OpenML
Nicolas Hug
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Nicolas's runs

Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set cnae-9
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9919, f_measure: 0.9159, kappa: 0.9052, kb_relative_information_score: 0.8472, mean_absolute_error: 0.0536, mean_prior_absolute_error: 0.1975, weighted_recall: 0.9157, number_of_instances: 1080, precision: 0.9176, predictive_accuracy: 0.9157, prior_entropy: 3.1699, relative_absolute_error: 0.2715, root_mean_prior_squared_error: 0.3143, root_mean_squared_error: 0.1298, root_relative_squared_error: 0.4131, unweighted_recall: 0.9157,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set cnae-9
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.991, f_measure: 0.9079, kappa: 0.8958, kb_relative_information_score: 0.8627, mean_absolute_error: 0.0406, mean_prior_absolute_error: 0.1975, weighted_recall: 0.9074, number_of_instances: 1080, precision: 0.9098, predictive_accuracy: 0.9074, prior_entropy: 3.1699, relative_absolute_error: 0.2055, root_mean_prior_squared_error: 0.3143, root_mean_squared_error: 0.1275, root_relative_squared_error: 0.4056, unweighted_recall: 0.9074,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =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: 0.9065, f_measure: 0.9177, kappa: 0.1594, kb_relative_information_score: -0.2382, mean_absolute_error: 0.0934, mean_prior_absolute_error: 0.1186, weighted_recall: 0.9376, number_of_instances: 2534, precision: 0.9169, predictive_accuracy: 0.9376, prior_entropy: 0.3398, relative_absolute_error: 0.7878, root_mean_prior_squared_error: 0.2432, root_mean_squared_error: 0.2133, root_relative_squared_error: 0.877, unweighted_recall: 0.55,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set ozone-level-8hr
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9014, f_measure: 0.9152, kappa: 0.1256, kb_relative_information_score: -0.2693, mean_absolute_error: 0.0959, mean_prior_absolute_error: 0.1186, weighted_recall: 0.9373, number_of_instances: 2534, precision: 0.9148, predictive_accuracy: 0.9373, prior_entropy: 0.3398, relative_absolute_error: 0.8088, root_mean_prior_squared_error: 0.2432, root_mean_squared_error: 0.2151, root_relative_squared_error: 0.8845, unweighted_recall: 0.5381,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set nomao
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9876, f_measure: 0.9491, kappa: 0.8753, kb_relative_information_score: 0.8192, mean_absolute_error: 0.0753, mean_prior_absolute_error: 0.4081, weighted_recall: 0.9492, number_of_instances: 34465, precision: 0.9491, predictive_accuracy: 0.9492, prior_entropy: 0.863, relative_absolute_error: 0.1845, root_mean_prior_squared_error: 0.4517, root_mean_squared_error: 0.1926, root_relative_squared_error: 0.4264, unweighted_recall: 0.9371,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set nomao
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9876, f_measure: 0.9491, kappa: 0.8751, kb_relative_information_score: 0.8202, mean_absolute_error: 0.0747, mean_prior_absolute_error: 0.4081, weighted_recall: 0.9491, number_of_instances: 34465, precision: 0.949, predictive_accuracy: 0.9491, prior_entropy: 0.863, relative_absolute_error: 0.1831, root_mean_prior_squared_error: 0.4517, root_mean_squared_error: 0.1928, root_relative_squared_error: 0.4269, unweighted_recall: 0.9373,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =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: 0.8713, f_measure: 0.7296, kappa: 0.5887, kb_relative_information_score: 0.4884, mean_absolute_error: 0.2112, mean_prior_absolute_error: 0.3312, weighted_recall: 0.7322, number_of_instances: 5456, precision: 0.7376, predictive_accuracy: 0.7322, prior_entropy: 1.7146, relative_absolute_error: 0.6375, root_mean_prior_squared_error: 0.4069, root_mean_squared_error: 0.3175, root_relative_squared_error: 0.7803, unweighted_recall: 0.68,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set wall-robot-navigation
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8948, f_measure: 0.7303, kappa: 0.5895, kb_relative_information_score: 0.5166, mean_absolute_error: 0.1964, mean_prior_absolute_error: 0.3312, weighted_recall: 0.7337, number_of_instances: 5456, precision: 0.7406, predictive_accuracy: 0.7337, prior_entropy: 1.7146, relative_absolute_error: 0.593, root_mean_prior_squared_error: 0.4069, root_mean_squared_error: 0.3048, root_relative_squared_error: 0.7491, unweighted_recall: 0.6714,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set qsar-biodeg
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9269, f_measure: 0.8731, kappa: 0.7147, kb_relative_information_score: 0.545, mean_absolute_error: 0.2142, mean_prior_absolute_error: 0.4472, weighted_recall: 0.8739, number_of_instances: 1055, precision: 0.8729, predictive_accuracy: 0.8739, prior_entropy: 0.9223, relative_absolute_error: 0.479, root_mean_prior_squared_error: 0.4728, root_mean_squared_error: 0.3134, root_relative_squared_error: 0.6629, unweighted_recall: 0.8532,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set qsar-biodeg
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9261, f_measure: 0.873, kappa: 0.7139, kb_relative_information_score: 0.5562, mean_absolute_error: 0.2077, mean_prior_absolute_error: 0.4472, weighted_recall: 0.8739, number_of_instances: 1055, precision: 0.8727, predictive_accuracy: 0.8739, prior_entropy: 0.9223, relative_absolute_error: 0.4644, root_mean_prior_squared_error: 0.4728, root_mean_squared_error: 0.3133, root_relative_squared_error: 0.6627, unweighted_recall: 0.8518,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set phoneme
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8017, f_measure: 0.7458, kappa: 0.37, kb_relative_information_score: 0.2383, mean_absolute_error: 0.317, mean_prior_absolute_error: 0.4147, weighted_recall: 0.7556, number_of_instances: 5404, precision: 0.7431, predictive_accuracy: 0.7556, prior_entropy: 0.8732, relative_absolute_error: 0.7644, root_mean_prior_squared_error: 0.4554, root_mean_squared_error: 0.3991, root_relative_squared_error: 0.8765, unweighted_recall: 0.6731,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set phoneme
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8016, f_measure: 0.7448, kappa: 0.3672, kb_relative_information_score: 0.2388, mean_absolute_error: 0.3168, mean_prior_absolute_error: 0.4147, weighted_recall: 0.755, number_of_instances: 5404, precision: 0.7422, predictive_accuracy: 0.755, prior_entropy: 0.8732, relative_absolute_error: 0.7639, root_mean_prior_squared_error: 0.4554, root_mean_squared_error: 0.3991, root_relative_squared_error: 0.8766, unweighted_recall: 0.6714,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set wdbc
