OpenML

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set climate-model-simulation-crashes

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7687, f_measure: 0.9505, kappa: 0.6533, kb_relative_information_score: 327.0069, mean_absolute_error: 0.0444, mean_prior_absolute_error: 0.1571, number_of_instances: 540, precision: 0.9534, predictive_accuracy: 0.9556, prior_entropy: 0.4254, recall: 0.9556, relative_absolute_error: 0.2829, root_mean_prior_squared_error: 0.2792, root_mean_squared_error: 0.2108, root_relative_squared_error: 0.7552,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set madelon

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5962, f_measure: 0.596, kappa: 0.1923, kb_relative_information_score: 500, mean_absolute_error: 0.4038, mean_prior_absolute_error: 0.5, number_of_instances: 2600, precision: 0.5963, predictive_accuracy: 0.5962, prior_entropy: 1, recall: 0.5962, relative_absolute_error: 0.8077, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.6355, root_relative_squared_error: 1.271,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set vehicle

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9051, f_measure: 0.8585, kappa: 0.8108, kb_relative_information_score: 701.4509, mean_absolute_error: 0.0709, mean_prior_absolute_error: 0.3748, number_of_instances: 846, precision: 0.8589, predictive_accuracy: 0.8582, prior_entropy: 1.9991, recall: 0.8582, relative_absolute_error: 0.1892, root_mean_prior_squared_error: 0.4329, root_mean_squared_error: 0.2663, root_relative_squared_error: 0.6152,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set PhishingWebsites

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9698, f_measure: 0.9708, kappa: 0.9407, kb_relative_information_score: 10396.7114, mean_absolute_error: 0.0292, mean_prior_absolute_error: 0.4935, number_of_instances: 11055, precision: 0.9708, predictive_accuracy: 0.9708, prior_entropy: 0.9906, recall: 0.9708, relative_absolute_error: 0.0592, root_mean_prior_squared_error: 0.4967, root_mean_squared_error: 0.1709, root_relative_squared_error: 0.3441,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set cnae-9

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7807, f_measure: 0.6618, kappa: 0.5615, kb_relative_information_score: 636.4321, mean_absolute_error: 0.0866, mean_prior_absolute_error: 0.1975, number_of_instances: 1080, precision: 0.8583, predictive_accuracy: 0.6102, prior_entropy: 3.1699, recall: 0.6102, relative_absolute_error: 0.4385, root_mean_prior_squared_error: 0.3143, root_mean_squared_error: 0.2943, root_relative_squared_error: 0.9365,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set mfeat-morphological

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8558, f_measure: 0.7377, kappa: 0.7117, kb_relative_information_score: 1457.2519, mean_absolute_error: 0.0519, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.74, predictive_accuracy: 0.7405, prior_entropy: 3.3219, recall: 0.7405, relative_absolute_error: 0.2883, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2278, root_relative_squared_error: 0.7594,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set optdigits

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9941, f_measure: 0.9893, kappa: 0.9881, kb_relative_information_score: 5557.1949, mean_absolute_error: 0.0021, mean_prior_absolute_error: 0.18, number_of_instances: 5620, precision: 0.9894, predictive_accuracy: 0.9893, prior_entropy: 3.3218, recall: 0.9893, relative_absolute_error: 0.0119, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.0462, root_relative_squared_error: 0.154,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set jm1

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5613, f_measure: 0.7673, kappa: 0.1715, kb_relative_information_score: 3276.7969, mean_absolute_error: 0.1848, mean_prior_absolute_error: 0.3121, number_of_instances: 10885, precision: 0.7807, predictive_accuracy: 0.8152, prior_entropy: 0.7088, recall: 0.8152, relative_absolute_error: 0.5922, root_mean_prior_squared_error: 0.395, root_mean_squared_error: 0.4299, root_relative_squared_error: 1.0884,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set car

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9996, f_measure: 0.9994, kappa: 0.9987, kb_relative_information_score: 1718.116, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.229, number_of_instances: 1728, precision: 0.9994, predictive_accuracy: 0.9994, prior_entropy: 1.2099, recall: 0.9994, relative_absolute_error: 0.0013, root_mean_prior_squared_error: 0.3381, root_mean_squared_error: 0.017, root_relative_squared_error: 0.0503,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set analcatdata_authorship

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9963, f_measure: 0.9952, kappa: 0.9931, kb_relative_information_score: 834.1126, mean_absolute_error: 0.0024, mean_prior_absolute_error: 0.3439, number_of_instances: 841, precision: 0.9953, predictive_accuracy: 0.9952, prior_entropy: 1.7898, recall: 0.9952, relative_absolute_error: 0.0069, root_mean_prior_squared_error: 0.4146, root_mean_squared_error: 0.0488, root_relative_squared_error: 0.1176,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set splice

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9731, f_measure: 0.9656, kappa: 0.944, kb_relative_information_score: 3021.371, mean_absolute_error: 0.023, mean_prior_absolute_error: 0.4101, number_of_instances: 3190, precision: 0.9656, predictive_accuracy: 0.9655, prior_entropy: 1.4804, recall: 0.9655, relative_absolute_error: 0.0561, root_mean_prior_squared_error: 0.4528, root_mean_squared_error: 0.1516, root_relative_squared_error: 0.3349,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set car

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9996, f_measure: 0.9994, kappa: 0.9987, kb_relative_information_score: 1718.116, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.229, number_of_instances: 1728, precision: 0.9994, predictive_accuracy: 0.9994, prior_entropy: 1.2099, recall: 0.9994, relative_absolute_error: 0.0013, root_mean_prior_squared_error: 0.3381, root_mean_squared_error: 0.017, root_relative_squared_error: 0.0503,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set tic-tac-toe

