Task
Supervised Classification on baskball

Supervised Classification on baskball

Task 4302 Supervised Classification baskball 206 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7206, f_measure: 0.7203, kappa: 0.4427, kb_relative_information_score: 262.3819, mean_absolute_error: 0.3795, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7243, predictive_accuracy: 0.7208, prior_entropy: 0.9997, recall: 0.7208, relative_absolute_error: 0.7593, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4556, root_relative_squared_error: 0.9113, scimark_benchmark: 1296.9979, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7476, f_measure: 0.6943, kappa: 0.3906, kb_relative_information_score: 287.0802, mean_absolute_error: 0.3589, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.6975, predictive_accuracy: 0.6948, prior_entropy: 0.9997, recall: 0.6948, relative_absolute_error: 0.7181, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4635, root_relative_squared_error: 0.9271, scimark_benchmark: 1370.3901, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5778, f_measure: 0.5746, kappa: 0.1564, kb_relative_information_score: 153.5035, mean_absolute_error: 0.4198, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.582, predictive_accuracy: 0.5802, prior_entropy: 0.9997, recall: 0.5802, relative_absolute_error: 0.8399, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.6479, root_relative_squared_error: 1.2961, scimark_benchmark: 1287.9613, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7476, f_measure: 0.6943, kappa: 0.3906, kb_relative_information_score: 287.0802, mean_absolute_error: 0.3589, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.6975, predictive_accuracy: 0.6948, prior_entropy: 0.9997, recall: 0.6948, relative_absolute_error: 0.7181, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4635, root_relative_squared_error: 0.9271, scimark_benchmark: 1260.1387, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6612, f_measure: 0.7236, kappa: 0.4517, kb_relative_information_score: 256.1558, mean_absolute_error: 0.3848, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7324, predictive_accuracy: 0.725, prior_entropy: 0.9997, recall: 0.725, relative_absolute_error: 0.77, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4504, root_relative_squared_error: 0.9009, scimark_benchmark: 1322.7257,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7206, f_measure: 0.7203, kappa: 0.4427, kb_relative_information_score: 262.3819, mean_absolute_error: 0.3795, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7243, predictive_accuracy: 0.7208, prior_entropy: 0.9997, recall: 0.7208, relative_absolute_error: 0.7593, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4556, root_relative_squared_error: 0.9113, scimark_benchmark: 1344.4042,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7476, f_measure: 0.6943, kappa: 0.3906, kb_relative_information_score: 287.0802, mean_absolute_error: 0.3589, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.6975, predictive_accuracy: 0.6948, prior_entropy: 0.9997, recall: 0.6948, relative_absolute_error: 0.7181, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4635, root_relative_squared_error: 0.9271, scimark_benchmark: 942.9708, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7769, f_measure: 0.7048, kappa: 0.4094, kb_relative_information_score: 277.4047, mean_absolute_error: 0.3689, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7056, predictive_accuracy: 0.7052, prior_entropy: 0.9997, recall: 0.7052, relative_absolute_error: 0.7381, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4386, root_relative_squared_error: 0.8773, scimark_benchmark: 1059.8591, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6612, f_measure: 0.7236, kappa: 0.4517, kb_relative_information_score: 256.7815, mean_absolute_error: 0.3845, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7324, predictive_accuracy: 0.725, prior_entropy: 0.9997, recall: 0.725, relative_absolute_error: 0.7693, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4504, root_relative_squared_error: 0.9011, scimark_benchmark: 1341.5795,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7441, f_measure: 0.7114, kappa: 0.4225, kb_relative_information_score: 259.4717, mean_absolute_error: 0.3759, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7114, predictive_accuracy: 0.7115, prior_entropy: 0.9997, recall: 0.7115, relative_absolute_error: 0.7522, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4575, root_relative_squared_error: 0.9151, scimark_benchmark: 1280.6338,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6612, f_measure: 0.7236, kappa: 0.4517, kb_relative_information_score: 256.1558, mean_absolute_error: 0.3848, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7324, predictive_accuracy: 0.725, prior_entropy: 0.9997, recall: 0.725, relative_absolute_error: 0.77, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4504, root_relative_squared_error: 0.9009, scimark_benchmark: 918.0213,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6612, f_measure: 0.7236, kappa: 0.4517, kb_relative_information_score: 256.7815, mean_absolute_error: 0.3845, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7324, predictive_accuracy: 0.725, prior_entropy: 0.9997, recall: 0.725, relative_absolute_error: 0.7693, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4504, root_relative_squared_error: 0.9011, scimark_benchmark: 918.0213,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6612, f_measure: 0.7236, kappa: 0.4517, kb_relative_information_score: 256.7815, mean_absolute_error: 0.3845, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7324, predictive_accuracy: 0.725, prior_entropy: 0.9997, recall: 0.725, relative_absolute_error: 0.7693, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4504, root_relative_squared_error: 0.9011, scimark_benchmark: 938.0414,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7206, f_measure: 0.7203, kappa: 0.4427, kb_relative_information_score: 262.3819, mean_absolute_error: 0.3795, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7243, predictive_accuracy: 0.7208, prior_entropy: 0.9997, recall: 0.7208, relative_absolute_error: 0.7593, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4556, root_relative_squared_error: 0.9113, scimark_benchmark: 1288.1375, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6612, f_measure: 