relative_absolute_error: 0.7218, root_mean_prior_squared_error: 0.4258, root_mean_squared_error: 0.5119, root_relative_squared_error: 1.2021, unweighted_recall: 0.5557,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(pca= ... orest.ExtraTreesClassifier)(2) on task Supervised Classification on data set diabetes

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8202, f_measure: 0.7591, kappa: 0.459, kb_relative_information_score: 0.2803, mean_absolute_error: 0.3338, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7682, number_of_instances: 768, precision: 0.7629, predictive_accuracy: 0.7682, prior_entropy: 0.9331, relative_absolute_error: 0.7343, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4031, root_relative_squared_error: 0.8457, unweighted_recall: 0.7164,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(7) on task Supervised Classification on data set diabetes

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7944, f_measure: 0.7359, kappa: 0.4068, kb_relative_information_score: 0.3049, mean_absolute_error: 0.316, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7461, number_of_instances: 768, precision: 0.7385, predictive_accuracy: 0.7461, prior_entropy: 0.9331, relative_absolute_error: 0.6953, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4188, root_relative_squared_error: 0.8786, unweighted_recall: 0.6916,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(3) on task Supervised Classification on data set kc2

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8137, f_measure: 0.8115, kappa: 0.3917, kb_relative_information_score: 0.2623, mean_absolute_error: 0.2149, mean_prior_absolute_error: 0.3266, weighted_recall: 0.8238, number_of_instances: 522, precision: 0.8077, predictive_accuracy: 0.8238, prior_entropy: 0.7318, relative_absolute_error: 0.6579, root_mean_prior_squared_error: 0.4037, root_mean_squared_error: 0.3518, root_relative_squared_error: 0.8716, unweighted_recall: 0.6741,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(grad ... GradientBoostingClassifier)(4) on task Supervised Classification on data set kc2

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7948, f_measure: 0.8204, kappa: 0.418, kb_relative_information_score: 0.27, mean_absolute_error: 0.2215, mean_prior_absolute_error: 0.3266, weighted_recall: 0.8333, number_of_instances: 522, precision: 0.8182, predictive_accuracy: 0.8333, prior_entropy: 0.7318, relative_absolute_error: 0.6784, root_mean_prior_squared_error: 0.4037, root_mean_squared_error: 0.3516, root_relative_squared_error: 0.871, unweighted_recall: 0.6836,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(3) on task Supervised Classification on data set vehicle

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.909, f_measure: 0.7196, kappa: 0.6376, kb_relative_information_score: 0.633, mean_absolute_error: 0.1684, mean_prior_absolute_error: 0.3748, weighted_recall: 0.7281, number_of_instances: 846, precision: 0.7156, predictive_accuracy: 0.7281, prior_entropy: 1.9991, relative_absolute_error: 0.4494, root_mean_prior_squared_error: 0.4329, root_mean_squared_error: 0.2932, root_relative_squared_error: 0.6773, unweighted_recall: 0.7318,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(3) on task Supervised Classification on data set mfeat-morphological

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9381, f_measure: 0.698, kappa: 0.6661, kb_relative_information_score: 0.7188, mean_absolute_error: 0.0687, mean_prior_absolute_error: 0.18, weighted_recall: 0.6995, number_of_instances: 2000, precision: 0.6973, predictive_accuracy: 0.6995, prior_entropy: 3.3219, relative_absolute_error: 0.3814, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2066, root_relative_squared_error: 0.6887, unweighted_recall: 0.6995,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(grad ... GradientBoostingClassifier)(4) on task Supervised Classification on data set wdbc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.985, f_measure: 0.9594, kappa: 0.913, kb_relative_information_score: 0.8244, mean_absolute_error: 0.0937, mean_prior_absolute_error: 0.4676, weighted_recall: 0.9596, number_of_instances: 569, precision: 0.9596, predictive_accuracy: 0.9596, prior_entropy: 0.9526, relative_absolute_error: 0.2004, root_mean_prior_squared_error: 0.4835, root_mean_squared_error: 0.1794, root_relative_squared_error: 0.3711, unweighted_recall: 0.9534,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(3) on task Supervised Classification on data set wdbc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9865, f_measure: 0.9559, kappa: 0.9052, kb_relative_information_score: 0.845, mean_absolute_error: 0.0772, mean_prior_absolute_error: 0.4676, weighted_recall: 0.9561, number_of_instances: 569, precision: 0.9562, predictive_accuracy: 0.9561, prior_entropy: 0.9526, relative_absolute_error: 0.165, root_mean_prior_squared_error: 0.4835, root_mean_squared_error: 0.1916, root_relative_squared_error: 0.3963, unweighted_recall: 0.9487,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(7) on task Supervised Classification on data set analcatdata_authorship