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9985, f_measure: 0.999, kappa: 0.9977, kb_relative_information_score: 955.3995, mean_absolute_error: 0.001, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.999, predictive_accuracy: 0.999, prior_entropy: 0.9312, recall: 0.999, relative_absolute_error: 0.0023, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.0323, root_relative_squared_error: 0.0679,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set kc2

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6503, f_measure: 0.8147, kappa: 0.3813, kb_relative_information_score: 225.1239, mean_absolute_error: 0.159, mean_prior_absolute_error: 0.3266, number_of_instances: 522, precision: 0.8307, predictive_accuracy: 0.841, prior_entropy: 0.734, recall: 0.841, relative_absolute_error: 0.4869, root_mean_prior_squared_error: 0.4037, root_mean_squared_error: 0.3988, root_relative_squared_error: 0.9878,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set tic-tac-toe

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.991, f_measure: 0.9937, kappa: 0.9861, kb_relative_information_score: 943.8984, mean_absolute_error: 0.0063, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9938, predictive_accuracy: 0.9937, prior_entropy: 0.9312, recall: 0.9937, relative_absolute_error: 0.0138, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.0791, root_relative_squared_error: 0.1663,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set mfeat-factors

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9906, f_measure: 0.983, kappa: 0.9811, kb_relative_information_score: 1964.4442, mean_absolute_error: 0.0034, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.983, predictive_accuracy: 0.983, prior_entropy: 3.3219, recall: 0.983, relative_absolute_error: 0.0189, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.0583, root_relative_squared_error: 0.1944,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set analcatdata_dmft

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5292, f_measure: 0.2179, kappa: 0.059, kb_relative_information_score: 109.9018, mean_absolute_error: 0.2606, mean_prior_absolute_error: 0.2774, number_of_instances: 797, precision: 0.2213, predictive_accuracy: 0.2183, prior_entropy: 2.5803, recall: 0.2183, relative_absolute_error: 0.9393, root_mean_prior_squared_error: 0.3724, root_mean_squared_error: 0.5105, root_relative_squared_error: 1.3706,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set credit-approval

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8546, f_measure: 0.8526, kappa: 0.7032, kb_relative_information_score: 482.3691, mean_absolute_error: 0.1478, mean_prior_absolute_error: 0.494, number_of_instances: 690, precision: 0.8554, predictive_accuracy: 0.8522, prior_entropy: 0.9913, recall: 0.8522, relative_absolute_error: 0.2993, root_mean_prior_squared_error: 0.497, root_mean_squared_error: 0.3845, root_relative_squared_error: 0.7737,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set pc3

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5017, f_measure: 0.8495, kappa: 0.006, kb_relative_information_score: 385.6655, mean_absolute_error: 0.1043, mean_prior_absolute_error: 0.1842, number_of_instances: 1563, precision: 0.8265, predictive_accuracy: 0.8957, prior_entropy: 0.478, recall: 0.8957, relative_absolute_error: 0.5662, root_mean_prior_squared_error: 0.3031, root_mean_squared_error: 0.3229, root_relative_squared_error: 1.0653,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set mfeat-morphological

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8583, f_measure: 0.7425, kappa: 0.7167, kb_relative_information_score: 1466.6637, mean_absolute_error: 0.051, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7451, predictive_accuracy: 0.745, prior_entropy: 3.3219, recall: 0.745, relative_absolute_error: 0.2833, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2258, root_relative_squared_error: 0.7528,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set analcatdata_authorship

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9972, f_measure: 0.9964, kappa: 0.9948, kb_relative_information_score: 836.3556, mean_absolute_error: 0.0018, mean_prior_absolute_error: 0.3439, number_of_instances: 841, precision: 0.9964, predictive_accuracy: 0.9964, prior_entropy: 1.7898, recall: 0.9964, relative_absolute_error: 0.0052, root_mean_prior_squared_error: 0.4146, root_mean_squared_error: 0.0422, root_relative_squared_error: 0.1019,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set semeion

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9634, f_measure: 0.9348, kappa: 0.9268, kb_relative_information_score: 1483.2111, mean_absolute_error: 0.0132, mean_prior_absolute_error: 0.18, number_of_instances: 1593, precision: 0.9371, predictive_accuracy: 0.9341, prior_entropy: 3.3218, recall: 0.9341, relative_absolute_error: 0.0732, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1148, root_relative_squared_error: 0.3827,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set kc2

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6731, f_measure: 0.8137, kappa: 0.3955, kb_relative_information_score: 200.2176, mean_absolute_error: 0.1724, mean_prior_absolute_error: 0.3266, number_of_instances: 522, precision: 0.811, predictive_accuracy: 0.8276, prior_entropy: 0.734, recall: 0.8276, relative_absolute_error: 0.5279, root_mean_prior_squared_error: 0.4037, root_mean_squared_error: 0.4152, root_relative_squared_error: 1.0286,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set wilt

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9376, f_measure: 0.9878, kappa: 0.8799, kb_relative_information_score: 3993.7247, mean_absolute_error: 0.0122, mean_prior_absolute_error: 0.1022, number_of_instances: 4839, precision: 0.9877, predictive_accuracy: 0.9878, prior_entropy: 0.3037, recall: 0.9878, relative_absolute_error: 0.1193, root_mean_prior_squared_error: 0.2259, root_mean_squared_error: 0.1104, root_relative_squared_error: 0.4888,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set cnae-9

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9651, f_measure: 0.9387, kappa: 0.9302, kb_relative_information_score: 1009.4084, mean_absolute_error: 0.0138, mean_prior_absolute_error: 0.1975, number_of_instances: 1080, precision: 0.9402, predictive_accuracy: 0.938, prior_entropy: 3.1699, recall: 0.938, relative_absolute_error: 0.0698, root_mean_prior_squared_error: 0.3143, root_mean_squared_error: 0.1174, root_relative_squared_error: 0.3736,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set semeion

