OpenML

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.9872, f_measure: 0.9906, kappa: 0.9792, kb_relative_information_score: 936.9977, mean_absolute_error: 0.0094, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9907, predictive_accuracy: 0.9906, prior_entropy: 0.9312, recall: 0.9906, relative_absolute_error: 0.0207, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.0969, root_relative_squared_error: 0.2037,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.9841, f_measure: 0.9885, kappa: 0.9745, kb_relative_information_score: 932.3972, mean_absolute_error: 0.0115, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9886, predictive_accuracy: 0.9885, prior_entropy: 0.9312, recall: 0.9885, relative_absolute_error: 0.0253, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1072, root_relative_squared_error: 0.2252,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.9872, f_measure: 0.9906, kappa: 0.9792, kb_relative_information_score: 936.9977, mean_absolute_error: 0.0094, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9907, predictive_accuracy: 0.9906, prior_entropy: 0.9312, recall: 0.9906, relative_absolute_error: 0.0207, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.0969, root_relative_squared_error: 0.2037,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.997, f_measure: 0.9979, kappa: 0.9954, kb_relative_information_score: 953.0993, mean_absolute_error: 0.0021, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9979, predictive_accuracy: 0.9979, prior_entropy: 0.9312, recall: 0.9979, relative_absolute_error: 0.0046, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.0457, root_relative_squared_error: 0.096,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.9759, f_measure: 0.9832, kappa: 0.9627, kb_relative_information_score: 920.8961, mean_absolute_error: 0.0167, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9837, predictive_accuracy: 0.9833, prior_entropy: 0.9312, recall: 0.9833, relative_absolute_error: 0.0369, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1292, root_relative_squared_error: 0.2716,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.9872, f_measure: 0.9906, kappa: 0.9792, kb_relative_information_score: 936.9977, mean_absolute_error: 0.0094, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9907, predictive_accuracy: 0.9906, prior_entropy: 0.9312, recall: 0.9906, relative_absolute_error: 0.0207, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.0969, root_relative_squared_error: 0.2037,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5136, f_measure: 0.5377, kappa: 0.0351, kb_relative_information_score: 214.7252, mean_absolute_error: 0.3372, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.7776, predictive_accuracy: 0.6628, prior_entropy: 0.9312, recall: 0.6628, relative_absolute_error: 0.7443, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5807, root_relative_squared_error: 1.2202,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.667, f_measure: 0.7267, kappa: 0.3855, kb_relative_information_score: 426.3464, mean_absolute_error: 0.2411, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.7807, predictive_accuracy: 0.7589, prior_entropy: 0.9312, recall: 0.7589, relative_absolute_error: 0.5323, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.491, root_relative_squared_error: 1.0319,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.994, f_measure: 0.9958, kappa: 0.9908, kb_relative_information_score: 948.4988, mean_absolute_error: 0.0042, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9959, predictive_accuracy: 0.9958, prior_entropy: 0.9312, recall: 0.9958, relative_absolute_error: 0.0092, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.0646, root_relative_squared_error: 0.1358,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.994, f_measure: 0.9958, kappa: 0.9908, kb_relative_information_score: 948.4988, mean_absolute_error: 0.0042, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9959, predictive_accuracy: 0.9958, prior_entropy: 0.9312, recall: 0.9958, relative_absolute_error: 0.0092, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.0646, root_relative_squared_error: 0.1358,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.9759, f_measure: 0.9832, kappa: 0.9627, kb_relative_information_score: 920.8961, mean_absolute_error: 0.0167, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9837, predictive_accuracy: 0.9833, prior_entropy: 0.9312, recall: 0.9833, relative_absolute_error: 0.0369, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1292, root_relative_squared_error: 0.2716,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.9872, f_measure: 0.9906, kappa: 0.9792, kb_relative_information_score: 936.9977, mean_absolute_error: 0.0094, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9907, predictive_accuracy: 0.9906, prior_entropy: 0.9312, recall: 0.9906, relative_absolute_error: 0.0207, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.0969, root_relative_squared_error: 0.2037,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.9759, f_measure: 0.9832, kappa: 0.9627, kb_relative_information_score: 920.8961, mean_absolute_error: 0.0167, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9837, predictive_accuracy: 0.9833, prior_entropy: 0.9312, recall: 0.9833, relative_absolute_error: 0.0369, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1292, root_relative_squared_error: 0.2716,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.9856, f_measure: 0.9895, kappa: 0.9768, kb_relative_information_score: 934.6975, mean_absolute_error: 