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9948, f_measure: 0.9628, kappa: 0.9198, kb_relative_information_score: 0.8413, mean_absolute_error: 0.0849, mean_prior_absolute_error: 0.4676, weighted_recall: 0.9631, number_of_instances: 569, precision: 0.9643, predictive_accuracy: 0.9631, prior_entropy: 0.9526, relative_absolute_error: 0.1816, root_mean_prior_squared_error: 0.4835, root_mean_squared_error: 0.1663, root_relative_squared_error: 0.344, unweighted_recall: 0.9524,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set wdbc
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9937, f_measure: 0.9718, kappa: 0.9396, kb_relative_information_score: 0.893, mean_absolute_error: 0.055, mean_prior_absolute_error: 0.4676, weighted_recall: 0.9719, number_of_instances: 569, precision: 0.9719, predictive_accuracy: 0.9719, prior_entropy: 0.9526, relative_absolute_error: 0.1176, root_mean_prior_squared_error: 0.4835, root_mean_squared_error: 0.1528, root_relative_squared_error: 0.3161, unweighted_recall: 0.968,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set Bioresponse
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7757, f_measure: 0.72, kappa: 0.4369, kb_relative_information_score: 0.1573, mean_absolute_error: 0.4322, mean_prior_absolute_error: 0.4964, weighted_recall: 0.7251, number_of_instances: 3751, precision: 0.7296, predictive_accuracy: 0.7251, prior_entropy: 0.9948, relative_absolute_error: 0.8706, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4535, root_relative_squared_error: 0.9103, unweighted_recall: 0.7148,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set Bioresponse
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7508, f_measure: 0.712, kappa: 0.4198, kb_relative_information_score: 0.1552, mean_absolute_error: 0.4319, mean_prior_absolute_error: 0.4964, weighted_recall: 0.7161, number_of_instances: 3751, precision: 0.7182, predictive_accuracy: 0.7161, prior_entropy: 0.9948, relative_absolute_error: 0.8699, root_mean_prior_squared_error: 0.4982, root_mean_squared_error: 0.4608, root_relative_squared_error: 0.9249, unweighted_recall: 0.7069,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set adult
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8857, f_measure: 0.8352, kappa: 0.5296, kb_relative_information_score: 0.3736, mean_absolute_error: 0.2199, mean_prior_absolute_error: 0.3641, weighted_recall: 0.8434, number_of_instances: 48842, precision: 0.8352, predictive_accuracy: 0.8434, prior_entropy: 0.7938, relative_absolute_error: 0.6041, root_mean_prior_squared_error: 0.4266, root_mean_squared_error: 0.3318, root_relative_squared_error: 0.7778, unweighted_recall: 0.7421,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set madelon
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5788, f_measure: 0.555, kappa: 0.11, kb_relative_information_score: 0.021, mean_absolute_error: 0.4921, mean_prior_absolute_error: 0.5, weighted_recall: 0.555, number_of_instances: 2600, precision: 0.555, predictive_accuracy: 0.555, prior_entropy: 1, relative_absolute_error: 0.9843, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4956, root_relative_squared_error: 0.9913, unweighted_recall: 0.555,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set electricity
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8159, f_measure: 0.7489, kappa: 0.4834, kb_relative_information_score: 0.3331, mean_absolute_error: 0.3402, mean_prior_absolute_error: 0.4886, weighted_recall: 0.7546, number_of_instances: 45312, precision: 0.7564, predictive_accuracy: 0.7546, prior_entropy: 0.9835, relative_absolute_error: 0.6962, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4105, root_relative_squared_error: 0.8306, unweighted_recall: 0.7349,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set texture
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9998, f_measure: 0.9982, kappa: 0.998, kb_relative_information_score: 0.9779, mean_absolute_error: 0.0088, mean_prior_absolute_error: 0.1653, weighted_recall: 0.9982, number_of_instances: 5500, precision: 0.9982, predictive_accuracy: 0.9982, prior_entropy: 3.4594, relative_absolute_error: 0.0533, root_mean_prior_squared_error: 0.2875, root_mean_squared_error: 0.0317, root_relative_squared_error: 0.1103, unweighted_recall: 0.9982,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set texture
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 0.9978, kappa: 0.9976, kb_relative_information_score: 0.9906, mean_absolute_error: 0.0036, mean_prior_absolute_error: 0.1653, weighted_recall: 0.9978, number_of_instances: 5500, precision: 0.9978, predictive_accuracy: 0.9978, prior_entropy: 3.4594, relative_absolute_error: 0.0218, root_mean_prior_squared_error: 0.2875, root_mean_squared_error: 0.0221, root_relative_squared_error: 0.077, unweighted_recall: 0.9978,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set dresses-sales
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.4323, kappa: -0.0113, kb_relative_information_score: -0.0006, mean_absolute_error: 0.4868, mean_prior_absolute_error: 0.4873, weighted_recall: 0.572, number_of_instances: 500, precision: 0.461, predictive_accuracy: 0.572, prior_entropy: 0.9815, relative_absolute_error: 0.9991, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.4947, root_relative_squared_error: 1.0024, unweighted_recall: 0.4951,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set dresses-sales
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4898, kb_relative_information_score: -0.0039, mean_absolute_error: 0.4883, mean_prior_absolute_error: 0.4873, weighted_recall: 0.58, number_of_instances: 500, predictive_accuracy: 0.58, prior_entropy: 0.9815, relative_absolute_error: 1.0021, root_mean_prior_squared_error: 0.4936, root_mean_squared_error: 0.4942, root_relative_squared_error: 1.0014, unweighted_recall: 0.5,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set har
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9986, f_measure: 0.9864, kappa: 0.9836, kb_relative_information_score: 0.971, mean_absolute_error: 0.0136, mean_prior_absolute_error: 0.2771, weighted_recall: 0.9864, number_of_instances: 10299, precision: 0.9864, predictive_accuracy: 0.9864, prior_entropy: 2.5759, relative_absolute_error: 0.0492, root_mean_prior_squared_error: 0.3722, root_mean_squared_error: 0.0624, root_relative_squared_error: 0.1676, unweighted_recall: 0.9872,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set har
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9993, f_measure: 0.9859, kappa: 0.9831, kb_relative_information_score: 0.9791, mean_absolute_error: 0.009, mean_prior_absolute_error: 0.2771, weighted_recall: 0.9859, number_of_instances: 10299, precision: 0.9859, predictive_accuracy: 0.9859, prior_entropy: 2.5759, relative_absolute_error: 0.0326, root_mean_prior_squared_error: 0.3722, root_mean_squared_error: 0.0609, root_relative_squared_error: 0.1635, unweighted_recall: 0.9867,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set GesturePhaseSegmentationProcessed