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9784, f_measure: 0.9611, kappa: 0.9568, kb_relative_information_score: 1528.0894, mean_absolute_error: 0.0078, mean_prior_absolute_error: 0.18, number_of_instances: 1593, precision: 0.9615, predictive_accuracy: 0.9611, prior_entropy: 3.3218, recall: 0.9611, relative_absolute_error: 0.0432, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.0882, root_relative_squared_error: 0.2941,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set car

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 1, kappa: 1, kb_relative_information_score: 1722.0583, mean_prior_absolute_error: 0.229, number_of_instances: 1728, precision: 1, predictive_accuracy: 1, prior_entropy: 1.2099, recall: 1, root_mean_prior_squared_error: 0.3381,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set churn

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.827, f_measure: 0.9323, kappa: 0.7102, kb_relative_information_score: 3322.0105, mean_absolute_error: 0.0648, mean_prior_absolute_error: 0.2429, number_of_instances: 5000, precision: 0.9321, predictive_accuracy: 0.9352, prior_entropy: 0.5883, recall: 0.9352, relative_absolute_error: 0.2668, root_mean_prior_squared_error: 0.3484, root_mean_squared_error: 0.2546, root_relative_squared_error: 0.7306,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set wdbc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9699, f_measure: 0.9753, kappa: 0.947, kb_relative_information_score: 538.0058, mean_absolute_error: 0.0246, mean_prior_absolute_error: 0.4676, number_of_instances: 569, precision: 0.9756, predictive_accuracy: 0.9754, prior_entropy: 0.953, recall: 0.9754, relative_absolute_error: 0.0526, root_mean_prior_squared_error: 0.4835, root_mean_squared_error: 0.1569, root_relative_squared_error: 0.3244,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set first-order-theorem-proving

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.5731, kappa: 0.4329, kb_relative_information_score: 2726.4303, mean_absolute_error: 0.1389, mean_prior_absolute_error: 0.2508, number_of_instances: 6118, precision: 0.5683, predictive_accuracy: 0.5832, prior_entropy: 2.3005, recall: 0.5832, relative_absolute_error: 0.554, root_mean_prior_squared_error: 0.3541, root_mean_squared_error: 0.3727, root_relative_squared_error: 1.0527,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set dna

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9724, f_measure: 0.9643, kappa: 0.9419, kb_relative_information_score: 3011.5748, mean_absolute_error: 0.0239, mean_prior_absolute_error: 0.41, number_of_instances: 3186, precision: 0.9644, predictive_accuracy: 0.9642, prior_entropy: 1.48, recall: 0.9642, relative_absolute_error: 0.0582, root_mean_prior_squared_error: 0.4527, root_mean_squared_error: 0.1544, root_relative_squared_error: 0.3412,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set analcatdata_authorship

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9963, f_measure: 0.9952, kappa: 0.9931, kb_relative_information_score: 834.1126, mean_absolute_error: 0.0024, mean_prior_absolute_error: 0.3439, number_of_instances: 841, precision: 0.9953, predictive_accuracy: 0.9952, prior_entropy: 1.7898, recall: 0.9952, relative_absolute_error: 0.0069, root_mean_prior_squared_error: 0.4146, root_mean_squared_error: 0.0488, root_relative_squared_error: 0.1176,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set madelon

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5962, f_measure: 0.596, kappa: 0.1923, kb_relative_information_score: 500, mean_absolute_error: 0.4038, mean_prior_absolute_error: 0.5, number_of_instances: 2600, precision: 0.5963, predictive_accuracy: 0.5962, prior_entropy: 1, recall: 0.5962, relative_absolute_error: 0.8077, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.6355, root_relative_squared_error: 1.271,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set splice

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9724, f_measure: 0.9655, kappa: 0.9439, kb_relative_information_score: 3019.8515, mean_absolute_error: 0.023, mean_prior_absolute_error: 0.4101, number_of_instances: 3190, precision: 0.9655, predictive_accuracy: 0.9655, prior_entropy: 1.4804, recall: 0.9655, relative_absolute_error: 0.0561, root_mean_prior_squared_error: 0.4528, root_mean_squared_error: 0.1516, root_relative_squared_error: 0.3349,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set balance-scale

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.997, f_measure: 0.9968, kappa: 0.9944, kb_relative_information_score: 617.8343, mean_absolute_error: 0.0021, mean_prior_absolute_error: 0.3798, number_of_instances: 625, precision: 0.9968, predictive_accuracy: 0.9968, prior_entropy: 1.3212, recall: 0.9968, relative_absolute_error: 0.0056, root_mean_prior_squared_error: 0.4356, root_mean_squared_error: 0.0462, root_relative_squared_error: 0.106,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set mfeat-pixel

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9897, f_measure: 0.9815, kappa: 0.9794, kb_relative_information_score: 1961.307, mean_absolute_error: 0.0037, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.9816, predictive_accuracy: 0.9815, prior_entropy: 3.3219, recall: 0.9815, relative_absolute_error: 0.0206, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.0608, root_relative_squared_error: 0.2028,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set wdbc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9685, f_measure: 0.9735, kappa: 0.9432, kb_relative_information_score: 535.8061, mean_absolute_error: 0.0264, mean_prior_absolute_error: 0.4676, number_of_instances: 569, precision: 0.9738, predictive_accuracy: 0.9736, prior_entropy: 0.953, recall: 0.9736, relative_absolute_error: 0.0564, root_mean_prior_squared_error: 0.4835, root_mean_squared_error: 0.1624, root_relative_squared_error: 0.3358,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set Australian