0.0104, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9897, predictive_accuracy: 0.9896, prior_entropy: 0.9312, recall: 0.9896, relative_absolute_error: 0.023, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1022, root_relative_squared_error: 0.2147,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.9759, f_measure: 0.9832, kappa: 0.9627, kb_relative_information_score: 920.8961, mean_absolute_error: 0.0167, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9837, predictive_accuracy: 0.9833, prior_entropy: 0.9312, recall: 0.9833, relative_absolute_error: 0.0369, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1292, root_relative_squared_error: 0.2716,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.997, f_measure: 0.9979, kappa: 0.9954, kb_relative_information_score: 953.0993, mean_absolute_error: 0.0021, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9979, predictive_accuracy: 0.9979, prior_entropy: 0.9312, recall: 0.9979, relative_absolute_error: 0.0046, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.0457, root_relative_squared_error: 0.096,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.9759, f_measure: 0.9832, kappa: 0.9627, kb_relative_information_score: 920.8961, mean_absolute_error: 0.0167, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9837, predictive_accuracy: 0.9833, prior_entropy: 0.9312, recall: 0.9833, relative_absolute_error: 0.0369, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1292, root_relative_squared_error: 0.2716,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.997, f_measure: 0.9979, kappa: 0.9954, kb_relative_information_score: 953.0993, mean_absolute_error: 0.0021, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9979, predictive_accuracy: 0.9979, prior_entropy: 0.9312, recall: 0.9979, relative_absolute_error: 0.0046, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.0457, root_relative_squared_error: 0.096,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.9955, f_measure: 0.9969, kappa: 0.9931, kb_relative_information_score: 950.7991, mean_absolute_error: 0.0031, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9969, predictive_accuracy: 0.9969, prior_entropy: 0.9312, recall: 0.9969, relative_absolute_error: 0.0069, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.056, root_relative_squared_error: 0.1176,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.994, f_measure: 0.9958, kappa: 0.9908, kb_relative_information_score: 948.4988, mean_absolute_error: 0.0042, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9959, predictive_accuracy: 0.9958, prior_entropy: 0.9312, recall: 0.9958, relative_absolute_error: 0.0092, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.0646, root_relative_squared_error: 0.1358,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.9872, f_measure: 0.9906, kappa: 0.9792, kb_relative_information_score: 936.9977, mean_absolute_error: 0.0094, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9907, predictive_accuracy: 0.9906, prior_entropy: 0.9312, recall: 0.9906, relative_absolute_error: 0.0207, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.0969, root_relative_squared_error: 0.2037,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.9759, f_measure: 0.9832, kappa: 0.9627, kb_relative_information_score: 920.8961, mean_absolute_error: 0.0167, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9837, predictive_accuracy: 0.9833, prior_entropy: 0.9312, recall: 0.9833, relative_absolute_error: 0.0369, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1292, root_relative_squared_error: 0.2716,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.9744, f_measure: 0.9821, kappa: 0.9603, kb_relative_information_score: 918.5958, mean_absolute_error: 0.0177, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9827, predictive_accuracy: 0.9823, prior_entropy: 0.9312, recall: 0.9823, relative_absolute_error: 0.0392, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1332, root_relative_squared_error: 0.2799,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5774, f_measure: 0.6275, kappa: 0.1924, kb_relative_information_score: 309.0347, mean_absolute_error: 0.2944, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.7793, predictive_accuracy: 0.7056, prior_entropy: 0.9312, recall: 0.7056, relative_absolute_error: 0.6498, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5426, root_relative_squared_error: 1.1401,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.5, kb_relative_information_score: 194.0231, mean_absolute_error: 0.3466, mean_prior_absolute_error: 0.453, number_of_instances: 958, predictive_accuracy: 0.6534, prior_entropy: 0.9312, recall: 0.6534, relative_absolute_error: 0.765, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.5887, root_relative_squared_error: 1.2371,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.6889, f_measure: 0.745, kappa: 0.4237, kb_relative_information_score: 444.7483, mean_absolute_error: 0.2328, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.7745, predictive_accuracy: 0.7672, prior_entropy: 0.9312, recall: 0.7672, relative_absolute_error: 0.5138, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.4825, root_relative_squared_error: 1.0139,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=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: 0.9759, f_measure: 0.9832, kappa: 0.9627, kb_relative_information_score: 920.8961, mean_absolute_error: 0.0167, mean_prior_absolute_error: 0.453, number_of_instances: 958, precision: 0.9837, predictive_accuracy: 0.9833, prior_entropy: 0.9312, recall: 0.9833, relative_absolute_error: 