0.7236, kappa: 0.4517, kb_relative_information_score: 256.7815, mean_absolute_error: 0.3845, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7324, predictive_accuracy: 0.725, prior_entropy: 0.9997, recall: 0.725, relative_absolute_error: 0.7693, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4504, root_relative_squared_error: 0.9011, scimark_benchmark: 1312.2688,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7543, f_measure: 0.7228, kappa: 0.4463, kb_relative_information_score: 146.0364, mean_absolute_error: 0.4393, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.724, predictive_accuracy: 0.7229, prior_entropy: 0.9997, recall: 0.7229, relative_absolute_error: 0.879, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4556, root_relative_squared_error: 0.9113, scimark_benchmark: 1345.7204, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6612, f_measure: 0.7236, kappa: 0.4517, kb_relative_information_score: 256.7815, mean_absolute_error: 0.3845, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7324, predictive_accuracy: 0.725, prior_entropy: 0.9997, recall: 0.725, relative_absolute_error: 0.7693, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4504, root_relative_squared_error: 0.9011, scimark_benchmark: 1345.7204,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7441, f_measure: 0.7114, kappa: 0.4225, kb_relative_information_score: 259.4717, mean_absolute_error: 0.3759, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7114, predictive_accuracy: 0.7115, prior_entropy: 0.9997, recall: 0.7115, relative_absolute_error: 0.7522, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4575, root_relative_squared_error: 0.9151, scimark_benchmark: 1347.917,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6612, f_measure: 0.7236, kappa: 0.4517, kb_relative_information_score: 256.7815, mean_absolute_error: 0.3845, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7324, predictive_accuracy: 0.725, prior_entropy: 0.9997, recall: 0.725, relative_absolute_error: 0.7693, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4504, root_relative_squared_error: 0.9011, scimark_benchmark: 933.1165,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6612, f_measure: 0.7236, kappa: 0.4517, kb_relative_information_score: 256.7815, mean_absolute_error: 0.3845, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7324, predictive_accuracy: 0.725, prior_entropy: 0.9997, recall: 0.725, relative_absolute_error: 0.7693, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4504, root_relative_squared_error: 0.9011, scimark_benchmark: 1354.3488,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6612, f_measure: 0.7236, kappa: 0.4517, kb_relative_information_score: 256.1558, mean_absolute_error: 0.3848, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7324, predictive_accuracy: 0.725, prior_entropy: 0.9997, recall: 0.725, relative_absolute_error: 0.77, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4504, root_relative_squared_error: 0.9009, scimark_benchmark: 933.1165,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7476, f_measure: 0.6943, kappa: 0.3906, kb_relative_information_score: 287.0802, mean_absolute_error: 0.3589, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.6975, predictive_accuracy: 0.6948, prior_entropy: 0.9997, recall: 0.6948, relative_absolute_error: 0.7181, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4635, root_relative_squared_error: 0.9271, scimark_benchmark: 1354.7191, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7284, f_measure: 0.6802, kappa: 0.3606, kb_relative_information_score: 312.7821, mean_absolute_error: 0.341, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.6807, predictive_accuracy: 0.6802, prior_entropy: 0.9997, recall: 0.6802, relative_absolute_error: 0.6822, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4985, root_relative_squared_error: 0.9972, scimark_benchmark: 1352.6859, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7441, f_measure: 0.7114, kappa: 0.4225, kb_relative_information_score: 259.4717, mean_absolute_error: 0.3759, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7114, predictive_accuracy: 0.7115, prior_entropy: 0.9997, recall: 0.7115, relative_absolute_error: 0.7522, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4575, root_relative_squared_error: 0.9151, scimark_benchmark: 1328.941,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6621, f_measure: 0.6796, kappa: 0.3616, kb_relative_information_score: 248.9547, mean_absolute_error: 0.3818, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.6832, predictive_accuracy: 0.6802, prior_entropy: 0.9997, recall: 0.6802, relative_absolute_error: 0.764, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5035, root_relative_squared_error: 1.0073, scimark_benchmark: 1151.6869,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.554, f_measure: 0.5542, kappa: 0.1079, kb_relative_information_score: 103.4734, mean_absolute_error: 0.4458, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.5542, predictive_accuracy: 0.5542, prior_entropy: 0.9997, recall: 0.5542, relative_absolute_error: 0.892, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.6677, root_relative_squared_error: 1.3357, scimark_benchmark: 1320.9026,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.75, f_measure: 0.7177, kappa: 0.4356, kb_relative_information_score: 149.4338, mean_absolute_error: 0.4373, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7182, predictive_accuracy: 0.7177, prior_entropy: 0.9997, recall: 0.7177, relative_absolute_error: 0.8751, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4559, root_relative_squared_error: 0.912, scimark_benchmark: 1342.1678,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7791, f_measure: 0.751, kappa: 0.5024, kb_relative_information_score: 290.9918, mean_absolute_error: 0.3653, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.752, predictive_accuracy: 0.751, prior_entropy: 0.9997, recall: 0.751, relative_absolute_error: 0.7309, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4369, root_relative_squared_error: 0.8741, scimark_benchmark: 1342.3004, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6608, f_measure: 0.7236, kappa: 0.4517, kb_relative_information_score: 261.1922, mean_absolute_error: 0.382, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7324, predictive_accuracy: 0.725, prior_entropy: 