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9992, f_measure: 0.9727, kappa: 0.9602, kb_relative_information_score: 0.86, mean_absolute_error: 0.0706, mean_prior_absolute_error: 0.3439, weighted_recall: 0.9727, number_of_instances: 841, precision: 0.9727, predictive_accuracy: 0.9727, prior_entropy: 1.7874, relative_absolute_error: 0.2054, root_mean_prior_squared_error: 0.4146, root_mean_squared_error: 0.1371, root_relative_squared_error: 0.3307, unweighted_recall: 0.9699,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... ree.DecisionTreeClassifier)(2) on task Supervised Classification on data set qsar-biodeg

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.496, kb_relative_information_score: 0.0002, mean_absolute_error: 0.4472, mean_prior_absolute_error: 0.4472, weighted_recall: 0.6626, number_of_instances: 1055, predictive_accuracy: 0.6626, prior_entropy: 0.9223, relative_absolute_error: 0.9998, root_mean_prior_squared_error: 0.4728, root_mean_squared_error: 0.4728, root_relative_squared_error: 1, unweighted_recall: 0.5,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... ogistic.LogisticRegression)(5) on task Supervised Classification on data set qsar-biodeg

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9251, f_measure: 0.8706, kappa: 0.7097, kb_relative_information_score: 0.5795, mean_absolute_error: 0.1946, mean_prior_absolute_error: 0.4472, weighted_recall: 0.8711, number_of_instances: 1055, precision: 0.8703, predictive_accuracy: 0.8711, prior_entropy: 0.9223, relative_absolute_error: 0.4352, root_mean_prior_squared_error: 0.4728, root_mean_squared_error: 0.313, root_relative_squared_error: 0.6619, unweighted_recall: 0.8524,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(2) on task Supervised Classification on data set qsar-biodeg

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6554, f_measure: 0.6159, kappa: 0.1896, kb_relative_information_score: -0.0678, mean_absolute_error: 0.456, mean_prior_absolute_error: 0.4472, weighted_recall: 0.6057, number_of_instances: 1055, precision: 0.6433, predictive_accuracy: 0.6057, prior_entropy: 0.9223, relative_absolute_error: 1.0196, root_mean_prior_squared_error: 0.4728, root_mean_squared_error: 0.4967, root_relative_squared_error: 1.0505, unweighted_recall: 0.6032,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(minm ... est.RandomForestClassifier)(2) on task Supervised Classification on data set qsar-biodeg

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6485, f_measure: 0.6388, kappa: 0.2096, kb_relative_information_score: -0.0554, mean_absolute_error: 0.4525, mean_prior_absolute_error: 0.4472, weighted_recall: 0.6332, number_of_instances: 1055, precision: 0.6478, predictive_accuracy: 0.6332, prior_entropy: 0.9223, relative_absolute_error: 1.0118, root_mean_prior_squared_error: 0.4728, root_mean_squared_error: 0.4895, root_relative_squared_error: 1.0353, unweighted_recall: 0.6088,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... r_perceptron.MLPClassifier)(2) on task Supervised Classification on data set wilt

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9929, f_measure: 0.9873, kappa: 0.8749, kb_relative_information_score: 0.7648, mean_absolute_error: 0.0172, mean_prior_absolute_error: 0.1022, weighted_recall: 0.9874, number_of_instances: 4839, precision: 0.9873, predictive_accuracy: 0.9874, prior_entropy: 0.3029, relative_absolute_error: 0.1682, root_mean_prior_squared_error: 0.2259, root_mean_squared_error: 0.0957, root_relative_squared_error: 0.4238, unweighted_recall: 0.9319,

Sergey Redyuk 3 years ago
ran flow sklearn.model_selection._searc ... ogistic.LogisticRegression)(2) on task Supervised Classification on data set balance-scale

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9274, kappa: 0.7418, kb_relative_information_score: 0.3229, mean_absolute_error: 0.2577, mean_prior_absolute_error: 0.3798, weighted_recall: 0.8608, number_of_instances: 625, predictive_accuracy: 0.8608, prior_entropy: 1.3181, relative_absolute_error: 0.6785, root_mean_prior_squared_error: 0.4356, root_mean_squared_error: 0.3388, root_relative_squared_error: 0.7779, unweighted_recall: 0.6227,

Sergey Redyuk 3 years ago
ran flow sklearn.model_selection._searc ... orest.ExtraTreesClassifier)(2) on task Supervised Classification on data set balance-scale

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.952, kappa: 0.822, kb_relative_information_score: 0.3715, mean_absolute_error: 0.2471, mean_prior_absolute_error: 0.3798, weighted_recall: 0.904, number_of_instances: 625, predictive_accuracy: 0.904, prior_entropy: 1.3181, relative_absolute_error: 0.6507, root_mean_prior_squared_error: 0.4356, root_mean_squared_error: 0.3107, root_relative_squared_error: 0.7133, unweighted_recall: 0.6539,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(grad ... GradientBoostingClassifier)(4) on task Supervised Classification on data set diabetes