0.0369, root_mean_prior_squared_error: 0.4759, root_mean_squared_error: 0.1292, root_relative_squared_error: 0.2716,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8761, f_measure: 0.8347, kappa: 0.7522, kb_relative_information_score: 3869.533, mean_absolute_error: 0.1101, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8348, predictive_accuracy: 0.8348, prior_entropy: 1.5849, recall: 0.8348, relative_absolute_error: 0.2478, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3319, root_relative_squared_error: 0.704,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7917, f_measure: 0.6788, kappa: 0.5829, kb_relative_information_score: 3098.9517, mean_absolute_error: 0.1859, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.7951, predictive_accuracy: 0.7212, prior_entropy: 1.5849, recall: 0.7212, relative_absolute_error: 0.4182, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.4311, root_relative_squared_error: 0.9146,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: 459.3327, mean_absolute_error: 0.4411, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, predictive_accuracy: 0.3384, prior_entropy: 1.5849, recall: 0.3384, relative_absolute_error: 0.9925, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.6641, root_relative_squared_error: 1.4089,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.854, f_measure: 0.7939, kappa: 0.7074, kb_relative_information_score: 3666.8652, mean_absolute_error: 0.1303, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.837, predictive_accuracy: 0.8046, prior_entropy: 1.5849, recall: 0.8046, relative_absolute_error: 0.2931, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3609, root_relative_squared_error: 0.7657,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8853, f_measure: 0.8432, kappa: 0.7701, kb_relative_information_score: 3952.6917, mean_absolute_error: 0.1023, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8606, predictive_accuracy: 0.8466, prior_entropy: 1.5849, recall: 0.8466, relative_absolute_error: 0.2301, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3198, root_relative_squared_error: 0.6784,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: 459.3327, mean_absolute_error: 0.4411, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, predictive_accuracy: 0.3384, prior_entropy: 1.5849, recall: 0.3384, relative_absolute_error: 0.9925, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.6641, root_relative_squared_error: 1.4089,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: 459.3327, mean_absolute_error: 0.4411, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, predictive_accuracy: 0.3384, prior_entropy: 1.5849, recall: 0.3384, relative_absolute_error: 0.9925, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.6641, root_relative_squared_error: 1.4089,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8988, f_measure: 0.8647, kappa: 0.7975, kb_relative_information_score: 4076.7053, mean_absolute_error: 0.09, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8658, predictive_accuracy: 0.865, prior_entropy: 1.5849, recall: 0.865, relative_absolute_error: 0.2025, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3, root_relative_squared_error: 0.6364,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.872, f_measure: 0.8294, kappa: 0.7441, kb_relative_information_score: 3832.5106, mean_absolute_error: 0.1137, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8294, predictive_accuracy: 0.8294, prior_entropy: 1.5849, recall: 0.8294, relative_absolute_error: 0.2559, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3372, root_relative_squared_error: 0.7154,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: 459.3327, mean_absolute_error: 0.4411, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, predictive_accuracy: 0.3384, prior_entropy: 1.5849, recall: 0.3384, relative_absolute_error: 0.9925, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.6641, root_relative_squared_error: 1.4089,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8252, f_measure: 0.7436, kappa: 0.6498, kb_relative_information_score: 3404.0861, mean_absolute_error: 0.156, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8184, predictive_accuracy: 0.766, prior_entropy: 1.5849, recall: 0.766, relative_absolute_error: 0.351, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.395, root_relative_squared_error: 0.8379,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: 459.3327, mean_absolute_error: 0.4411, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, predictive_accuracy: 0.3384, prior_entropy: 1.5849, recall: 0.3384, relative_absolute_error: 0.9925, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.6641, root_relative_squared_error: 1.4089,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: 459.3327, mean_absolute_error: 0.4411, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, predictive_accuracy: 0.3384, prior_entropy: 1.5849, recall: 0.3384, relative_absolute_error: 0.9925, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.6641, root_relative_squared_error: 1.4089,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8806, f_measure: 0.8407, kappa: 0.7612, kb_relative_information_score: 3910.6759, mean_absolute_error: 0.1061, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8408, predictive_accuracy: 0.8408, prior_entropy: 1.5849, recall: 0.8408, relative_absolute_error: 0.2388, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3258, root_relative_squared_error: 0.6911,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8977, f_measure: 0.8629, kappa: 0.7952, kb_relative_information_score: 