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8627, f_measure: 0.8584, kappa: 0.7161, kb_relative_information_score: 490.5101, mean_absolute_error: 0.142, mean_prior_absolute_error: 0.494, number_of_instances: 690, precision: 0.8646, predictive_accuracy: 0.858, prior_entropy: 0.9913, recall: 0.858, relative_absolute_error: 0.2875, root_mean_prior_squared_error: 0.497, root_mean_squared_error: 0.3769, root_relative_squared_error: 0.7583,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set steel-plates-fault

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8486, f_measure: 0.7731, kappa: 0.7085, kb_relative_information_score: 1442.7153, mean_absolute_error: 0.0648, mean_prior_absolute_error: 0.2223, number_of_instances: 1941, precision: 0.7739, predictive_accuracy: 0.7733, prior_entropy: 2.4138, recall: 0.7733, relative_absolute_error: 0.2913, root_mean_prior_squared_error: 0.3334, root_mean_squared_error: 0.2545, root_relative_squared_error: 0.7634,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set dresses-sales

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5353, f_measure: 0.5467, kappa: 0.075, kb_relative_information_score: 59.9624, mean_absolute_error: 0.424, mean_prior_absolute_error: 0.4873, number_of_instances: 500, precision: 0.556, predictive_accuracy: 0.576, prior_entropy: 0.9816, recall: 0.576, relative_absolute_error: 0.8702, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.6512, root_relative_squared_error: 1.3193,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set spambase

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9344, f_measure: 0.9394, kappa: 0.8729, kb_relative_information_score: 4007.0895, mean_absolute_error: 0.0604, mean_prior_absolute_error: 0.4776, number_of_instances: 4601, precision: 0.9395, predictive_accuracy: 0.9396, prior_entropy: 0.9674, recall: 0.9396, relative_absolute_error: 0.1265, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2458, root_relative_squared_error: 0.503,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set credit-approval

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8532, f_measure: 0.8497, kappa: 0.6984, kb_relative_information_score: 478.2986, mean_absolute_error: 0.1507, mean_prior_absolute_error: 0.494, number_of_instances: 690, precision: 0.8548, predictive_accuracy: 0.8493, prior_entropy: 0.9913, recall: 0.8493, relative_absolute_error: 0.3051, root_mean_prior_squared_error: 0.497, root_mean_squared_error: 0.3882, root_relative_squared_error: 0.7812,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set tic-tac-toe

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9925, f_measure: 0.9948, kappa: 0.9884, kb_relative_information_score: 946.1986, mean_absolute_error: 0.0052, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9948, predictive_accuracy: 0.9948, prior_entropy: 0.9312, recall: 0.9948, relative_absolute_error: 0.0115, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.0722, root_relative_squared_error: 0.1518,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set car

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 1, kappa: 1, kb_relative_information_score: 1722.0583, mean_prior_absolute_error: 0.229, number_of_instances: 1728, precision: 1, predictive_accuracy: 1, prior_entropy: 1.2099, recall: 1, root_mean_prior_squared_error: 0.3381,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set breast-w

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.966, f_measure: 0.9672, kappa: 0.9275, kb_relative_information_score: 645.6205, mean_absolute_error: 0.0329, mean_prior_absolute_error: 0.4519, number_of_instances: 699, precision: 0.9674, predictive_accuracy: 0.9671, prior_entropy: 0.9297, recall: 0.9671, relative_absolute_error: 0.0728, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1814, root_relative_squared_error: 0.3816,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set ozone-level-8hr

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6422, f_measure: 0.9366, kappa: 0.3872, kb_relative_information_score: 912.5738, mean_absolute_error: 0.0533, mean_prior_absolute_error: 0.1186, number_of_instances: 2534, precision: 0.9369, predictive_accuracy: 0.9467, prior_entropy: 0.3411, recall: 0.9467, relative_absolute_error: 0.4492, root_mean_prior_squared_error: 0.2432, root_mean_squared_error: 0.2308, root_relative_squared_error: 0.949,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set Bioresponse

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7816, f_measure: 0.784, kappa: 0.5645, kb_relative_information_score: 2116.1992, mean_absolute_error: 0.2157, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.784, predictive_accuracy: 0.7843, prior_entropy: 0.9948, recall: 0.7843, relative_absolute_error: 0.4345, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4644, root_relative_squared_error: 0.9322,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set dresses-sales

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5466, f_measure: 0.5512, kappa: 0.1011, kb_relative_information_score: 80.7154, mean_absolute_error: 0.404, mean_prior_absolute_error: 0.4873, number_of_instances: 500, precision: 0.5808, predictive_accuracy: 0.596, prior_entropy: 0.9816, recall: 0.596, relative_absolute_error: 0.8291, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.6356, root_relative_squared_error: 1.2878,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set Bioresponse

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7771, f_measure: 0.7801, kappa: 0.5564, kb_relative_information_score: 2087.9088, mean_absolute_error: 0.2194, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.7803, predictive_accuracy: 0.7806, prior_entropy: 0.9948, recall: 0.7806, relative_absolute_error: 0.442, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4684, root_relative_squared_error: 0.9402,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set blood-transfusion-service-center

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.624, f_measure: 0.7604, kappa: 0.296, kb_relative_information_score: 250.3717, mean_absolute_error: 0.2139, mean_prior_absolute_error: 0.363, number_of_instances: 748, precision: 0.7616, predictive_accuracy: 0.7861, prior_entropy: 0.7928, recall: 0.7861, relative_absolute_error: 0.5892, root_mean_prior_squared_error: 0.4258, root_mean_squared_error: 0.4625, root_relative_squared_error: 1.0861,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set spambase