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7369, f_measure: 0.3951, kappa: 0.2693, kb_relative_information_score: 0.2362, mean_absolute_error: 0.2692, mean_prior_absolute_error: 0.3065, weighted_recall: 0.4747, number_of_instances: 9873, precision: 0.4328, predictive_accuracy: 0.4747, prior_entropy: 2.1934, relative_absolute_error: 0.8784, root_mean_prior_squared_error: 0.3915, root_mean_squared_error: 0.3653, root_relative_squared_error: 0.9333, unweighted_recall: 0.3436,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set adult
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8857, f_measure: 0.8356, kappa: 0.5314, kb_relative_information_score: 0.374, mean_absolute_error: 0.2197, mean_prior_absolute_error: 0.3641, weighted_recall: 0.8435, number_of_instances: 48842, precision: 0.8353, predictive_accuracy: 0.8435, prior_entropy: 0.7938, relative_absolute_error: 0.6036, root_mean_prior_squared_error: 0.4266, root_mean_squared_error: 0.3318, root_relative_squared_error: 0.7777, unweighted_recall: 0.7438,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set GesturePhaseSegmentationProcessed
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7614, f_measure: 0.4066, kappa: 0.2757, kb_relative_information_score: 0.2277, mean_absolute_error: 0.2679, mean_prior_absolute_error: 0.3065, weighted_recall: 0.4771, number_of_instances: 9873, precision: 0.4754, predictive_accuracy: 0.4771, prior_entropy: 2.1934, relative_absolute_error: 0.8741, root_mean_prior_squared_error: 0.3915, root_mean_squared_error: 0.3626, root_relative_squared_error: 0.9263, unweighted_recall: 0.3499,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set madelon
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5832, f_measure: 0.5602, kappa: 0.1238, kb_relative_information_score: 0.016, mean_absolute_error: 0.4941, mean_prior_absolute_error: 0.5, weighted_recall: 0.5619, number_of_instances: 2600, precision: 0.5629, predictive_accuracy: 0.5619, prior_entropy: 1, relative_absolute_error: 0.9882, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4958, root_relative_squared_error: 0.9917, unweighted_recall: 0.5619,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set bank-marketing
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8694, f_measure: 0.865, kappa: 0.2505, kb_relative_information_score: 0.0846, mean_absolute_error: 0.1614, mean_prior_absolute_error: 0.2066, weighted_recall: 0.8908, number_of_instances: 45211, precision: 0.867, predictive_accuracy: 0.8908, prior_entropy: 0.5206, relative_absolute_error: 0.7811, root_mean_prior_squared_error: 0.3214, root_mean_squared_error: 0.2842, root_relative_squared_error: 0.8843, unweighted_recall: 0.5884,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set electricity
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8161, f_measure: 0.7493, kappa: 0.4841, kb_relative_information_score: 0.338, mean_absolute_error: 0.3374, mean_prior_absolute_error: 0.4886, weighted_recall: 0.7546, number_of_instances: 45312, precision: 0.7559, predictive_accuracy: 0.7546, prior_entropy: 0.9835, relative_absolute_error: 0.6906, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4104, root_relative_squared_error: 0.8303, unweighted_recall: 0.7356,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set bank-marketing
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8563, f_measure: 0.8654, kappa: 0.2577, kb_relative_information_score: 0.0595, mean_absolute_error: 0.1646, mean_prior_absolute_error: 0.2066, weighted_recall: 0.8891, number_of_instances: 45211, precision: 0.8644, predictive_accuracy: 0.8891, prior_entropy: 0.5206, relative_absolute_error: 0.7966, root_mean_prior_squared_error: 0.3214, root_mean_squared_error: 0.2885, root_relative_squared_error: 0.8977, unweighted_recall: 0.5932,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set analcatdata_dmft
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5647, f_measure: 0.1975, kappa: 0.0598, kb_relative_information_score: 0.0505, mean_absolute_error: 0.2747, mean_prior_absolute_error: 0.2774, weighted_recall: 0.2171, number_of_instances: 797, precision: 0.2063, predictive_accuracy: 0.2171, prior_entropy: 2.5803, relative_absolute_error: 0.9901, root_mean_prior_squared_error: 0.3724, root_mean_squared_error: 0.3706, root_relative_squared_error: 0.995, unweighted_recall: 0.2197,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set analcatdata_dmft
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5719, f_measure: 0.173, kappa: 0.0261, kb_relative_information_score: 0.0403, mean_absolute_error: 0.2753, mean_prior_absolute_error: 0.2774, weighted_recall: 0.1982, number_of_instances: 797, precision: 0.2086, predictive_accuracy: 0.1982, prior_entropy: 2.5803, relative_absolute_error: 0.9923, root_mean_prior_squared_error: 0.3724, root_mean_squared_error: 0.3707, root_relative_squared_error: 0.9954, unweighted_recall: 0.1901,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set analcatdata_authorship
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9998, f_measure: 0.9964, kappa: 0.9948, kb_relative_information_score: 0.9606, mean_absolute_error: 0.0228, mean_prior_absolute_error: 0.3439, weighted_recall: 0.9964, number_of_instances: 841, precision: 0.9964, predictive_accuracy: 0.9964, prior_entropy: 1.7874, relative_absolute_error: 0.0663, root_mean_prior_squared_error: 0.4146, root_mean_squared_error: 0.0503, root_relative_squared_error: 0.1214, unweighted_recall: 0.9975,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set analcatdata_authorship
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9999, f_measure: 0.9941, kappa: 0.9914, kb_relative_information_score: 0.9773, mean_absolute_error: 0.0123, mean_prior_absolute_error: 0.3439, weighted_recall: 0.9941, number_of_instances: 841, precision: 0.9941, predictive_accuracy: 0.9941, prior_entropy: 1.7874, relative_absolute_error: 0.0359, root_mean_prior_squared_error: 0.4146, root_mean_squared_error: 0.0491, root_relative_squared_error: 0.1185, unweighted_recall: 0.996,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set pc1
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6803, f_measure: 0.902, kappa: 0.0629, kb_relative_information_score: -0.107, mean_absolute_error: 0.1241, mean_prior_absolute_error: 0.1299, weighted_recall: 0.9306, number_of_instances: 1109, precision: 0.9029, predictive_accuracy: 0.9306, prior_entropy: 0.3638, relative_absolute_error: 0.9557, root_mean_prior_squared_error: 0.2542, root_mean_squared_error: 0.2483, root_relative_squared_error: 0.977, unweighted_recall: 0.518,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set isolet