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8289, f_measure: 0.7586, kappa: 0.4617, kb_relative_information_score: 0.3338, mean_absolute_error: 0.3076, mean_prior_absolute_error: 0.4545, weighted_recall: 0.763, number_of_instances: 768, precision: 0.7578, predictive_accuracy: 0.763, prior_entropy: 0.9331, relative_absolute_error: 0.6768, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4, root_relative_squared_error: 0.8393, unweighted_recall: 0.7236,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(3) on task Supervised Classification on data set diabetes

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8039, f_measure: 0.7489, kappa: 0.4373, kb_relative_information_score: 0.3132, mean_absolute_error: 0.3126, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7565, number_of_instances: 768, precision: 0.7499, predictive_accuracy: 0.7565, prior_entropy: 0.9331, relative_absolute_error: 0.6879, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4151, root_relative_squared_error: 0.8709, unweighted_recall: 0.7083,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... est.RandomForestClassifier)(3) on task Supervised Classification on data set cmc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6517, f_measure: 0.4959, kappa: 0.2198, kb_relative_information_score: 0.2131, mean_absolute_error: 0.371, mean_prior_absolute_error: 0.4308, weighted_recall: 0.5037, number_of_instances: 1473, precision: 0.4943, predictive_accuracy: 0.5037, prior_entropy: 1.539, relative_absolute_error: 0.8611, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4702, root_relative_squared_error: 1.0131, unweighted_recall: 0.4735,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... ree.DecisionTreeClassifier)(2) on task Supervised Classification on data set cmc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4975, kb_relative_information_score: 0.0002, mean_absolute_error: 0.4308, mean_prior_absolute_error: 0.4308, weighted_recall: 0.427, number_of_instances: 1473, predictive_accuracy: 0.427, prior_entropy: 1.539, relative_absolute_error: 0.9999, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4641, root_relative_squared_error: 1, unweighted_recall: 0.3333,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(3) on task Supervised Classification on data set cmc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6905, f_measure: 0.514, kappa: 0.2473, kb_relative_information_score: 0.2593, mean_absolute_error: 0.3487, mean_prior_absolute_error: 0.4308, weighted_recall: 0.52, number_of_instances: 1473, precision: 0.5125, predictive_accuracy: 0.52, prior_entropy: 1.539, relative_absolute_error: 0.8093, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4584, root_relative_squared_error: 0.9876, unweighted_recall: 0.4916,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(Medi ... arn.naive_bayes.GaussianNB)(2) on task Supervised Classification on data set cmc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6659, f_measure: 0.4694, kappa: 0.2172, kb_relative_information_score: 0.2227, mean_absolute_error: 0.3728, mean_prior_absolute_error: 0.4308, weighted_recall: 0.4684, number_of_instances: 1473, precision: 0.5103, predictive_accuracy: 0.4684, prior_entropy: 1.539, relative_absolute_error: 0.8653, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4816, root_relative_squared_error: 1.0376, unweighted_recall: 0.4937,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(pca= ... est.RandomForestClassifier)(4) on task Supervised Classification on data set banknote-authentication

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9999, f_measure: 0.9978, kappa: 0.9956, kb_relative_information_score: 0.977, mean_absolute_error: 0.0138, mean_prior_absolute_error: 0.4939, weighted_recall: 0.9978, number_of_instances: 1372, precision: 0.9978, predictive_accuracy: 0.9978, prior_entropy: 0.9911, relative_absolute_error: 0.0279, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.058, root_relative_squared_error: 0.1167, unweighted_recall: 0.9979,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(feat ... ogistic.LogisticRegression)(2) on task Supervised Classification on data set banknote-authentication

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 1, kappa: 1, kb_relative_information_score: 0.9898, mean_absolute_error: 0.0064, mean_prior_absolute_error: 0.4939, weighted_recall: 1, number_of_instances: 1372, precision: 1, predictive_accuracy: 1, prior_entropy: 0.9911, relative_absolute_error: 0.013, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.0293, root_relative_squared_error: 0.0589, unweighted_recall: 1,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(voti ... st.RandomForestClassifier))(2) on task Supervised Classification on data set banknote-authentication

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9999, f_measure: 0.9964, kappa: 0.9926, kb_relative_information_score: 0.98, mean_absolute_error: 0.0115, mean_prior_absolute_error: 0.4939, weighted_recall: 0.9964, number_of_instances: 1372, precision: 0.9964, predictive_accuracy: 0.9964, prior_entropy: 0.9911, relative_absolute_error: 0.0233, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.0597, root_relative_squared_error: 0.1202, unweighted_recall: 0.9967,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(2) on task Supervised Classification on data set banknote-authentication

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9951, f_measure: 0.9709, kappa: 0.9411, kb_relative_information_score: 0.6673, mean_absolute_error: 0.1883, mean_prior_absolute_error: 0.4939, weighted_recall: 0.9708, number_of_instances: 1372, precision: 0.9712, predictive_accuracy: 0.9708, prior_entropy: 0.9911, relative_absolute_error: 0.3814, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.2433, root_relative_squared_error: 0.4897, unweighted_recall: 0.9718,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(7) on task Supervised Classification on data set banknote-authentication

