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Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(colu ... tic_gradient.SGDClassifier)(2) on task Supervised Classification on data set first-order-theorem-proving
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6091, f_measure: 0.4179, kappa: 0.2202, kb_relative_information_score: 0.2798, mean_absolute_error: 0.1786, mean_prior_absolute_error: 0.2508, weighted_recall: 0.4642, number_of_instances: 6118, precision: 0.4225, predictive_accuracy: 0.4642, prior_entropy: 2.3, relative_absolute_error: 0.7122, root_mean_prior_squared_error: 0.3541, root_mean_squared_error: 0.4226, root_relative_squared_error: 1.1936, unweighted_recall: 0.2994,
Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(colu ... tic_gradient.SGDClassifier)(2) on task Supervised Classification on data set climate-model-simulation-crashes
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: 0.2584, mean_absolute_error: 0.0852, 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: 0.5421, root_mean_prior_squared_error: 0.2792, root_mean_squared_error: 0.2919, root_relative_squared_error: 1.0455, unweighted_recall: 0.5,
Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(colu ... tic_gradient.SGDClassifier)(2) on task Supervised Classification on data set steel-plates-fault
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7089, f_measure: 0.5644, kappa: 0.4423, kb_relative_information_score: 0.4828, mean_absolute_error: 0.1182, mean_prior_absolute_error: 0.2223, weighted_recall: 0.5863, number_of_instances: 1941, precision: 0.5883, predictive_accuracy: 0.5863, prior_entropy: 2.4107, relative_absolute_error: 0.5316, root_mean_prior_squared_error: 0.3334, root_mean_squared_error: 0.3438, root_relative_squared_error: 1.0313, unweighted_recall: 0.4926,
Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(colu ... tic_gradient.SGDClassifier)(2) on task Supervised Classification on data set churn
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5071, f_measure: 0.7978, kappa: 0.0238, kb_relative_information_score: 0.2686, mean_absolute_error: 0.1414, mean_prior_absolute_error: 0.2429, weighted_recall: 0.8586, number_of_instances: 5000, precision: 0.8094, predictive_accuracy: 0.8586, prior_entropy: 0.5879, relative_absolute_error: 0.5821, root_mean_prior_squared_error: 0.3484, root_mean_squared_error: 0.376, root_relative_squared_error: 1.0792, unweighted_recall: 0.5071,
Sergey Redyuk 3 years ago
ran flow sklearn.pipeline.Pipeline(colu ... tic_gradient.SGDClassifier)(2) on task Supervised Classification on data set segment
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7598, f_measure: 0.5195, kappa: 0.5197, kb_relative_information_score: 0.5557, mean_absolute_error: 0.1176, mean_prior_absolute_error: 0.2449, weighted_recall: 0.5883, number_of_instances: 2310, precision: 0.6082, predictive_accuracy: 0.5883, prior_entropy: 2.8074, relative_absolute_error: 0.4803, root_mean_prior_squared_error: 0.3499, root_mean_squared_error: 0.343, root_relative_squared_error: 0.9801, unweighted_recall: 0.5883,