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9985, f_measure: 0.9684, kappa: 0.9672, kb_relative_information_score: 0.898, mean_absolute_error: 0.0204, mean_prior_absolute_error: 0.074, weighted_recall: 0.9684, number_of_instances: 7797, precision: 0.9685, predictive_accuracy: 0.9684, prior_entropy: 4.7004, relative_absolute_error: 0.2755, root_mean_prior_squared_error: 0.1923, root_mean_squared_error: 0.0743, root_relative_squared_error: 0.3864, unweighted_recall: 0.9684,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set pc1
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6764, kb_relative_information_score: -0.0085, mean_absolute_error: 0.1276, mean_prior_absolute_error: 0.1299, weighted_recall: 0.9306, number_of_instances: 1109, predictive_accuracy: 0.9306, prior_entropy: 0.3638, relative_absolute_error: 0.9822, root_mean_prior_squared_error: 0.2542, root_mean_squared_error: 0.2525, root_relative_squared_error: 0.9934, unweighted_recall: 0.5,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set kc1
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6767, f_measure: 0.8122, kappa: 0.1762, kb_relative_information_score: 0.0906, mean_absolute_error: 0.2344, mean_prior_absolute_error: 0.2616, weighted_recall: 0.8573, number_of_instances: 2109, precision: 0.8392, predictive_accuracy: 0.8573, prior_entropy: 0.6212, relative_absolute_error: 0.8962, root_mean_prior_squared_error: 0.3615, root_mean_squared_error: 0.3407, root_relative_squared_error: 0.9425, unweighted_recall: 0.5584,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set kc1
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6666, f_measure: 0.8072, kappa: 0.1524, kb_relative_information_score: 0.0814, mean_absolute_error: 0.2374, mean_prior_absolute_error: 0.2616, weighted_recall: 0.8554, number_of_instances: 2109, precision: 0.8364, predictive_accuracy: 0.8554, prior_entropy: 0.6212, relative_absolute_error: 0.9076, root_mean_prior_squared_error: 0.3615, root_mean_squared_error: 0.3426, root_relative_squared_error: 0.9478, unweighted_recall: 0.5498,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set kc2
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7842, f_measure: 0.8147, kappa: 0.3813, kb_relative_information_score: 0.2167, mean_absolute_error: 0.2569, mean_prior_absolute_error: 0.3266, weighted_recall: 0.841, number_of_instances: 522, precision: 0.8307, predictive_accuracy: 0.841, prior_entropy: 0.7318, relative_absolute_error: 0.7865, root_mean_prior_squared_error: 0.4037, root_mean_squared_error: 0.3529, root_relative_squared_error: 0.8742, unweighted_recall: 0.6503,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set kc2
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7957, f_measure: 0.8001, kappa: 0.3263, kb_relative_information_score: 0.2109, mean_absolute_error: 0.2584, mean_prior_absolute_error: 0.3266, weighted_recall: 0.8352, number_of_instances: 522, precision: 0.83, predictive_accuracy: 0.8352, prior_entropy: 0.7318, relative_absolute_error: 0.7913, root_mean_prior_squared_error: 0.4037, root_mean_squared_error: 0.3564, root_relative_squared_error: 0.8829, unweighted_recall: 0.6224,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set jm1
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6568, f_measure: 0.7386, kappa: 0.0641, kb_relative_information_score: 0.0344, mean_absolute_error: 0.2997, mean_prior_absolute_error: 0.3121, weighted_recall: 0.8104, number_of_instances: 10885, precision: 0.7776, predictive_accuracy: 0.8104, prior_entropy: 0.7087, relative_absolute_error: 0.9603, root_mean_prior_squared_error: 0.395, root_mean_squared_error: 0.3865, root_relative_squared_error: 0.9784, unweighted_recall: 0.5208,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set cmc
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6736, f_measure: 0.4987, kappa: 0.2193, kb_relative_information_score: 0.1324, mean_absolute_error: 0.4017, mean_prior_absolute_error: 0.4308, weighted_recall: 0.5064, number_of_instances: 1473, precision: 0.5011, predictive_accuracy: 0.5064, prior_entropy: 1.539, relative_absolute_error: 0.9323, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.446, root_relative_squared_error: 0.961, unweighted_recall: 0.4719,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set cmc
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6974, f_measure: 0.4997, kappa: 0.2212, kb_relative_information_score: 0.1688, mean_absolute_error: 0.3859, mean_prior_absolute_error: 0.4308, weighted_recall: 0.5071, number_of_instances: 1473, precision: 0.5009, predictive_accuracy: 0.5071, prior_entropy: 1.539, relative_absolute_error: 0.8957, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4376, root_relative_squared_error: 0.9428, unweighted_recall: 0.4733,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set mfeat-zernike
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9744, f_measure: 0.8234, kappa: 0.8067, kb_relative_information_score: 0.777, mean_absolute_error: 0.0713, mean_prior_absolute_error: 0.18, weighted_recall: 0.826, number_of_instances: 2000, precision: 0.8213, predictive_accuracy: 0.826, prior_entropy: 3.3219, relative_absolute_error: 0.3962, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1649, root_relative_squared_error: 0.5497, unweighted_recall: 0.826,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set jm1
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6515, f_measure: 0.7385, kappa: 0.0637, kb_relative_information_score: 0.0346, mean_absolute_error: 0.2996, mean_prior_absolute_error: 0.3121, weighted_recall: 0.8102, number_of_instances: 10885, precision: 0.7761, predictive_accuracy: 0.8102, prior_entropy: 0.7087, relative_absolute_error: 0.9599, root_mean_prior_squared_error: 0.395, root_mean_squared_error: 0.3869, root_relative_squared_error: 0.9794, unweighted_recall: 0.5207,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set mfeat-zernike
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9867, f_measure: 0.8615, kappa: 0.8472, kb_relative_information_score: 0.8406, mean_absolute_error: 0.0473, mean_prior_absolute_error: 0.18, weighted_recall: 0.8625, number_of_instances: 2000, precision: 0.8618, predictive_accuracy: 0.8625, prior_entropy: 3.3219, relative_absolute_error: 0.2627, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1392, root_relative_squared_error: 0.4639, unweighted_recall: 0.8625,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set mfeat-morphological
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9554, f_measure: 0.7361, kappa: 0.7128, kb_relative_information_score: 0.6941, mean_absolute_error: 0.0908, mean_prior_absolute_error: 0.18, weighted_recall: 0.7415, number_of_instances: 2000, precision: 0.743, predictive_accuracy: 0.7415, prior_entropy: 3.3219, relative_absolute_error: 0.5042, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1977, root_relative_squared_error: 0.6589, unweighted_recall: 0.7415,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set mfeat-morphological