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9997, f_measure: 0.9913, kappa: 0.9823, kb_relative_information_score: 0.9616, mean_absolute_error: 0.0219, mean_prior_absolute_error: 0.4939, weighted_recall: 0.9913, number_of_instances: 1372, precision: 0.9913, predictive_accuracy: 0.9913, prior_entropy: 0.9911, relative_absolute_error: 0.0443, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.0844, root_relative_squared_error: 0.1699, unweighted_recall: 0.9913,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... .tree.ExtraTreeClassifier))(2) on task Supervised Classification on data set banknote-authentication

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9862, f_measure: 0.9876, kappa: 0.9748, kb_relative_information_score: 0.9748, mean_absolute_error: 0.0124, mean_prior_absolute_error: 0.4939, weighted_recall: 0.9876, number_of_instances: 1372, precision: 0.9878, predictive_accuracy: 0.9876, prior_entropy: 0.9911, relative_absolute_error: 0.0251, root_mean_prior_squared_error: 0.4969, root_mean_squared_error: 0.1113, root_relative_squared_error: 0.224, unweighted_recall: 0.9862,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(pca= ... est.RandomForestClassifier)(4) on task Supervised Classification on data set kc2

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.784, f_measure: 0.7887, kappa: 0.3048, kb_relative_information_score: 0.1994, mean_absolute_error: 0.2346, mean_prior_absolute_error: 0.3266, weighted_recall: 0.8103, number_of_instances: 522, precision: 0.7856, predictive_accuracy: 0.8103, prior_entropy: 0.7318, relative_absolute_error: 0.7183, root_mean_prior_squared_error: 0.4037, root_mean_squared_error: 0.3637, root_relative_squared_error: 0.9008, unweighted_recall: 0.6276,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(2) on task Supervised Classification on data set wdbc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8708, f_measure: 0.7386, kappa: 0.4335, kb_relative_information_score: 0.337, mean_absolute_error: 0.3193, mean_prior_absolute_error: 0.4676, weighted_recall: 0.7592, number_of_instances: 569, precision: 0.7721, predictive_accuracy: 0.7592, prior_entropy: 0.9526, relative_absolute_error: 0.6829, root_mean_prior_squared_error: 0.4835, root_mean_squared_error: 0.3863, root_relative_squared_error: 0.7991, unweighted_recall: 0.697,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(pca= ... orest.ExtraTreesClassifier)(2) on task Supervised Classification on data set wdbc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9921, f_measure: 0.961, kappa: 0.9162, kb_relative_information_score: 0.6539, mean_absolute_error: 0.1883, mean_prior_absolute_error: 0.4676, weighted_recall: 0.9613, number_of_instances: 569, precision: 0.962, predictive_accuracy: 0.9613, prior_entropy: 0.9526, relative_absolute_error: 0.4026, root_mean_prior_squared_error: 0.4835, root_mean_squared_error: 0.2377, root_relative_squared_error: 0.4916, unweighted_recall: 0.9519,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(2) on task Supervised Classification on data set analcatdata_authorship

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8114, f_measure: 0.5804, kappa: 0.3922, kb_relative_information_score: 0.2925, mean_absolute_error: 0.2793, mean_prior_absolute_error: 0.3439, weighted_recall: 0.6017, number_of_instances: 841, precision: 0.6223, predictive_accuracy: 0.6017, prior_entropy: 1.7874, relative_absolute_error: 0.8122, root_mean_prior_squared_error: 0.4146, root_mean_squared_error: 0.3613, root_relative_squared_error: 0.8714, unweighted_recall: 0.4787,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... est.RandomForestClassifier)(3) on task Supervised Classification on data set qsar-biodeg

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8995, f_measure: 0.8421, kappa: 0.6402, kb_relative_information_score: 0.4858, mean_absolute_error: 0.2376, mean_prior_absolute_error: 0.4472, weighted_recall: 0.8464, number_of_instances: 1055, precision: 0.8454, predictive_accuracy: 0.8464, prior_entropy: 0.9223, relative_absolute_error: 0.5313, root_mean_prior_squared_error: 0.4728, root_mean_squared_error: 0.3388, root_relative_squared_error: 0.7166, unweighted_recall: 0.8056,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(2) on task Supervised Classification on data set qsar-biodeg

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7005, f_measure: 0.6366, kappa: 0.2431, kb_relative_information_score: -0.0265, mean_absolute_error: 0.4404, mean_prior_absolute_error: 0.4472, weighted_recall: 0.6265, number_of_instances: 1055, precision: 0.6714, predictive_accuracy: 0.6265, prior_entropy: 0.9223, relative_absolute_error: 0.9846, root_mean_prior_squared_error: 0.4728, root_mean_squared_error: 0.4848, root_relative_squared_error: 1.0253, unweighted_recall: 0.6341,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(3) on task Supervised Classification on data set qsar-biodeg