0.9997, recall: 0.725, relative_absolute_error: 0.7644, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.451, root_relative_squared_error: 0.9022, scimark_benchmark: 1358.4523,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7275, f_measure: 0.7021, kappa: 0.4043, kb_relative_information_score: 405.7579, mean_absolute_error: 0.2884, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7024, predictive_accuracy: 0.7021, prior_entropy: 0.9997, recall: 0.7021, relative_absolute_error: 0.577, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5196, root_relative_squared_error: 1.0394, scimark_benchmark: 1006.9991,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7521, f_measure: 0.7219, kappa: 0.444, kb_relative_information_score: 143.9315, mean_absolute_error: 0.4402, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7226, predictive_accuracy: 0.7219, prior_entropy: 0.9997, recall: 0.7219, relative_absolute_error: 0.8808, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4563, root_relative_squared_error: 0.9128, scimark_benchmark: 1349.9917, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7506, f_measure: 0.725, kappa: 0.4503, kb_relative_information_score: 142.546, mean_absolute_error: 0.4407, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7257, predictive_accuracy: 0.725, prior_entropy: 0.9997, recall: 0.725, relative_absolute_error: 0.8819, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4569, root_relative_squared_error: 0.914, scimark_benchmark: 1348.7888, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7407, f_measure: 0.7011, kappa: 0.4022, kb_relative_information_score: 276.4378, mean_absolute_error: 0.3671, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7014, predictive_accuracy: 0.701, prior_entropy: 0.9997, recall: 0.701, relative_absolute_error: 0.7344, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4646, root_relative_squared_error: 0.9294, scimark_benchmark: 1320.9366,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6608, f_measure: 0.7236, kappa: 0.4517, kb_relative_information_score: 261.1922, mean_absolute_error: 0.382, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7324, predictive_accuracy: 0.725, prior_entropy: 0.9997, recall: 0.725, relative_absolute_error: 0.7644, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.451, root_relative_squared_error: 0.9022, scimark_benchmark: 1151.3336,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6285, f_measure: 0.6686, kappa: 0.3381, kb_relative_information_score: 216.231, mean_absolute_error: 0.4012, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.67, predictive_accuracy: 0.6688, prior_entropy: 0.9997, recall: 0.6688, relative_absolute_error: 0.8028, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5055, root_relative_squared_error: 1.0113, scimark_benchmark: 1347.388,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7609, f_measure: 0.7187, kappa: 0.4371, kb_relative_information_score: 233.293, mean_absolute_error: 0.3938, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7187, predictive_accuracy: 0.7188, prior_entropy: 0.9997, recall: 0.7188, relative_absolute_error: 0.7879, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4446, root_relative_squared_error: 0.8894, scimark_benchmark: 1322.4968, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7313, f_measure: 0.6802, kappa: 0.3606, kb_relative_information_score: 301.3248, mean_absolute_error: 0.3486, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.6806, predictive_accuracy: 0.6802, prior_entropy: 0.9997, recall: 0.6802, relative_absolute_error: 0.6975, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4837, root_relative_squared_error: 0.9676, scimark_benchmark: 854.5188,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7798, f_measure: 0.7107, kappa: 0.4216, kb_relative_information_score: 297.1283, mean_absolute_error: 0.3579, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7125, predictive_accuracy: 0.7115, prior_entropy: 0.9997, recall: 0.7115, relative_absolute_error: 0.7162, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4377, root_relative_squared_error: 0.8756, scimark_benchmark: 938.0414,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7769, f_measure: 0.7048, kappa: 0.4094, kb_relative_information_score: 277.4047, mean_absolute_error: 0.3689, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7056, predictive_accuracy: 0.7052, prior_entropy: 0.9997, recall: 0.7052, relative_absolute_error: 0.7381, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4386, root_relative_squared_error: 0.8773, scimark_benchmark: 918.0213, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6612, f_measure: 0.7236, kappa: 0.4517, kb_relative_information_score: 257.4066, mean_absolute_error: 0.3841, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7324, predictive_accuracy: 0.725, prior_entropy: 0.9997, recall: 0.725, relative_absolute_error: 0.7686, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4505, root_relative_squared_error: 0.9012, scimark_benchmark: 1372.2145,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7476, f_measure: 0.6943, kappa: 0.3906, kb_relative_information_score: 287.0802, mean_absolute_error: 0.3589, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.6975, predictive_accuracy: 0.6948, prior_entropy: 0.9997, recall: 0.6948, relative_absolute_error: 0.7181, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4635, root_relative_squared_error: 0.9271, scimark_benchmark: 1310.3951, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6188, f_measure: 0.6188, kappa: 0.2375, kb_relative_information_score: 227.5479, mean_absolute_error: 0.3813, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.619, predictive_accuracy: 0.6188, prior_entropy: 0.9997, recall: 0.6188, relative_absolute_error: 0.7628, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.6175, root_relative_squared_error: 1.2352, scimark_benchmark: 1073.494,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6915, f_measure: 0.702, kappa: 0.4047, kb_relative_information_score: 251.9194, mean_absolute_error: 0.3838, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7033, predictive_accuracy: 0.7021, prior_entropy: 0.9997, recall: 0.7021, relative_absolute_error: 0.7679, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4727, root_relative_squared_error: 0.9457, scimark_benchmark: 