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9359, f_measure: 0.9411, kappa: 0.8764, kb_relative_information_score: 4024.1765, mean_absolute_error: 0.0587, mean_prior_absolute_error: 0.4776, number_of_instances: 4601, precision: 0.9413, predictive_accuracy: 0.9413, prior_entropy: 0.9674, recall: 0.9413, relative_absolute_error: 0.1229, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2422, root_relative_squared_error: 0.4957,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set pc1

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5796, f_measure: 0.9161, kappa: 0.2356, kb_relative_information_score: 305.7153, mean_absolute_error: 0.0667, mean_prior_absolute_error: 0.1299, number_of_instances: 1109, precision: 0.915, predictive_accuracy: 0.9333, prior_entropy: 0.3667, recall: 0.9333, relative_absolute_error: 0.5137, root_mean_prior_squared_error: 0.2542, root_mean_squared_error: 0.2583, root_relative_squared_error: 1.0162,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set splice

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9734, f_measure: 0.9662, kappa: 0.945, kb_relative_information_score: 3023.7713, mean_absolute_error: 0.0226, mean_prior_absolute_error: 0.4101, number_of_instances: 3190, precision: 0.9662, predictive_accuracy: 0.9661, prior_entropy: 1.4804, recall: 0.9661, relative_absolute_error: 0.055, root_mean_prior_squared_error: 0.4528, root_mean_squared_error: 0.1502, root_relative_squared_error: 0.3318,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set pc3

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5096, f_measure: 0.8526, kappa: 0.0327, kb_relative_information_score: 378.4745, mean_absolute_error: 0.1049, mean_prior_absolute_error: 0.1842, number_of_instances: 1563, precision: 0.8415, predictive_accuracy: 0.8951, prior_entropy: 0.478, recall: 0.8951, relative_absolute_error: 0.5697, root_mean_prior_squared_error: 0.3031, root_mean_squared_error: 0.3239, root_relative_squared_error: 1.0686,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set wall-robot-navigation

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9404, f_measure: 0.9229, kappa: 0.8835, kb_relative_information_score: 4860.6723, mean_absolute_error: 0.0385, mean_prior_absolute_error: 0.3312, number_of_instances: 5456, precision: 0.923, predictive_accuracy: 0.923, prior_entropy: 1.7151, recall: 0.923, relative_absolute_error: 0.1162, root_mean_prior_squared_error: 0.4069, root_mean_squared_error: 0.1962, root_relative_squared_error: 0.4821,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set phoneme

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8635, f_measure: 0.8928, kappa: 0.7395, kb_relative_information_score: 3911.5923, mean_absolute_error: 0.1062, mean_prior_absolute_error: 0.4147, number_of_instances: 5404, precision: 0.8925, predictive_accuracy: 0.8938, prior_entropy: 0.8733, recall: 0.8938, relative_absolute_error: 0.2561, root_mean_prior_squared_error: 0.4554, root_mean_squared_error: 0.3259, root_relative_squared_error: 0.7157,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set balance-scale

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.997, f_measure: 0.9968, kappa: 0.9944, kb_relative_information_score: 617.8343, mean_absolute_error: 0.0021, mean_prior_absolute_error: 0.3798, number_of_instances: 625, precision: 0.9968, predictive_accuracy: 0.9968, prior_entropy: 1.3212, recall: 0.9968, relative_absolute_error: 0.0056, root_mean_prior_squared_error: 0.4356, root_mean_squared_error: 0.0462, root_relative_squared_error: 0.106,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set PhishingWebsites

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9734, f_measure: 0.9744, kappa: 0.9481, kb_relative_information_score: 10478.2285, mean_absolute_error: 0.0256, mean_prior_absolute_error: 0.4935, number_of_instances: 11055, precision: 0.9744, predictive_accuracy: 0.9744, prior_entropy: 0.9906, recall: 0.9744, relative_absolute_error: 0.0519, root_mean_prior_squared_error: 0.4967, root_mean_squared_error: 0.16, root_relative_squared_error: 0.3221,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set segment

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9533, f_measure: 0.9198, kappa: 0.9066, kb_relative_information_score: 2110.3447, mean_absolute_error: 0.0229, mean_prior_absolute_error: 0.2449, number_of_instances: 2310, precision: 0.9207, predictive_accuracy: 0.9199, prior_entropy: 2.8074, recall: 0.9199, relative_absolute_error: 0.0934, root_mean_prior_squared_error: 0.3499, root_mean_squared_error: 0.1513, root_relative_squared_error: 0.4323,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set satimage

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9552, f_measure: 0.9254, kappa: 0.9091, kb_relative_information_score: 5855.2699, mean_absolute_error: 0.0245, mean_prior_absolute_error: 0.2701, number_of_instances: 6430, precision: 0.9253, predictive_accuracy: 0.9264, prior_entropy: 2.4836, recall: 0.9264, relative_absolute_error: 0.0908, root_mean_prior_squared_error: 0.3675, root_mean_squared_error: 0.1566, root_relative_squared_error: 0.4261,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set Bioresponse

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7814, f_measure: 0.784, kappa: 0.5643, kb_relative_information_score: 2116.1992, mean_absolute_error: 0.2157, mean_prior_absolute_error: 0.4964, number_of_instances: 3751, precision: 0.784, predictive_accuracy: 0.7843, prior_entropy: 0.9948, recall: 0.7843, relative_absolute_error: 0.4345, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4644, root_relative_squared_error: 0.9322,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set analcatdata_authorship

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9953, f_measure: 0.9941, kappa: 0.9913, kb_relative_information_score: 832.9207, mean_absolute_error: 0.003, mean_prior_absolute_error: 0.3439, number_of_instances: 841, precision: 0.9941, predictive_accuracy: 0.9941, prior_entropy: 1.7898, recall: 0.9941, relative_absolute_error: 0.0086, root_mean_prior_squared_error: 0.4146, root_mean_squared_error: 0.0545, root_relative_squared_error: 0.1315,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set churn