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9107, f_measure: 0.8492, kappa: 0.658, kb_relative_information_score: 0.5431, mean_absolute_error: 0.21, mean_prior_absolute_error: 0.4472, weighted_recall: 0.8521, number_of_instances: 1055, precision: 0.8504, predictive_accuracy: 0.8521, prior_entropy: 0.9223, relative_absolute_error: 0.4694, root_mean_prior_squared_error: 0.4728, root_mean_squared_error: 0.3262, root_relative_squared_error: 0.69, unweighted_recall: 0.8181,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... ree.DecisionTreeClassifier)(2) on task Supervised Classification on data set climate-model-simulation-crashes

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4715, kb_relative_information_score: 0.0047, mean_absolute_error: 0.1559, mean_prior_absolute_error: 0.1571, weighted_recall: 0.9148, number_of_instances: 540, predictive_accuracy: 0.9148, prior_entropy: 0.4202, relative_absolute_error: 0.992, root_mean_prior_squared_error: 0.2792, root_mean_squared_error: 0.2792, root_relative_squared_error: 1.0001, unweighted_recall: 0.5,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(pca= ... est.RandomForestClassifier)(4) on task Supervised Classification on data set wilt

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9767, f_measure: 0.984, kappa: 0.8391, kb_relative_information_score: 0.5658, mean_absolute_error: 0.0252, mean_prior_absolute_error: 0.1022, weighted_recall: 0.9845, number_of_instances: 4839, precision: 0.984, predictive_accuracy: 0.9845, prior_entropy: 0.3029, relative_absolute_error: 0.2466, root_mean_prior_squared_error: 0.2259, root_mean_squared_error: 0.1083, root_relative_squared_error: 0.4794, unweighted_recall: 0.8961,

Sergey Redyuk 3 years ago
ran flow sklearn.svm.classes.SVC(45) on task Supervised Classification on data set wall-robot-navigation

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.926, f_measure: 0.9049, kappa: 0.8559, kb_relative_information_score: 0.8619, mean_absolute_error: 0.0474, mean_prior_absolute_error: 0.3312, weighted_recall: 0.9052, number_of_instances: 5456, precision: 0.9054, predictive_accuracy: 0.9052, prior_entropy: 1.7146, relative_absolute_error: 0.143, root_mean_prior_squared_error: 0.4069, root_mean_squared_error: 0.2177, root_relative_squared_error: 0.5349, unweighted_recall: 0.8837,

Sergey Redyuk 3 years ago
ran flow sklearn.ensemble.gradient_boos ... GradientBoostingClassifier(25) on task Supervised Classification on data set PhishingWebsites

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9904, f_measure: 0.9488, kappa: 0.8962, kb_relative_information_score: 0.8345, mean_absolute_error: 0.089, mean_prior_absolute_error: 0.4935, weighted_recall: 0.9489, number_of_instances: 11055, precision: 0.9489, predictive_accuracy: 0.9489, prior_entropy: 0.9906, relative_absolute_error: 0.1803, root_mean_prior_squared_error: 0.4967, root_mean_squared_error: 0.1964, root_relative_squared_error: 0.3954, unweighted_recall: 0.9472,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(poly ... est.RandomForestClassifier)(2) on task Supervised Classification on data set balance-scale

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9817, f_measure: 0.9095, kappa: 0.8527, kb_relative_information_score: 0.6775, mean_absolute_error: 0.1385, mean_prior_absolute_error: 0.3798, weighted_recall: 0.9184, number_of_instances: 625, precision: 0.9122, predictive_accuracy: 0.9184, prior_entropy: 1.3181, relative_absolute_error: 0.3646, root_mean_prior_squared_error: 0.4356, root_mean_squared_error: 0.2276, root_relative_squared_error: 0.5226, unweighted_recall: 0.766,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(Medi ... arn.naive_bayes.GaussianNB)(2) on task Supervised Classification on data set balance-scale

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9721, kappa: 0.8279, kb_relative_information_score: 0.4844, mean_absolute_error: 0.2074, mean_prior_absolute_error: 0.3798, weighted_recall: 0.9072, number_of_instances: 625, predictive_accuracy: 0.9072, prior_entropy: 1.3181, relative_absolute_error: 0.546, root_mean_prior_squared_error: 0.4356, root_mean_squared_error: 0.2746, root_relative_squared_error: 0.6303, unweighted_recall: 0.6563,

Sergey Redyuk 3 years ago
ran flow sklearn.ensemble.voting_classi ... e.tree.ExtraTreeClassifier)(2) on task Supervised Classification on data set blood-transfusion-service-center

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5724, f_measure: 0.7185, kappa: 0.1728, kb_relative_information_score: 0.2189, mean_absolute_error: 0.2513, mean_prior_absolute_error: 0.363, weighted_recall: 0.7487, number_of_instances: 748, precision: 0.7099, predictive_accuracy: 0.7487, prior_entropy: 0.7916, relative_absolute_error: 0.6923, root_mean_prior_squared_error: 0.4258, root_mean_squared_error: 0.5013, root_relative_squared_error: 1.1773, unweighted_recall: 0.5724,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(7) on task Supervised Classification on data set blood-transfusion-service-center