4065.9996, mean_absolute_error: 0.0911, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8651, predictive_accuracy: 0.8634, prior_entropy: 1.5849, recall: 0.8634, relative_absolute_error: 0.2049, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3018, root_relative_squared_error: 0.6402,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8773, f_measure: 0.8363, kappa: 0.7546, kb_relative_information_score: 3880.4902, mean_absolute_error: 0.1091, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8364, predictive_accuracy: 0.8364, prior_entropy: 1.5849, recall: 0.8364, relative_absolute_error: 0.2454, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3303, root_relative_squared_error: 0.7006,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.842, f_measure: 0.7733, kappa: 0.6835, kb_relative_information_score: 3558.0126, mean_absolute_error: 0.1409, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8306, predictive_accuracy: 0.7886, prior_entropy: 1.5849, recall: 0.7886, relative_absolute_error: 0.3171, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3754, root_relative_squared_error: 0.7964,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8926, f_measure: 0.8566, kappa: 0.7852, kb_relative_information_score: 4020.3476, mean_absolute_error: 0.0955, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8569, predictive_accuracy: 0.8568, prior_entropy: 1.5849, recall: 0.8568, relative_absolute_error: 0.2148, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.309, root_relative_squared_error: 0.6555,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: 459.3327, mean_absolute_error: 0.4411, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, predictive_accuracy: 0.3384, prior_entropy: 1.5849, recall: 0.3384, relative_absolute_error: 0.9925, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.6641, root_relative_squared_error: 1.4089,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: 459.3327, mean_absolute_error: 0.4411, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, predictive_accuracy: 0.3384, prior_entropy: 1.5849, recall: 0.3384, relative_absolute_error: 0.9925, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.6641, root_relative_squared_error: 1.4089,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8968, f_measure: 0.8613, kappa: 0.7934, kb_relative_information_score: 4058.1726, mean_absolute_error: 0.0919, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8657, predictive_accuracy: 0.8622, prior_entropy: 1.5849, recall: 0.8622, relative_absolute_error: 0.2067, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3031, root_relative_squared_error: 0.643,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8066, f_measure: 0.7085, kappa: 0.6128, kb_relative_information_score: 3235.2097, mean_absolute_error: 0.1725, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8057, predictive_accuracy: 0.7412, prior_entropy: 1.5849, recall: 0.7412, relative_absolute_error: 0.3882, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.4154, root_relative_squared_error: 0.8812,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8967, f_measure: 0.8619, kappa: 0.7933, kb_relative_information_score: 4057.4667, mean_absolute_error: 0.0919, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8627, predictive_accuracy: 0.8622, prior_entropy: 1.5849, recall: 0.8622, relative_absolute_error: 0.2067, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3031, root_relative_squared_error: 0.643,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: 459.3327, mean_absolute_error: 0.4411, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, predictive_accuracy: 0.3384, prior_entropy: 1.5849, recall: 0.3384, relative_absolute_error: 0.9925, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.6641, root_relative_squared_error: 1.4089,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: 459.3327, mean_absolute_error: 0.4411, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, predictive_accuracy: 0.3384, prior_entropy: 1.5849, recall: 0.3384, relative_absolute_error: 0.9925, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.6641, root_relative_squared_error: 1.4089,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8228, f_measure: 0.7393, kappa: 0.645, kb_relative_information_score: 3382.2894, mean_absolute_error: 0.1581, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8165, predictive_accuracy: 0.7628, prior_entropy: 1.5849, recall: 0.7628, relative_absolute_error: 0.3558, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3977, root_relative_squared_error: 0.8436,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.892, f_measure: 0.8557, kappa: 0.784, kb_relative_information_score: 4014.8404, mean_absolute_error: 0.096, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, precision: 0.8564, predictive_accuracy: 0.856, prior_entropy: 1.5849, recall: 0.856, relative_absolute_error: 0.216, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.3098, root_relative_squared_error: 0.6573,

Hilde Weerts 6 years ago
ran flow sklearn.pipeline.Pipeline(impu ... lf=sklearn.svm.classes.SVC)(1) on task Supervised Classification on data set waveform-5000

0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: 459.3327, mean_absolute_error: 0.4411, mean_prior_absolute_error: 0.4444, number_of_instances: 5000, predictive_accuracy: 0.3384, prior_entropy: 1.5849, recall: 0.3384, relative_absolute_error: 0.9925, root_mean_prior_squared_error: 0.4714, root_mean_squared_error: 0.6641, root_relative_squared_error: 1.4089,

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