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.827, f_measure: 0.9323, kappa: 0.7102, kb_relative_information_score: 3322.0105, mean_absolute_error: 0.0648, mean_prior_absolute_error: 0.2429, number_of_instances: 5000, precision: 0.9321, predictive_accuracy: 0.9352, prior_entropy: 0.5883, recall: 0.9352, relative_absolute_error: 0.2668, root_mean_prior_squared_error: 0.3484, root_mean_squared_error: 0.2546, root_relative_squared_error: 0.7306,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set cnae-9

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9646, f_measure: 0.9371, kappa: 0.9292, kb_relative_information_score: 1008.3548, mean_absolute_error: 0.014, mean_prior_absolute_error: 0.1975, number_of_instances: 1080, precision: 0.9372, predictive_accuracy: 0.937, prior_entropy: 3.1699, recall: 0.937, relative_absolute_error: 0.0708, root_mean_prior_squared_error: 0.3143, root_mean_squared_error: 0.1183, root_relative_squared_error: 0.3764,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set tic-tac-toe

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 1, kappa: 1, kb_relative_information_score: 957.6998, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 1, predictive_accuracy: 1, prior_entropy: 0.9312, recall: 1, root_mean_prior_squared_error: 0.4759,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set kc2

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6606, f_measure: 0.8148, kappa: 0.3885, kb_relative_information_score: 214.4497, mean_absolute_error: 0.1648, mean_prior_absolute_error: 0.3266, number_of_instances: 522, precision: 0.819, predictive_accuracy: 0.8352, prior_entropy: 0.734, recall: 0.8352, relative_absolute_error: 0.5045, root_mean_prior_squared_error: 0.4037, root_mean_squared_error: 0.4059, root_relative_squared_error: 1.0055,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set optdigits

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.994, f_measure: 0.9892, kappa: 0.9879, kb_relative_information_score: 5556.1956, mean_absolute_error: 0.0022, mean_prior_absolute_error: 0.18, number_of_instances: 5620, precision: 0.9892, predictive_accuracy: 0.9891, prior_entropy: 3.3218, recall: 0.9891, relative_absolute_error: 0.0121, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.0466, root_relative_squared_error: 0.1553,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set mfeat-morphological

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8569, f_measure: 0.7403, kappa: 0.7139, kb_relative_information_score: 1461.4349, mean_absolute_error: 0.0515, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7429, predictive_accuracy: 0.7425, prior_entropy: 3.3219, recall: 0.7425, relative_absolute_error: 0.2861, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2269, root_relative_squared_error: 0.7565,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set vehicle

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9051, f_measure: 0.8585, kappa: 0.8108, kb_relative_information_score: 701.4509, mean_absolute_error: 0.0709, mean_prior_absolute_error: 0.3748, number_of_instances: 846, precision: 0.8589, predictive_accuracy: 0.8582, prior_entropy: 1.9991, recall: 0.8582, relative_absolute_error: 0.1892, root_mean_prior_squared_error: 0.4329, root_mean_squared_error: 0.2663, root_relative_squared_error: 0.6152,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set car

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9996, f_measure: 0.9994, kappa: 0.9987, kb_relative_information_score: 1718.116, mean_absolute_error: 0.0003, mean_prior_absolute_error: 0.229, number_of_instances: 1728, precision: 0.9994, predictive_accuracy: 0.9994, prior_entropy: 1.2099, recall: 0.9994, relative_absolute_error: 0.0013, root_mean_prior_squared_error: 0.3381, root_mean_squared_error: 0.017, root_relative_squared_error: 0.0503,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set mfeat-morphological

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8567, f_measure: 0.74, kappa: 0.7133, kb_relative_information_score: 1460.3891, mean_absolute_error: 0.0516, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7422, predictive_accuracy: 0.742, prior_entropy: 3.3219, recall: 0.742, relative_absolute_error: 0.2867, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2272, root_relative_squared_error: 0.7572,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set analcatdata_dmft

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5211, f_measure: 0.1932, kappa: 0.0427, kb_relative_information_score: 100.9218, mean_absolute_error: 0.2627, mean_prior_absolute_error: 0.2774, number_of_instances: 797, precision: 0.2111, predictive_accuracy: 0.212, prior_entropy: 2.5803, recall: 0.212, relative_absolute_error: 0.9468, root_mean_prior_squared_error: 0.3724, root_mean_squared_error: 0.5125, root_relative_squared_error: 1.3761,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set vehicle

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9083, f_measure: 0.8632, kappa: 0.8171, kb_relative_information_score: 706.3646, mean_absolute_error: 0.0686, mean_prior_absolute_error: 0.3748, number_of_instances: 846, precision: 0.8635, predictive_accuracy: 0.8629, prior_entropy: 1.9991, recall: 0.8629, relative_absolute_error: 0.1829, root_mean_prior_squared_error: 0.4329, root_mean_squared_error: 0.2618, root_relative_squared_error: 0.6048,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set wall-robot-navigation

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9454, f_measure: 0.9295, kappa: 0.8933, kb_relative_information_score: 4916.8195, mean_absolute_error: 0.0353, mean_prior_absolute_error: 0.3312, number_of_instances: 5456, precision: 0.9296, predictive_accuracy: 0.9294, prior_entropy: 1.7151, recall: 0.9294, relative_absolute_error: 0.1065, root_mean_prior_squared_error: 0.4069, root_mean_squared_error: 0.1878, root_relative_squared_error: 0.4616,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set mfeat-zernike