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6554, f_measure: 0.7278, kappa: 0.2092, kb_relative_information_score: 0.0576, mean_absolute_error: 0.3093, mean_prior_absolute_error: 0.363, weighted_recall: 0.7487, number_of_instances: 748, precision: 0.7191, predictive_accuracy: 0.7487, prior_entropy: 0.7916, relative_absolute_error: 0.852, root_mean_prior_squared_error: 0.4258, root_mean_squared_error: 0.4407, root_relative_squared_error: 1.035, unweighted_recall: 0.5917,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... vc=sklearn.svm.classes.SVC)(8) on task Supervised Classification on data set wdbc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.995, f_measure: 0.9737, kappa: 0.9437, kb_relative_information_score: 0.908, mean_absolute_error: 0.0466, mean_prior_absolute_error: 0.4676, weighted_recall: 0.9736, number_of_instances: 569, precision: 0.9737, predictive_accuracy: 0.9736, prior_entropy: 0.9526, relative_absolute_error: 0.0997, root_mean_prior_squared_error: 0.4835, root_mean_squared_error: 0.143, root_relative_squared_error: 0.2958, unweighted_recall: 0.9723,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... ree.DecisionTreeClassifier)(2) on task Supervised Classification on data set wdbc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4933, kb_relative_information_score: 0.0002, mean_absolute_error: 0.4675, mean_prior_absolute_error: 0.4676, weighted_recall: 0.6274, number_of_instances: 569, predictive_accuracy: 0.6274, prior_entropy: 0.9526, relative_absolute_error: 0.9998, root_mean_prior_squared_error: 0.4835, root_mean_squared_error: 0.4835, root_relative_squared_error: 1, unweighted_recall: 0.5,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(2) on task Supervised Classification on data set wdbc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4912, kb_relative_information_score: 0.1771, mean_absolute_error: 0.3745, mean_prior_absolute_error: 0.4676, weighted_recall: 0.6274, number_of_instances: 569, predictive_accuracy: 0.6274, prior_entropy: 0.9526, relative_absolute_error: 0.8009, root_mean_prior_squared_error: 0.4835, root_mean_squared_error: 0.6075, root_relative_squared_error: 1.2565, unweighted_recall: 0.5,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(7) on task Supervised Classification on data set wdbc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9848, f_measure: 0.9558, kappa: 0.905, kb_relative_information_score: 0.8472, mean_absolute_error: 0.0772, mean_prior_absolute_error: 0.4676, weighted_recall: 0.9561, number_of_instances: 569, precision: 0.9563, predictive_accuracy: 0.9561, prior_entropy: 0.9526, relative_absolute_error: 0.165, root_mean_prior_squared_error: 0.4835, root_mean_squared_error: 0.1859, root_relative_squared_error: 0.3846, unweighted_recall: 0.9477,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(3) on task Supervised Classification on data set analcatdata_authorship

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9988, f_measure: 0.9774, kappa: 0.9671, kb_relative_information_score: 0.8654, mean_absolute_error: 0.0669, mean_prior_absolute_error: 0.3439, weighted_recall: 0.9774, number_of_instances: 841, precision: 0.9777, predictive_accuracy: 0.9774, prior_entropy: 1.7874, relative_absolute_error: 0.1947, root_mean_prior_squared_error: 0.4146, root_mean_squared_error: 0.1363, root_relative_squared_error: 0.3288, unweighted_recall: 0.9677,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... ree.DecisionTreeClassifier)(2) on task Supervised Classification on data set analcatdata_authorship

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4924, kb_relative_information_score: 0.0009, mean_absolute_error: 0.3437, mean_prior_absolute_error: 0.3439, weighted_recall: 0.3769, number_of_instances: 841, predictive_accuracy: 0.3769, prior_entropy: 1.7874, relative_absolute_error: 0.9996, root_mean_prior_squared_error: 0.4146, root_mean_squared_error: 0.4146, root_relative_squared_error: 1, unweighted_recall: 0.25,

Sergey Redyuk 3 years ago
ran flow sklearn.tree.tree.ExtraTreeClassifier(28) on task Supervised Classification on data set qsar-biodeg

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7871, f_measure: 0.805, kappa: 0.5669, kb_relative_information_score: 0.5404, mean_absolute_error: 0.1962, mean_prior_absolute_error: 0.4472, weighted_recall: 0.8038, number_of_instances: 1055, precision: 0.8067, predictive_accuracy: 0.8038, prior_entropy: 0.9223, relative_absolute_error: 0.4387, root_mean_prior_squared_error: 0.4728, root_mean_squared_error: 0.443, root_relative_squared_error: 0.9368, unweighted_recall: 0.7871,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(pca= ... est.RandomForestClassifier)(4) on task Supervised Classification on data set qsar-biodeg

