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Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(colu ... est.RandomForestClassifier)(2) on task Supervised Classification on data set cnae-9
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9772, f_measure: 0.8358, kappa: 0.8115, kb_relative_information_score: 0.6641, mean_absolute_error: 0.0969, mean_prior_absolute_error: 0.1975, weighted_recall: 0.8324, number_of_instances: 1080, precision: 0.8685, predictive_accuracy: 0.8324, prior_entropy: 3.1699, relative_absolute_error: 0.4908, root_mean_prior_squared_error: 0.3143, root_mean_squared_error: 0.1883, root_relative_squared_error: 0.5991, unweighted_recall: 0.8324,
Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(colu ... est.RandomForestClassifier)(2) on task Supervised Classification on data set mfeat-factors
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9977, f_measure: 0.9475, kappa: 0.9417, kb_relative_information_score: 0.8571, mean_absolute_error: 0.0462, mean_prior_absolute_error: 0.18, weighted_recall: 0.9475, number_of_instances: 2000, precision: 0.9484, predictive_accuracy: 0.9475, prior_entropy: 3.3219, relative_absolute_error: 0.2568, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1149, root_relative_squared_error: 0.3829, unweighted_recall: 0.9475,
Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(colu ... est.RandomForestClassifier)(2) on task Supervised Classification on data set climate-model-simulation-crashes
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5735, kb_relative_information_score: -0.3715, mean_absolute_error: 0.1546, mean_prior_absolute_error: 0.1571, weighted_recall: 0.9148, number_of_instances: 540, predictive_accuracy: 0.9148, prior_entropy: 0.4202, relative_absolute_error: 0.9842, root_mean_prior_squared_error: 0.2792, root_mean_squared_error: 0.2799, root_relative_squared_error: 1.0025, unweighted_recall: 0.5,
Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(colu ... est.RandomForestClassifier)(2) on task Supervised Classification on data set churn
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6862, f_measure: 0.8097, kappa: 0.0865, kb_relative_information_score: -0.0403, mean_absolute_error: 0.2201, mean_prior_absolute_error: 0.2429, weighted_recall: 0.8614, number_of_instances: 5000, precision: 0.8274, predictive_accuracy: 0.8614, prior_entropy: 0.5879, relative_absolute_error: 0.9061, root_mean_prior_squared_error: 0.3484, root_mean_squared_error: 0.3317, root_relative_squared_error: 0.952, unweighted_recall: 0.527,
Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(colu ... est.RandomForestClassifier)(2) on task Supervised Classification on data set segment
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9815, f_measure: 0.8709, kappa: 0.851, kb_relative_information_score: 0.8213, mean_absolute_error: 0.0645, mean_prior_absolute_error: 0.2449, weighted_recall: 0.8723, number_of_instances: 2310, precision: 0.873, predictive_accuracy: 0.8723, prior_entropy: 2.8074, relative_absolute_error: 0.2635, root_mean_prior_squared_error: 0.3499, root_mean_squared_error: 0.1686, root_relative_squared_error: 0.4818, unweighted_recall: 0.8723,
Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(colu ... est.RandomForestClassifier)(2) on task Supervised Classification on data set steel-plates-fault
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8601, f_measure: 0.5929, kappa: 0.4834, kb_relative_information_score: 0.469, mean_absolute_error: 0.1487, mean_prior_absolute_error: 0.2223, weighted_recall: 0.6198, number_of_instances: 1941, precision: 0.6336, predictive_accuracy: 0.6198, prior_entropy: 2.4107, relative_absolute_error: 0.6687, root_mean_prior_squared_error: 0.3334, root_mean_squared_error: 0.264, root_relative_squared_error: 0.792, unweighted_recall: 0.5273,