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9656, f_measure: 0.7454, kappa: 0.7183, kb_relative_information_score: 0.7486, mean_absolute_error: 0.0708, mean_prior_absolute_error: 0.18, weighted_recall: 0.7465, number_of_instances: 2000, precision: 0.7484, predictive_accuracy: 0.7465, prior_entropy: 3.3219, relative_absolute_error: 0.3935, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1814, root_relative_squared_error: 0.6047, unweighted_recall: 0.7465,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set mfeat-karhunen
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9929, f_measure: 0.9595, kappa: 0.955, kb_relative_information_score: 0.8747, mean_absolute_error: 0.0453, mean_prior_absolute_error: 0.18, weighted_recall: 0.9595, number_of_instances: 2000, precision: 0.9598, predictive_accuracy: 0.9595, prior_entropy: 3.3219, relative_absolute_error: 0.2517, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1106, root_relative_squared_error: 0.3687, unweighted_recall: 0.9595,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set mfeat-karhunen
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9978, f_measure: 0.9585, kappa: 0.9539, kb_relative_information_score: 0.9223, mean_absolute_error: 0.0241, mean_prior_absolute_error: 0.18, weighted_recall: 0.9585, number_of_instances: 2000, precision: 0.9587, predictive_accuracy: 0.9585, prior_entropy: 3.3219, relative_absolute_error: 0.1339, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.0872, root_relative_squared_error: 0.2906, unweighted_recall: 0.9585,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set breast-w
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9944, f_measure: 0.9627, kappa: 0.9173, kb_relative_information_score: 0.8614, mean_absolute_error: 0.0697, mean_prior_absolute_error: 0.4519, weighted_recall: 0.9628, number_of_instances: 699, precision: 0.9627, predictive_accuracy: 0.9628, prior_entropy: 0.9293, relative_absolute_error: 0.1542, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1646, root_relative_squared_error: 0.3464, unweighted_recall: 0.9569,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set breast-w
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9944, f_measure: 0.9642, kappa: 0.9206, kb_relative_information_score: 0.8812, mean_absolute_error: 0.0576, mean_prior_absolute_error: 0.4519, weighted_recall: 0.9642, number_of_instances: 699, precision: 0.9642, predictive_accuracy: 0.9642, prior_entropy: 0.9293, relative_absolute_error: 0.1275, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1643, root_relative_squared_error: 0.3456, unweighted_recall: 0.9589,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set mfeat-fourier
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9765, f_measure: 0.8399, kappa: 0.8233, kb_relative_information_score: 0.7543, mean_absolute_error: 0.0777, mean_prior_absolute_error: 0.18, weighted_recall: 0.841, number_of_instances: 2000, precision: 0.8409, predictive_accuracy: 0.841, prior_entropy: 3.3219, relative_absolute_error: 0.4317, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1723, root_relative_squared_error: 0.5743, unweighted_recall: 0.841,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set mfeat-fourier
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9809, f_measure: 0.833, kappa: 0.8144, kb_relative_information_score: 0.8012, mean_absolute_error: 0.0571, mean_prior_absolute_error: 0.18, weighted_recall: 0.833, number_of_instances: 2000, precision: 0.8336, predictive_accuracy: 0.833, prior_entropy: 3.3219, relative_absolute_error: 0.3172, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1561, root_relative_squared_error: 0.5202, unweighted_recall: 0.833,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set mfeat-factors
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9964, f_measure: 0.9785, kappa: 0.9761, kb_relative_information_score: 0.9032, mean_absolute_error: 0.0368, mean_prior_absolute_error: 0.18, weighted_recall: 0.9785, number_of_instances: 2000, precision: 0.9786, predictive_accuracy: 0.9785, prior_entropy: 3.3219, relative_absolute_error: 0.2045, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.0917, root_relative_squared_error: 0.3057, unweighted_recall: 0.9785,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set mfeat-factors
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9991, f_measure: 0.979, kappa: 0.9767, kb_relative_information_score: 0.9545, mean_absolute_error: 0.0153, mean_prior_absolute_error: 0.18, weighted_recall: 0.979, number_of_instances: 2000, precision: 0.9791, predictive_accuracy: 0.979, prior_entropy: 3.3219, relative_absolute_error: 0.0852, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.0623, root_relative_squared_error: 0.2076, unweighted_recall: 0.979,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set isolet
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9994, f_measure: 0.9692, kappa: 0.968, kb_relative_information_score: 0.9573, mean_absolute_error: 0.0073, mean_prior_absolute_error: 0.074, weighted_recall: 0.9692, number_of_instances: 7797, precision: 0.9693, predictive_accuracy: 0.9692, prior_entropy: 4.7004, relative_absolute_error: 0.0991, root_mean_prior_squared_error: 0.1923, root_mean_squared_error: 0.0461, root_relative_squared_error: 0.2398, unweighted_recall: 0.9692,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set balance-scale
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9731, f_measure: 0.9148, kappa: 0.8419, kb_relative_information_score: 0.7668, mean_absolute_error: 0.1051, mean_prior_absolute_error: 0.3798, weighted_recall: 0.9072, number_of_instances: 625, precision: 0.9289, predictive_accuracy: 0.9072, prior_entropy: 1.3181, relative_absolute_error: 0.2767, root_mean_prior_squared_error: 0.4356, root_mean_squared_error: 0.2077, root_relative_squared_error: 0.4768, unweighted_recall: 0.8764,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set balance-scale
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9787, f_measure: 0.9247, kappa: 0.8593, kb_relative_information_score: 0.7811, mean_absolute_error: 0.0953, mean_prior_absolute_error: 0.3798, weighted_recall: 0.9168, number_of_instances: 625, precision: 0.9426, predictive_accuracy: 0.9168, prior_entropy: 1.3181, relative_absolute_error: 0.2509, root_mean_prior_squared_error: 0.4356, root_mean_squared_error: 0.2046, root_relative_squared_error: 0.4698, unweighted_recall: 0.9172,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set letter