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.898, f_measure: 0.8332, kappa: 0.6183, kb_relative_information_score: 0.4544, mean_absolute_error: 0.2549, mean_prior_absolute_error: 0.4472, weighted_recall: 0.8398, number_of_instances: 1055, precision: 0.841, predictive_accuracy: 0.8398, prior_entropy: 0.9223, relative_absolute_error: 0.5699, root_mean_prior_squared_error: 0.4728, root_mean_squared_error: 0.3415, root_relative_squared_error: 0.7223, unweighted_recall: 0.7902,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... vc=sklearn.svm.classes.SVC)(8) on task Supervised Classification on data set qsar-biodeg

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9296, f_measure: 0.8786, kappa: 0.7264, kb_relative_information_score: 0.6072, mean_absolute_error: 0.1847, mean_prior_absolute_error: 0.4472, weighted_recall: 0.8796, number_of_instances: 1055, precision: 0.8785, predictive_accuracy: 0.8796, prior_entropy: 0.9223, relative_absolute_error: 0.413, root_mean_prior_squared_error: 0.4728, root_mean_squared_error: 0.3016, root_relative_squared_error: 0.6377, unweighted_recall: 0.8575,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(poly ... est.RandomForestClassifier)(2) on task Supervised Classification on data set qsar-biodeg

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6567, f_measure: 0.6303, kappa: 0.2062, kb_relative_information_score: -0.0559, mean_absolute_error: 0.4518, mean_prior_absolute_error: 0.4472, weighted_recall: 0.6218, number_of_instances: 1055, precision: 0.6485, predictive_accuracy: 0.6218, prior_entropy: 0.9223, relative_absolute_error: 1.0101, root_mean_prior_squared_error: 0.4728, root_mean_squared_error: 0.4918, root_relative_squared_error: 1.0401, unweighted_recall: 0.6098,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... r_perceptron.MLPClassifier)(2) on task Supervised Classification on data set climate-model-simulation-crashes

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9349, f_measure: 0.9398, kappa: 0.5865, kb_relative_information_score: 0.4904, mean_absolute_error: 0.0571, mean_prior_absolute_error: 0.1571, weighted_recall: 0.9444, number_of_instances: 540, precision: 0.9391, predictive_accuracy: 0.9444, prior_entropy: 0.4202, relative_absolute_error: 0.3631, root_mean_prior_squared_error: 0.2792, root_mean_squared_error: 0.215, root_relative_squared_error: 0.7702, unweighted_recall: 0.7528,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(Medi ... arn.naive_bayes.GaussianNB)(2) on task Supervised Classification on data set climate-model-simulation-crashes

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.952, f_measure: 0.9369, kappa: 0.5427, kb_relative_information_score: 0.3701, mean_absolute_error: 0.0773, mean_prior_absolute_error: 0.1571, weighted_recall: 0.9463, number_of_instances: 540, precision: 0.9443, predictive_accuracy: 0.9463, prior_entropy: 0.4202, relative_absolute_error: 0.492, root_mean_prior_squared_error: 0.2792, root_mean_squared_error: 0.1967, root_relative_squared_error: 0.7048, unweighted_recall: 0.7045,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(3) on task Supervised Classification on data set climate-model-simulation-crashes

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8059, f_measure: 0.8818, kappa: 0.072, kb_relative_information_score: -0.2384, mean_absolute_error: 0.1274, mean_prior_absolute_error: 0.1571, weighted_recall: 0.9167, number_of_instances: 540, precision: 0.8966, predictive_accuracy: 0.9167, prior_entropy: 0.4202, relative_absolute_error: 0.8109, root_mean_prior_squared_error: 0.2792, root_mean_squared_error: 0.2575, root_relative_squared_error: 0.9223, unweighted_recall: 0.5207,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... ree.DecisionTreeClassifier)(3) on task Supervised Classification on data set wilt

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4981, kb_relative_information_score: 0.0008, mean_absolute_error: 0.1021, mean_prior_absolute_error: 0.1022, weighted_recall: 0.9461, number_of_instances: 4839, predictive_accuracy: 0.9461, prior_entropy: 0.3029, relative_absolute_error: 0.9984, root_mean_prior_squared_error: 0.2259, root_mean_squared_error: 0.2259, root_relative_squared_error: 1, unweighted_recall: 0.5,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(pca= ... est.RandomForestClassifier)(4) on task Supervised Classification on data set phoneme

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9402, f_measure: 0.8822, kappa: 0.7125, kb_relative_information_score: 0.599, mean_absolute_error: 0.1668, mean_prior_absolute_error: 0.4147, weighted_recall: 0.8838, number_of_instances: 5404, precision: 0.8819, predictive_accuracy: 0.8838, prior_entropy: 0.8732, relative_absolute_error: 0.4021, root_mean_prior_squared_error: 0.4554, root_mean_squared_error: 0.2894, root_relative_squared_error: 0.6355, unweighted_recall: 0.8472,