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9108, f_measure: 0.8373, kappa: 0.8217, kb_relative_information_score: 1664.3118, mean_absolute_error: 0.0321, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.8359, predictive_accuracy: 0.8395, prior_entropy: 3.3219, recall: 0.8395, relative_absolute_error: 0.1783, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1792, root_relative_squared_error: 0.5972,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set pc4

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6889, f_measure: 0.8962, kappa: 0.4684, kb_relative_information_score: 651.042, mean_absolute_error: 0.0919, mean_prior_absolute_error: 0.2148, number_of_instances: 1458, precision: 0.8973, predictive_accuracy: 0.9081, prior_entropy: 0.5368, recall: 0.9081, relative_absolute_error: 0.428, root_mean_prior_squared_error: 0.3274, root_mean_squared_error: 0.3032, root_relative_squared_error: 0.926,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set tic-tac-toe

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 1, kappa: 1, kb_relative_information_score: 957.6998, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 1, predictive_accuracy: 1, prior_entropy: 0.9312, recall: 1, root_mean_prior_squared_error: 0.4759,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set steel-plates-fault

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8466, f_measure: 0.7729, kappa: 0.7069, kb_relative_information_score: 1434.2593, mean_absolute_error: 0.0648, mean_prior_absolute_error: 0.2223, number_of_instances: 1941, precision: 0.7744, predictive_accuracy: 0.7733, prior_entropy: 2.4138, recall: 0.7733, relative_absolute_error: 0.2913, root_mean_prior_squared_error: 0.3334, root_mean_squared_error: 0.2545, root_relative_squared_error: 0.7634,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set wilt

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9261, f_measure: 0.9865, kappa: 0.8662, kb_relative_information_score: 3908.9972, mean_absolute_error: 0.0134, mean_prior_absolute_error: 0.1022, number_of_instances: 4839, precision: 0.9864, predictive_accuracy: 0.9866, prior_entropy: 0.3037, recall: 0.9866, relative_absolute_error: 0.1314, root_mean_prior_squared_error: 0.2259, root_mean_squared_error: 0.1159, root_relative_squared_error: 0.5131,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set mfeat-morphological

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8564, f_measure: 0.7383, kappa: 0.7128, kb_relative_information_score: 1459.3434, mean_absolute_error: 0.0517, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7412, predictive_accuracy: 0.7415, prior_entropy: 3.3219, recall: 0.7415, relative_absolute_error: 0.2872, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2274, root_relative_squared_error: 0.7579,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set mfeat-morphological

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8603, f_measure: 0.7465, kappa: 0.7206, kb_relative_information_score: 1473.984, mean_absolute_error: 0.0503, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7488, predictive_accuracy: 0.7485, prior_entropy: 3.3219, recall: 0.7485, relative_absolute_error: 0.2794, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2243, root_relative_squared_error: 0.7476,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set cmc

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6443, f_measure: 0.5398, kappa: 0.2867, kb_relative_information_score: 501.4198, mean_absolute_error: 0.3064, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.5403, predictive_accuracy: 0.5404, prior_entropy: 1.5392, recall: 0.5404, relative_absolute_error: 0.7112, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.5535, root_relative_squared_error: 1.1927,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set vehicle

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9083, f_measure: 0.8632, kappa: 0.8171, kb_relative_information_score: 706.3757, mean_absolute_error: 0.0686, mean_prior_absolute_error: 0.3748, number_of_instances: 846, precision: 0.8636, predictive_accuracy: 0.8629, prior_entropy: 1.9991, recall: 0.8629, relative_absolute_error: 0.1829, root_mean_prior_squared_error: 0.4329, root_mean_squared_error: 0.2618, root_relative_squared_error: 0.6048,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set splice

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9169, f_measure: 0.9167, kappa: 0.8618, kb_relative_information_score: 2757.7233, mean_absolute_error: 0.0548, mean_prior_absolute_error: 0.4101, number_of_instances: 3190, precision: 0.9264, predictive_accuracy: 0.9179, prior_entropy: 1.4804, recall: 0.9179, relative_absolute_error: 0.1335, root_mean_prior_squared_error: 0.4528, root_mean_squared_error: 0.234, root_relative_squared_error: 0.5168,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set first-order-theorem-proving

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7169, f_measure: 0.5663, kappa: 0.4242, kb_relative_information_score: 2693.1722, mean_absolute_error: 0.1388, mean_prior_absolute_error: 0.2508, number_of_instances: 6118, precision: 0.5618, predictive_accuracy: 0.5835, prior_entropy: 2.3005, recall: 0.5835, relative_absolute_error: 0.5536, root_mean_prior_squared_error: 0.3541, root_mean_squared_error: 0.3726, root_relative_squared_error: 1.0523,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set steel-plates-fault

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.85, f_measure: 0.7789, kappa: 0.7141, kb_relative_information_score: 1447.3819, mean_absolute_error: 0.0631, mean_prior_absolute_error: 0.2223, number_of_instances: 1941, precision: 0.7805, predictive_accuracy: 0.779, prior_entropy: 2.4138, recall: 0.779, relative_absolute_error: 0.284, root_mean_prior_squared_error: 0.3334, root_mean_squared_error: 0.2513, root_relative_squared_error: 0.7538,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set first-order-theorem-proving

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7207, f_measure: 0.5698, kappa: 0.4295, kb_relative_information_score: 2710.3477, mean_absolute_error: 0.1381, mean_prior_absolute_error: 0.2508, number_of_instances: 6118, precision: 0.5657, predictive_accuracy: 0.5856, prior_entropy: 2.3005, recall: 0.5856, relative_absolute_error: 0.5508, root_mean_prior_squared_error: 0.3541, root_mean_squared_error: 0.3716, root_relative_squared_error: 1.0496,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set vehicle