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9893, f_measure: 0.8557, kappa: 0.8503, kb_relative_information_score: 0.8179, mean_absolute_error: 0.0283, mean_prior_absolute_error: 0.074, weighted_recall: 0.8561, number_of_instances: 20000, precision: 0.857, predictive_accuracy: 0.8561, prior_entropy: 4.6998, relative_absolute_error: 0.3831, root_mean_prior_squared_error: 0.1923, root_mean_squared_error: 0.1064, root_relative_squared_error: 0.5533, unweighted_recall: 0.855,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set vehicle
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9317, f_measure: 0.7989, kappa: 0.7368, kb_relative_information_score: 0.6505, mean_absolute_error: 0.171, mean_prior_absolute_error: 0.3748, weighted_recall: 0.8026, number_of_instances: 846, precision: 0.7964, predictive_accuracy: 0.8026, prior_entropy: 1.9991, relative_absolute_error: 0.4562, root_mean_prior_squared_error: 0.4329, root_mean_squared_error: 0.2733, root_relative_squared_error: 0.6314, unweighted_recall: 0.805,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set vehicle
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9474, f_measure: 0.792, kappa: 0.7257, kb_relative_information_score: 0.7097, mean_absolute_error: 0.1399, mean_prior_absolute_error: 0.3748, weighted_recall: 0.7943, number_of_instances: 846, precision: 0.7901, predictive_accuracy: 0.7943, prior_entropy: 1.9991, relative_absolute_error: 0.3732, root_mean_prior_squared_error: 0.4329, root_mean_squared_error: 0.2551, root_relative_squared_error: 0.5892, unweighted_recall: 0.7968,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =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: 0.5745, f_measure: 0.5189, kappa: 0.0039, kb_relative_information_score: 0.0047, mean_absolute_error: 0.4484, mean_prior_absolute_error: 0.453, weighted_recall: 0.6545, number_of_instances: 958, precision: 0.774, predictive_accuracy: 0.6545, prior_entropy: 0.931, relative_absolute_error: 0.9898, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.4728, root_relative_squared_error: 0.9935, unweighted_recall: 0.5015,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set tic-tac-toe
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4783, kb_relative_information_score: -0.002, mean_absolute_error: 0.4527, mean_prior_absolute_error: 0.453, weighted_recall: 0.6534, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.931, relative_absolute_error: 0.9992, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.4762, root_relative_squared_error: 1.0007, unweighted_recall: 0.5,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set splice
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9764, f_measure: 0.9142, kappa: 0.8609, kb_relative_information_score: 0.793, mean_absolute_error: 0.1089, mean_prior_absolute_error: 0.4101, weighted_recall: 0.9135, number_of_instances: 3190, precision: 0.9161, predictive_accuracy: 0.9135, prior_entropy: 1.4802, relative_absolute_error: 0.2656, root_mean_prior_squared_error: 0.4528, root_mean_squared_error: 0.2139, root_relative_squared_error: 0.4724, unweighted_recall: 0.9104,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set splice
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9801, f_measure: 0.9121, kappa: 0.8577, kb_relative_information_score: 0.8179, mean_absolute_error: 0.0924, mean_prior_absolute_error: 0.4101, weighted_recall: 0.9113, number_of_instances: 3190, precision: 0.9147, predictive_accuracy: 0.9113, prior_entropy: 1.4802, relative_absolute_error: 0.2253, root_mean_prior_squared_error: 0.4528, root_mean_squared_error: 0.2081, root_relative_squared_error: 0.4597, unweighted_recall: 0.9099,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set spambase
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9716, f_measure: 0.9275, kappa: 0.8474, kb_relative_information_score: 0.7109, mean_absolute_error: 0.1521, mean_prior_absolute_error: 0.4776, weighted_recall: 0.9278, number_of_instances: 4601, precision: 0.928, predictive_accuracy: 0.9278, prior_entropy: 0.9674, relative_absolute_error: 0.3184, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2504, root_relative_squared_error: 0.5125, unweighted_recall: 0.9196,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set letter
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9941, f_measure: 0.8596, kappa: 0.854, kb_relative_information_score: 0.8445, mean_absolute_error: 0.0213, mean_prior_absolute_error: 0.074, weighted_recall: 0.8597, number_of_instances: 20000, precision: 0.8606, predictive_accuracy: 0.8597, prior_entropy: 4.6998, relative_absolute_error: 0.2874, root_mean_prior_squared_error: 0.1923, root_mean_squared_error: 0.093, root_relative_squared_error: 0.4834, unweighted_recall: 0.8586,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set spambase
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9715, f_measure: 0.9257, kappa: 0.8438, kb_relative_information_score: 0.7424, mean_absolute_error: 0.1337, mean_prior_absolute_error: 0.4776, weighted_recall: 0.9261, number_of_instances: 4601, precision: 0.9262, predictive_accuracy: 0.9261, prior_entropy: 0.9674, relative_absolute_error: 0.28, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2449, root_relative_squared_error: 0.5012, unweighted_recall: 0.9179,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set diabetes
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8286, f_measure: 0.7657, kappa: 0.4737, kb_relative_information_score: 0.3079, mean_absolute_error: 0.3232, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7747, number_of_instances: 768, precision: 0.7702, predictive_accuracy: 0.7747, prior_entropy: 0.9331, relative_absolute_error: 0.7111, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3974, root_relative_squared_error: 0.8337, unweighted_recall: 0.7231,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set diabetes
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8283, f_measure: 0.7642, kappa: 0.4702, kb_relative_information_score: 0.3188, mean_absolute_error: 0.3173, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7734, number_of_instances: 768, precision: 0.7688, predictive_accuracy: 0.7734, prior_entropy: 0.9331, relative_absolute_error: 0.6981, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3973, root_relative_squared_error: 0.8336, unweighted_recall: 0.7213,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set pendigits
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9981, f_measure: 0.9824, kappa: 0.9805, kb_relative_information_score: 0.9604, mean_absolute_error: 0.0138, mean_prior_absolute_error: 0.18, weighted_recall: 0.9824, number_of_instances: 10992, precision: 0.9824, predictive_accuracy: 0.9824, prior_entropy: 3.3208, relative_absolute_error: 0.0768, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.0592, root_relative_squared_error: 0.1973, unweighted_recall: 0.9823,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set vowel