1319.9043,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6639, f_measure: 0.7035, kappa: 0.4096, kb_relative_information_score: 252.0116, mean_absolute_error: 0.3846, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7079, predictive_accuracy: 0.7042, prior_entropy: 0.9997, recall: 0.7042, relative_absolute_error: 0.7695, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4705, root_relative_squared_error: 0.9411, scimark_benchmark: 1301.9956,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6869, f_measure: 0.6864, kappa: 0.3733, kb_relative_information_score: 357.6261, mean_absolute_error: 0.3135, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.6873, predictive_accuracy: 0.6865, prior_entropy: 0.9997, recall: 0.6865, relative_absolute_error: 0.6274, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5599, root_relative_squared_error: 1.1201, scimark_benchmark: 1321.9426,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5725, f_measure: 0.5129, kappa: 0.143, kb_relative_information_score: 125.4866, mean_absolute_error: 0.4344, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.6306, predictive_accuracy: 0.5656, prior_entropy: 0.9997, recall: 0.5656, relative_absolute_error: 0.8691, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.6591, root_relative_squared_error: 1.3184, scimark_benchmark: 1250.8301,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6695, f_measure: 0.6725, kappa: 0.3469, kb_relative_information_score: 228.8565, mean_absolute_error: 0.3929, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.6752, predictive_accuracy: 0.6729, prior_entropy: 0.9997, recall: 0.6729, relative_absolute_error: 0.7862, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4858, root_relative_squared_error: 0.9718, scimark_benchmark: 1330.0803,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7313, f_measure: 0.7305, kappa: 0.4644, kb_relative_information_score: 447.6802, mean_absolute_error: 0.2667, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7405, predictive_accuracy: 0.7333, prior_entropy: 0.9997, recall: 0.7333, relative_absolute_error: 0.5336, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5164, root_relative_squared_error: 1.033, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6901, f_measure: 0.6904, kappa: 0.3805, kb_relative_information_score: 365.6309, mean_absolute_error: 0.3094, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.6906, predictive_accuracy: 0.6906, prior_entropy: 0.9997, recall: 0.6906, relative_absolute_error: 0.619, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5562, root_relative_squared_error: 1.1127, scimark_benchmark: 1341.2341,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4681, f_measure: 0.345, kb_relative_information_score: -0.5904, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.2605, predictive_accuracy: 0.5104, prior_entropy: 0.9997, recall: 0.5104, relative_absolute_error: 1.0004, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5001, root_relative_squared_error: 1.0004, scimark_benchmark: 1380.2233,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6271, f_measure: 0.6666, kappa: 0.3339, kb_relative_information_score: 213.1521, mean_absolute_error: 0.4027, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.6678, predictive_accuracy: 0.6667, prior_entropy: 0.9997, recall: 0.6667, relative_absolute_error: 0.8058, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5067, root_relative_squared_error: 1.0136, scimark_benchmark: 1505.597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6762, build_cpu_time: 0.2671, build_memory: 1665647552.9417, f_measure: 0.6603, kappa: 0.3215, kb_relative_information_score: 307.6984, mean_absolute_error: 0.3395, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.6616, predictive_accuracy: 0.6604, prior_entropy: 0.9997, recall: 0.6604, relative_absolute_error: 0.6793, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5806, root_relative_squared_error: 1.1614, scimark_benchmark: 945.2151,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6825, build_cpu_time: 0.1752, build_memory: 816730494.4083, f_measure: 0.6539, kappa: 0.3092, kb_relative_information_score: 296.7171, mean_absolute_error: 0.3451, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.6557, predictive_accuracy: 0.6542, prior_entropy: 0.9997, recall: 0.6542, relative_absolute_error: 0.6906, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5844, root_relative_squared_error: 1.169, scimark_benchmark: 935.2997,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6927, build_cpu_time: 0.0822, build_memory: 2015694293.1583, f_measure: 0.6633, kappa: 0.3279, kb_relative_information_score: 312.2011, mean_absolute_error: 0.3374, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.6652, predictive_accuracy: 0.6635, prior_entropy: 0.9997, recall: 0.6635, relative_absolute_error: 0.6751, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5733, root_relative_squared_error: 1.1468, scimark_benchmark: 941.4198,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7109, build_cpu_time: 0.0333, build_memory: 862667683.4167, f_measure: 0.6674, kappa: 0.3363, kb_relative_information_score: 317.3953, mean_absolute_error: 0.3345, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.6694, predictive_accuracy: 0.6677, prior_entropy: 0.9997, recall: 0.6677, relative_absolute_error: 0.6692, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5678, root_relative_squared_error: 1.1358, scimark_benchmark: 938.0657,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7382, build_cpu_time: 0.0169, build_memory: 501686356.9083, f_measure: 0.6686, kappa: 0.3381, kb_relative_information_score: 326.4699, mean_absolute_error: 0.3297, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.67, predictive_accuracy: 0.6688, prior_entropy: 0.9997, recall: 0.6688, relative_absolute_error: 0.6597, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.557, root_relative_squared_error: 1.1143, scimark_benchmark: 941.8931,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7027, f_measure: 0.7026, kappa: 0.4065, kb_relative_information_score: 391.6465, mean_absolute_error: 0.2958, mean_prior_absolute_error: 0.4998, number_of_instances: 960, precision: 0.7066, predictive_accuracy: 0.7042, prior_entropy: 0.9997, recall: 0.7042, relative_absolute_error: 0.5919, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5439, root_relative_squared_error: 1.088,