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.906, f_measure: 0.8596, kappa: 0.8124, kb_relative_information_score: 702.7925, mean_absolute_error: 0.0703, mean_prior_absolute_error: 0.3748, number_of_instances: 846, precision: 0.8602, predictive_accuracy: 0.8593, prior_entropy: 1.9991, recall: 0.8593, relative_absolute_error: 0.1876, root_mean_prior_squared_error: 0.4329, root_mean_squared_error: 0.2652, root_relative_squared_error: 0.6126,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set phoneme

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8119, f_measure: 0.8422, kappa: 0.6205, kb_relative_information_score: 3181.2818, mean_absolute_error: 0.1582, mean_prior_absolute_error: 0.4147, number_of_instances: 5404, precision: 0.8427, predictive_accuracy: 0.8418, prior_entropy: 0.8733, recall: 0.8418, relative_absolute_error: 0.3815, root_mean_prior_squared_error: 0.4554, root_mean_squared_error: 0.3978, root_relative_squared_error: 0.8735,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set vehicle

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9068, f_measure: 0.8607, kappa: 0.814, kb_relative_information_score: 703.9751, mean_absolute_error: 0.0697, mean_prior_absolute_error: 0.3748, number_of_instances: 846, precision: 0.8612, predictive_accuracy: 0.8605, prior_entropy: 1.9991, recall: 0.8605, relative_absolute_error: 0.1861, root_mean_prior_squared_error: 0.4329, root_mean_squared_error: 0.2641, root_relative_squared_error: 0.61,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set mfeat-pixel

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.99, f_measure: 0.982, kappa: 0.98, kb_relative_information_score: 1962.3527, mean_absolute_error: 0.0036, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.9821, predictive_accuracy: 0.982, prior_entropy: 3.3219, recall: 0.982, relative_absolute_error: 0.02, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.06, root_relative_squared_error: 0.2,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set cnae-9

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9396, f_measure: 0.8971, kappa: 0.8792, kb_relative_information_score: 957.7818, mean_absolute_error: 0.0239, mean_prior_absolute_error: 0.1975, number_of_instances: 1080, precision: 0.9098, predictive_accuracy: 0.8926, prior_entropy: 3.1699, recall: 0.8926, relative_absolute_error: 0.1208, root_mean_prior_squared_error: 0.3143, root_mean_squared_error: 0.1545, root_relative_squared_error: 0.4916,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set mfeat-morphological

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8567, f_measure: 0.7396, kappa: 0.7133, kb_relative_information_score: 1460.3891, mean_absolute_error: 0.0516, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7417, predictive_accuracy: 0.742, prior_entropy: 3.3219, recall: 0.742, relative_absolute_error: 0.2867, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2272, root_relative_squared_error: 0.7572,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set tic-tac-toe

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9985, f_measure: 0.999, kappa: 0.9977, kb_relative_information_score: 955.3995, mean_absolute_error: 0.001, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.999, predictive_accuracy: 0.999, prior_entropy: 0.9312, recall: 0.999, relative_absolute_error: 0.0023, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.0323, root_relative_squared_error: 0.0679,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set tic-tac-toe

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9925, f_measure: 0.9948, kappa: 0.9884, kb_relative_information_score: 946.1986, mean_absolute_error: 0.0052, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9948, predictive_accuracy: 0.9948, prior_entropy: 0.9312, recall: 0.9948, relative_absolute_error: 0.0115, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.0722, root_relative_squared_error: 0.1518,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set jm1

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5518, f_measure: 0.7612, kappa: 0.1479, kb_relative_information_score: 3212.528, mean_absolute_error: 0.1864, mean_prior_absolute_error: 0.3121, number_of_instances: 10885, precision: 0.7774, predictive_accuracy: 0.8136, prior_entropy: 0.7088, recall: 0.8136, relative_absolute_error: 0.5972, root_mean_prior_squared_error: 0.395, root_mean_squared_error: 0.4317, root_relative_squared_error: 1.093,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set sick

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8338, f_measure: 0.9679, kappa: 0.7122, kb_relative_information_score: 2316.8423, mean_absolute_error: 0.031, mean_prior_absolute_error: 0.1152, number_of_instances: 3772, precision: 0.9674, predictive_accuracy: 0.969, prior_entropy: 0.3333, recall: 0.969, relative_absolute_error: 0.2693, root_mean_prior_squared_error: 0.2398, root_mean_squared_error: 0.1761, root_relative_squared_error: 0.7345,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set tic-tac-toe

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 1, kappa: 1, kb_relative_information_score: 957.6998, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 1, predictive_accuracy: 1, prior_entropy: 0.9312, recall: 1, root_mean_prior_squared_error: 0.4759,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set cnae-9

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9688, f_measure: 0.9449, kappa: 0.9375, kb_relative_information_score: 1016.7837, mean_absolute_error: 0.0123, mean_prior_absolute_error: 0.1975, number_of_instances: 1080, precision: 0.9458, predictive_accuracy: 0.9444, prior_entropy: 3.1699, recall: 0.9444, relative_absolute_error: 0.0625, root_mean_prior_squared_error: 0.3143, root_mean_squared_error: 0.1111, root_relative_squared_error: 0.3536,

Hilde Weerts 7 years ago
ran flow sklearn.model_selection._searc ... f=sklearn.svm.classes.SVC))(1) on task Supervised Classification on data set cnae-9

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9635, f_measure: 0.9356, kappa: 0.9271, kb_relative_information_score: 1006.2476, mean_absolute_error: 0.0144, mean_prior_absolute_error: 0.1975, number_of_instances: 1080, precision: 0.9367, predictive_accuracy: 0.9352, prior_entropy: 3.1699, recall: 0.9352, relative_absolute_error: 0.0729, root_mean_prior_squared_error: 0.3143, root_mean_squared_error: 0.12, root_relative_squared_error: 0.3819,

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