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9813, f_measure: 0.8036, kappa: 0.7878, kb_relative_information_score: 0.7102, mean_absolute_error: 0.0852, mean_prior_absolute_error: 0.1653, weighted_recall: 0.8071, number_of_instances: 990, precision: 0.8052, predictive_accuracy: 0.8071, prior_entropy: 3.4594, relative_absolute_error: 0.5154, root_mean_prior_squared_error: 0.2875, root_mean_squared_error: 0.1843, root_relative_squared_error: 0.6412, unweighted_recall: 0.8071,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set vowel
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.983, f_measure: 0.8122, kappa: 0.7956, kb_relative_information_score: 0.757, mean_absolute_error: 0.0663, mean_prior_absolute_error: 0.1653, weighted_recall: 0.8141, number_of_instances: 990, precision: 0.8119, predictive_accuracy: 0.8141, prior_entropy: 3.4594, relative_absolute_error: 0.4009, root_mean_prior_squared_error: 0.2875, root_mean_squared_error: 0.165, root_relative_squared_error: 0.5739, unweighted_recall: 0.8141,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set pendigits
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9825, kappa: 0.9806, kb_relative_information_score: 0.9717, mean_absolute_error: 0.0091, mean_prior_absolute_error: 0.18, weighted_recall: 0.9825, number_of_instances: 10992, precision: 0.9825, predictive_accuracy: 0.9825, prior_entropy: 3.3208, relative_absolute_error: 0.0503, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.0551, root_relative_squared_error: 0.1838, unweighted_recall: 0.9825,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set sick
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9411, f_measure: 0.96, kappa: 0.624, kb_relative_information_score: 0.2741, mean_absolute_error: 0.0601, mean_prior_absolute_error: 0.1152, weighted_recall: 0.9634, number_of_instances: 3772, precision: 0.96, predictive_accuracy: 0.9634, prior_entropy: 0.3324, relative_absolute_error: 0.5222, root_mean_prior_squared_error: 0.2398, root_mean_squared_error: 0.1651, root_relative_squared_error: 0.6884, unweighted_recall: 0.764,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set mfeat-pixel
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9941, f_measure: 0.976, kappa: 0.9733, kb_relative_information_score: 0.8959, mean_absolute_error: 0.0387, mean_prior_absolute_error: 0.18, weighted_recall: 0.976, number_of_instances: 2000, precision: 0.9762, predictive_accuracy: 0.976, prior_entropy: 3.3219, relative_absolute_error: 0.2153, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.0977, root_relative_squared_error: 0.3257, unweighted_recall: 0.976,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set sick
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9386, f_measure: 0.961, kappa: 0.6348, kb_relative_information_score: 0.2957, mean_absolute_error: 0.0584, mean_prior_absolute_error: 0.1152, weighted_recall: 0.9642, number_of_instances: 3772, precision: 0.961, predictive_accuracy: 0.9642, prior_entropy: 0.3324, relative_absolute_error: 0.5069, root_mean_prior_squared_error: 0.2398, root_mean_squared_error: 0.1651, root_relative_squared_error: 0.6884, unweighted_recall: 0.7705,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set credit-g
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7779, f_measure: 0.7368, kappa: 0.3515, kb_relative_information_score: 0.2074, mean_absolute_error: 0.3322, mean_prior_absolute_error: 0.4202, weighted_recall: 0.752, number_of_instances: 1000, precision: 0.7371, predictive_accuracy: 0.752, prior_entropy: 0.8813, relative_absolute_error: 0.7906, root_mean_prior_squared_error: 0.4583, root_mean_squared_error: 0.4066, root_relative_squared_error: 0.8872, unweighted_recall: 0.66,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set eucalyptus
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.893, f_measure: 0.652, kappa: 0.5608, kb_relative_information_score: 0.498, mean_absolute_error: 0.2037, mean_prior_absolute_error: 0.3132, weighted_recall: 0.6603, number_of_instances: 736, precision: 0.6528, predictive_accuracy: 0.6603, prior_entropy: 2.2621, relative_absolute_error: 0.6502, root_mean_prior_squared_error: 0.3957, root_mean_squared_error: 0.3083, root_relative_squared_error: 0.779, unweighted_recall: 0.6218,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set eucalyptus
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9033, f_measure: 0.6558, kappa: 0.5649, kb_relative_information_score: 0.5266, mean_absolute_error: 0.1887, mean_prior_absolute_error: 0.3132, weighted_recall: 0.6644, number_of_instances: 736, precision: 0.6623, predictive_accuracy: 0.6644, prior_entropy: 2.2621, relative_absolute_error: 0.6025, root_mean_prior_squared_error: 0.3957, root_mean_squared_error: 0.3023, root_relative_squared_error: 0.7639, unweighted_recall: 0.6204,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set mfeat-pixel
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9988, f_measure: 0.974, kappa: 0.9711, kb_relative_information_score: 0.9429, mean_absolute_error: 0.0186, mean_prior_absolute_error: 0.18, weighted_recall: 0.974, number_of_instances: 2000, precision: 0.9741, predictive_accuracy: 0.974, prior_entropy: 3.3219, relative_absolute_error: 0.1031, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.072, root_relative_squared_error: 0.2402, unweighted_recall: 0.974,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set credit-g
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7797, f_measure: 0.7284, kappa: 0.3284, kb_relative_information_score: 0.2035, mean_absolute_error: 0.3341, mean_prior_absolute_error: 0.4202, weighted_recall: 0.748, number_of_instances: 1000, precision: 0.7314, predictive_accuracy: 0.748, prior_entropy: 0.8813, relative_absolute_error: 0.7953, root_mean_prior_squared_error: 0.4583, root_mean_squared_error: 0.406, root_relative_squared_error: 0.8859, unweighted_recall: 0.6467,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set satimage
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9697, f_measure: 0.8666, kappa: 0.8402, kb_relative_information_score: 0.7832, mean_absolute_error: 0.0814, mean_prior_absolute_error: 0.2701, weighted_recall: 0.8711, number_of_instances: 6430, precision: 0.8648, predictive_accuracy: 0.8711, prior_entropy: 2.4834, relative_absolute_error: 0.3013, root_mean_prior_squared_error: 0.3675, root_mean_squared_error: 0.1889, root_relative_squared_error: 0.5141, unweighted_recall: 0.831,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set credit-approval
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8786, f_measure: 0.8554, kappa: 0.7116, kb_relative_information_score: 0.5429, mean_absolute_error: 0.246, mean_prior_absolute_error: 0.494, weighted_recall: 0.8551, number_of_instances: 690, precision: 0.8663, predictive_accuracy: 0.8551, prior_entropy: 0.9912, relative_absolute_error: 0.498, root_mean_prior_squared_error: 0.497, root_mean_squared_error: 0.3436, root_relative_squared_error: 0.6913, unweighted_recall: 0.862,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set ilpd