Metric:

Timeline

Plotting contribution timeline

Leaderboard

Rank Name Top Score Entries Highest rank

Note: The leaderboard ignores resubmissions of previous solutions, as well as parameter variations that do not improve performance.

Challenge

In supervised classification, you are given an input dataset in which instances are labeled with a certain class. The goal is to build a model that predicts the class for future unlabeled instances. The model is evaluated using a train-test procedure, e.g. cross-validation.

To make results by different users comparable, you are given the exact train-test folds to be used, and you need to return at least the predictions generated by your model for each of the test instances. OpenML will use these predictions to calculate a range of evaluation measures on the server.

You can also upload your own evaluation measures, provided that the code for doing so is available from the implementation used. For extremely large datasets, it may be infeasible to upload all predictions. In those cases, you need to compute and provide the evaluations yourself.

Optionally, you can upload the model trained on all the input data. There is no restriction on the file format, but please use a well-known format or PMML.

Given inputs

Expected outputs

evaluations A list of user-defined evaluations of the task as key-value pairs. KeyValue (optional)
model A file containing the model built on all the input data. File (optional)
predictions The desired output format Predictions (optional)

How to submit runs

Using your favorite machine learning environment

Download this task directly in your environment and automatically upload your results

OpenML bootcamp

From your own software

Use one of our APIs to download data from OpenML and upload your results

OpenML APIs