Sergey Redyuk 3 years ago
ran flow sklearn.ensemble.voting_classi ... e.tree.ExtraTreeClassifier)(2) on task Supervised Classification on data set phoneme

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8008, f_measure: 0.8608, kappa: 0.6534, kb_relative_information_score: 0.6561, mean_absolute_error: 0.1323, mean_prior_absolute_error: 0.4147, weighted_recall: 0.8677, number_of_instances: 5404, precision: 0.8686, predictive_accuracy: 0.8677, prior_entropy: 0.8732, relative_absolute_error: 0.319, root_mean_prior_squared_error: 0.4554, root_mean_squared_error: 0.3637, root_relative_squared_error: 0.7988, unweighted_recall: 0.8008,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... vc=sklearn.svm.classes.SVC)(8) on task Supervised Classification on data set phoneme

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9102, f_measure: 0.8407, kappa: 0.6118, kb_relative_information_score: 0.4884, mean_absolute_error: 0.2145, mean_prior_absolute_error: 0.4147, weighted_recall: 0.8425, number_of_instances: 5404, precision: 0.8397, predictive_accuracy: 0.8425, prior_entropy: 0.8732, relative_absolute_error: 0.5171, root_mean_prior_squared_error: 0.4554, root_mean_squared_error: 0.3295, root_relative_squared_error: 0.7237, unweighted_recall: 0.7992,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... est.RandomForestClassifier)(3) on task Supervised Classification on data set segment

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9901, f_measure: 0.9257, kappa: 0.9131, kb_relative_information_score: 0.8936, mean_absolute_error: 0.0399, mean_prior_absolute_error: 0.2449, weighted_recall: 0.9255, number_of_instances: 2310, precision: 0.9259, predictive_accuracy: 0.9255, prior_entropy: 2.8074, relative_absolute_error: 0.1631, root_mean_prior_squared_error: 0.3499, root_mean_squared_error: 0.1324, root_relative_squared_error: 0.3784, unweighted_recall: 0.9255,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(pca= ... est.RandomForestClassifier)(4) on task Supervised Classification on data set steel-plates-fault

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9029, f_measure: 0.7295, kappa: 0.6488, kb_relative_information_score: 0.6273, mean_absolute_error: 0.1113, mean_prior_absolute_error: 0.2223, weighted_recall: 0.7311, number_of_instances: 1941, precision: 0.7379, predictive_accuracy: 0.7311, prior_entropy: 2.4107, relative_absolute_error: 0.5007, root_mean_prior_squared_error: 0.3334, root_mean_squared_error: 0.2312, root_relative_squared_error: 0.6935, unweighted_recall: 0.721,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... ree.DecisionTreeClassifier)(3) on task Supervised Classification on data set steel-plates-fault

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4968, kb_relative_information_score: 0.0007, mean_absolute_error: 0.2223, mean_prior_absolute_error: 0.2223, weighted_recall: 0.3467, number_of_instances: 1941, predictive_accuracy: 0.3467, prior_entropy: 2.4107, relative_absolute_error: 0.9996, root_mean_prior_squared_error: 0.3334, root_mean_squared_error: 0.3334, root_relative_squared_error: 1, unweighted_recall: 0.1429,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(impu ... ree.DecisionTreeClassifier)(3) on task Supervised Classification on data set churn

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4983, kb_relative_information_score: 0.0003, mean_absolute_error: 0.2428, mean_prior_absolute_error: 0.2429, weighted_recall: 0.8586, number_of_instances: 5000, predictive_accuracy: 0.8586, prior_entropy: 0.5879, relative_absolute_error: 0.9996, root_mean_prior_squared_error: 0.3484, root_mean_squared_error: 0.3484, root_relative_squared_error: 1, unweighted_recall: 0.5,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(stan ... r_perceptron.MLPClassifier)(2) on task Supervised Classification on data set churn

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8901, f_measure: 0.9272, kappa: 0.692, kb_relative_information_score: 0.6117, mean_absolute_error: 0.0751, mean_prior_absolute_error: 0.2429, weighted_recall: 0.9292, number_of_instances: 5000, precision: 0.9263, predictive_accuracy: 0.9292, prior_entropy: 0.5879, relative_absolute_error: 0.3094, root_mean_prior_squared_error: 0.3484, root_mean_squared_error: 0.2496, root_relative_squared_error: 0.7164, unweighted_recall: 0.8276,

Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(pca= ... est.RandomForestClassifier)(4) on task Supervised Classification on data set churn

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8996, f_measure: 0.9156, kappa: 0.623, kb_relative_information_score: 0.338, mean_absolute_error: 0.1375, mean_prior_absolute_error: 0.2429, weighted_recall: 0.9242, number_of_instances: 5000, precision: 0.9223, predictive_accuracy: 0.9242, prior_entropy: 0.5879, relative_absolute_error: 0.5662, root_mean_prior_squared_error: 0.3484, root_mean_squared_error: 0.2471, root_relative_squared_error: 0.7093, unweighted_recall: 0.758,

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