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Marc Zöller 5 years ago
ran flow sklearn.pipeline.Pipeline(step ... 1=sklearn.svm._classes.SVC)(1) on task Supervised Classification on data set eeg-eye-state
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: -0.1193, mean_absolute_error: 0.5512, mean_prior_absolute_error: 0.4948, weighted_recall: 0.4488, number_of_instances: 14980, predictive_accuracy: 0.4488, prior_entropy: 0.9924, relative_absolute_error: 1.1141, root_mean_prior_squared_error: 0.4974, root_mean_squared_error: 0.7424, root_relative_squared_error: 1.4927, unweighted_recall: 0.5,
Marc Zöller 5 years ago
ran flow sklearn.pipeline.Pipeline(step ... 1=sklearn.svm._classes.SVC)(1) on task Supervised Classification on data set eeg-eye-state
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: -0.1193, mean_absolute_error: 0.5512, mean_prior_absolute_error: 0.4948, weighted_recall: 0.4488, number_of_instances: 14980, predictive_accuracy: 0.4488, prior_entropy: 0.9924, relative_absolute_error: 1.1141, root_mean_prior_squared_error: 0.4974, root_mean_squared_error: 0.7424, root_relative_squared_error: 1.4927, unweighted_recall: 0.5,
Marc Zöller 5 years ago
ran flow sklearn.pipeline.Pipeline(step ... 1=sklearn.svm._classes.SVC)(1) on task Supervised Classification on data set eeg-eye-state
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: -0.1193, mean_absolute_error: 0.5512, mean_prior_absolute_error: 0.4948, weighted_recall: 0.4488, number_of_instances: 14980, predictive_accuracy: 0.4488, prior_entropy: 0.9924, relative_absolute_error: 1.1141, root_mean_prior_squared_error: 0.4974, root_mean_squared_error: 0.7424, root_relative_squared_error: 1.4927, unweighted_recall: 0.5,
Marc Zöller 5 years ago
ran flow sklearn.pipeline.Pipeline(step ... 1=sklearn.svm._classes.SVC)(1) on task Supervised Classification on data set pollen
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5016, f_measure: 0.3686, kappa: 0.0005, kb_relative_information_score: 0.0001, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.5, weighted_recall: 0.5003, number_of_instances: 3848, precision: 0.5016, predictive_accuracy: 0.5003, prior_entropy: 1, relative_absolute_error: 0.9999, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5001, root_relative_squared_error: 1.0002, unweighted_recall: 0.5003,
Marc Zöller 5 years ago
ran flow sklearn.pipeline.Pipeline(step ... 1=sklearn.svm._classes.SVC)(1) on task Supervised Classification on data set pollen
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4919, f_measure: 0.4775, kappa: -0.0161, kb_relative_information_score: -0.0161, mean_absolute_error: 0.5081, mean_prior_absolute_error: 0.5, weighted_recall: 0.4919, number_of_instances: 3848, precision: 0.4909, predictive_accuracy: 0.4919, prior_entropy: 1, relative_absolute_error: 1.0161, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.7128, root_relative_squared_error: 1.4256, unweighted_recall: 0.4919,
Marc Zöller 5 years ago
ran flow sklearn.pipeline.Pipeline(step ... 1=sklearn.svm._classes.SVC)(1) on task Supervised Classification on data set pollen
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4948, f_measure: 0.494, kappa: -0.0104, kb_relative_information_score: -0.0104, mean_absolute_error: 0.5052, mean_prior_absolute_error: 0.5, weighted_recall: 0.4948, number_of_instances: 3848, precision: 0.4948, predictive_accuracy: 0.4948, prior_entropy: 1, relative_absolute_error: 1.0104, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.7108, root_relative_squared_error: 1.4215, unweighted_recall: 0.4948,
Marc Zöller 5 years ago
ran flow sklearn.pipeline.Pipeline(step ... 1=sklearn.svm._classes.SVC)(1) on task Supervised Classification on data set pollen
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4971, f_measure: 0.4971, kappa: -0.0057, kb_relative_information_score: -0.0057, mean_absolute_error: 0.5029, mean_prior_absolute_error: 0.5, weighted_recall: 0.4971, number_of_instances: 3848, precision: 0.4971, predictive_accuracy: 0.4971, prior_entropy: 1, relative_absolute_error: 1.0057, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.7091, root_relative_squared_error: 1.4183, unweighted_recall: 0.4971,
Marc Zöller 5 years ago
ran flow sklearn.pipeline.Pipeline(step ... 1=sklearn.svm._classes.SVC)(1) on task Supervised Classification on data set pollen
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5168, f_measure: 0.4709, kappa: 0.014, kb_relative_information_score: 0.0006, mean_absolute_error: 0.4998, mean_prior_absolute_error: 0.5, weighted_recall: 0.507, number_of_instances: 3848, precision: 0.5096, predictive_accuracy: 0.507, prior_entropy: 1, relative_absolute_error: 0.9996, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4999, root_relative_squared_error: 0.9997, unweighted_recall: 0.507,
Marc Zöller 5 years ago
ran flow sklearn.pipeline.Pipeline(step ... 1=sklearn.svm._classes.SVC)(1) on task Supervised Classification on data set wilt
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4981, kb_relative_information_score: -0.1605, mean_absolute_error: 0.1041, mean_prior_absolute_error: 0.1022, weighted_recall: 0.9461, number_of_instances: 4839, predictive_accuracy: 0.9461, prior_entropy: 0.3029, relative_absolute_error: 1.0182, root_mean_prior_squared_error: 0.2259, root_mean_squared_error: 0.2259, root_relative_squared_error: 1.0001, unweighted_recall: 0.5,