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7225, f_measure: 0.613, kappa: 0.0332, kb_relative_information_score: 0.0603, mean_absolute_error: 0.374, mean_prior_absolute_error: 0.4091, weighted_recall: 0.7153, number_of_instances: 583, precision: 0.669, predictive_accuracy: 0.7153, prior_entropy: 0.8641, relative_absolute_error: 0.9141, root_mean_prior_squared_error: 0.4521, root_mean_squared_error: 0.427, root_relative_squared_error: 0.9446, unweighted_recall: 0.512,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set credit-approval
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.887, f_measure: 0.8554, kappa: 0.7116, kb_relative_information_score: 0.5601, mean_absolute_error: 0.2358, mean_prior_absolute_error: 0.494, weighted_recall: 0.8551, number_of_instances: 690, precision: 0.8663, predictive_accuracy: 0.8551, prior_entropy: 0.9912, relative_absolute_error: 0.4774, root_mean_prior_squared_error: 0.497, root_mean_squared_error: 0.3427, root_relative_squared_error: 0.6895, unweighted_recall: 0.862,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set ilpd
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.65, f_measure: 0.5934, kappa: -0.0034, kb_relative_information_score: 0.0055, mean_absolute_error: 0.4012, mean_prior_absolute_error: 0.4091, weighted_recall: 0.7118, number_of_instances: 583, precision: 0.5088, predictive_accuracy: 0.7118, prior_entropy: 0.8641, relative_absolute_error: 0.9806, root_mean_prior_squared_error: 0.4521, root_mean_squared_error: 0.4429, root_relative_squared_error: 0.9797, unweighted_recall: 0.4988,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set segment
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9787, f_measure: 0.8899, kappa: 0.8722, kb_relative_information_score: 0.8212, mean_absolute_error: 0.0657, mean_prior_absolute_error: 0.2449, weighted_recall: 0.8905, number_of_instances: 2310, precision: 0.8905, predictive_accuracy: 0.8905, prior_entropy: 2.8074, relative_absolute_error: 0.2685, root_mean_prior_squared_error: 0.3499, root_mean_squared_error: 0.1645, root_relative_squared_error: 0.4702, unweighted_recall: 0.8905,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set optdigits
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9988, f_measure: 0.9842, kappa: 0.9824, kb_relative_information_score: 0.9514, mean_absolute_error: 0.0182, mean_prior_absolute_error: 0.18, weighted_recall: 0.9842, number_of_instances: 5620, precision: 0.9842, predictive_accuracy: 0.9842, prior_entropy: 3.3218, relative_absolute_error: 0.1013, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.0625, root_relative_squared_error: 0.2084, unweighted_recall: 0.9841,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set semeion
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9931, f_measure: 0.9442, kappa: 0.9379, kb_relative_information_score: 0.8481, mean_absolute_error: 0.0528, mean_prior_absolute_error: 0.18, weighted_recall: 0.9441, number_of_instances: 1593, precision: 0.9449, predictive_accuracy: 0.9441, prior_entropy: 3.3218, relative_absolute_error: 0.2932, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.126, root_relative_squared_error: 0.4199, unweighted_recall: 0.9439,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set segment
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9832, f_measure: 0.8901, kappa: 0.8722, kb_relative_information_score: 0.8489, mean_absolute_error: 0.0578, mean_prior_absolute_error: 0.2449, weighted_recall: 0.8905, number_of_instances: 2310, precision: 0.8905, predictive_accuracy: 0.8905, prior_entropy: 2.8074, relative_absolute_error: 0.2359, root_mean_prior_squared_error: 0.3499, root_mean_squared_error: 0.1582, root_relative_squared_error: 0.4522, unweighted_recall: 0.8905,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set car
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8294, f_measure: 0.8475, kappa: 0.6583, kb_relative_information_score: 0.5312, mean_absolute_error: 0.1344, mean_prior_absolute_error: 0.229, weighted_recall: 0.8536, number_of_instances: 1728, precision: 0.848, predictive_accuracy: 0.8536, prior_entropy: 1.2058, relative_absolute_error: 0.5868, root_mean_prior_squared_error: 0.3381, root_mean_squared_error: 0.2488, root_relative_squared_error: 0.7358, unweighted_recall: 0.749,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set satimage
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9828, f_measure: 0.8644, kappa: 0.8369, kb_relative_information_score: 0.8252, mean_absolute_error: 0.0635, mean_prior_absolute_error: 0.2701, weighted_recall: 0.8684, number_of_instances: 6430, precision: 0.8626, predictive_accuracy: 0.8684, prior_entropy: 2.4834, relative_absolute_error: 0.235, root_mean_prior_squared_error: 0.3675, root_mean_squared_error: 0.1754, root_relative_squared_error: 0.4774, unweighted_recall: 0.8285,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set car
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.936, f_measure: 0.846, kappa: 0.657, kb_relative_information_score: 0.5897, mean_absolute_error: 0.1124, mean_prior_absolute_error: 0.229, weighted_recall: 0.8513, number_of_instances: 1728, precision: 0.8452, predictive_accuracy: 0.8513, prior_entropy: 1.2058, relative_absolute_error: 0.4908, root_mean_prior_squared_error: 0.3381, root_mean_squared_error: 0.2338, root_relative_squared_error: 0.6914, unweighted_recall: 0.7459,
Nicolas Hug 5 years ago
ran flow sklearn.calibration.Calibrated ... =sklearn.svm._classes.SVC))(1) on task Supervised Classification on data set kr-vs-kp
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9934, f_measure: 0.9668, kappa: 0.9336, kb_relative_information_score: 0.8806, mean_absolute_error: 0.0664, mean_prior_absolute_error: 0.499, weighted_recall: 0.9668, number_of_instances: 3196, precision: 0.9671, predictive_accuracy: 0.9668, prior_entropy: 0.9986, relative_absolute_error: 0.1331, root_mean_prior_squared_error: 0.4995, root_mean_squared_error: 0.1653, root_relative_squared_error: 0.3309, unweighted_recall: 0.9673,
Nicolas Hug 5 years ago
ran flow sklearn.pipeline.Pipeline(simp ... c=sklearn.svm._classes.SVC)(2) on task Supervised Classification on data set semeion
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9974, f_measure: 0.9392, kappa: 0.9323, kb_relative_information_score: 0.9045, mean_absolute_error: 0.0284, mean_prior_absolute_error: 0.18, weighted_recall: 0.9391, number_of_instances: 1593, precision: 0.9397, predictive_accuracy: 0.9391, prior_entropy: 3.3218, relative_absolute_error: 0.1578, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.0999, root_relative_squared_error: 0.3329, unweighted_recall: 0.9389,