Task
Supervised Classification on visualizing_hamster

Supervised Classification on visualizing_hamster

Task 4461 Supervised Classification visualizing_hamster 237 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7254, f_measure: 0.7079, kappa: 0.4092, kb_relative_information_score: 0.2383, mean_absolute_error: 0.3894, mean_prior_absolute_error: 0.4955, weighted_recall: 0.711, number_of_instances: 730, precision: 0.7109, predictive_accuracy: 0.711, prior_entropy: 0.9934, relative_absolute_error: 0.7858, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4601, root_relative_squared_error: 0.9245, scimark_benchmark: 931.1106, unweighted_recall: 0.702,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6084, f_measure: 0.5772, kappa: 0.1465, kb_relative_information_score: 0.0644, mean_absolute_error: 0.4694, mean_prior_absolute_error: 0.4955, weighted_recall: 0.5849, number_of_instances: 730, precision: 0.58, predictive_accuracy: 0.5849, prior_entropy: 0.9934, relative_absolute_error: 0.9474, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5027, root_relative_squared_error: 1.01, scimark_benchmark: 979.7764, unweighted_recall: 0.5719,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.475, f_measure: 0.408, kappa: 0.0025, kb_relative_information_score: -0.4509, mean_absolute_error: 0.4959, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5147, predictive_accuracy: 0.5466, prior_entropy: 0.9937, recall: 0.5466, relative_absolute_error: 1.0007, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5059, root_relative_squared_error: 1.0164, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7124, f_measure: 0.6975, kappa: 0.3881, kb_relative_information_score: 174.4787, mean_absolute_error: 0.3891, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.6976, predictive_accuracy: 0.6986, prior_entropy: 0.9937, recall: 0.6986, relative_absolute_error: 0.7852, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4679, root_relative_squared_error: 0.9402, scimark_benchmark: 972.587, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6934, f_measure: 0.6684, kappa: 0.3292, kb_relative_information_score: 207.5364, mean_absolute_error: 0.3593, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.6685, predictive_accuracy: 0.6699, prior_entropy: 0.9937, recall: 0.6699, relative_absolute_error: 0.7252, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5135, root_relative_squared_error: 1.0318, scimark_benchmark: 934.3687, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5723, f_measure: 0.5736, kappa: 0.1494, kb_relative_information_score: 126.1867, mean_absolute_error: 0.4082, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5881, predictive_accuracy: 0.5918, prior_entropy: 0.9937, recall: 0.5918, relative_absolute_error: 0.8238, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.6389, root_relative_squared_error: 1.2838, scimark_benchmark: 904.0772,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4748, f_measure: 0.408, kappa: 0.0025, kb_relative_information_score: -0.5865, mean_absolute_error: 0.4959, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5147, predictive_accuracy: 0.5466, prior_entropy: 0.9937, recall: 0.5466, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5047, root_relative_squared_error: 1.014, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4748, f_measure: 0.408, kappa: 0.0025, kb_relative_information_score: -0.5865, mean_absolute_error: 0.4959, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5147, predictive_accuracy: 0.5466, prior_entropy: 0.9937, recall: 0.5466, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5047, root_relative_squared_error: 1.014, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7054, f_measure: 0.6808, kappa: 0.3542, kb_relative_information_score: 130.688, mean_absolute_error: 0.4184, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.6824, predictive_accuracy: 0.6836, prior_entropy: 0.9937, recall: 0.6836, relative_absolute_error: 0.8444, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4655, root_relative_squared_error: 0.9354, scimark_benchmark: 934.695,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.618, f_measure: 0.5943, kappa: 0.1808, kb_relative_information_score: 47.7357, mean_absolute_error: 0.469, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5975, predictive_accuracy: 0.6014, prior_entropy: 0.9937, recall: 0.6014, relative_absolute_error: 0.9464, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4943, root_relative_squared_error: 0.9932, scimark_benchmark: 934.2976, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5752, f_measure: 0.5801, kappa: 0.1534, kb_relative_information_score: 122.1359, mean_absolute_error: 0.411, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5843, predictive_accuracy: 0.589, prior_entropy: 0.9937, recall: 0.589, relative_absolute_error: 0.8293, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.6411, root_relative_squared_error: 1.2881,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5746, f_measure: 0.5962, kappa: 0.2169, kb_relative_information_score: 90.8821, mean_absolute_error: 0.4418, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.6499, predictive_accuracy: 0.6301, prior_entropy: 0.9937, recall: 0.6301, relative_absolute_error: 0.8916, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4939, root_relative_squared_error: 0.9924, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5752, f_measure: 0.5801, kappa: 0.1534, kb_relative_information_score: 122.1359, mean_absolute_error: 0.411, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5843, predictive_accuracy: 0.589, prior_entropy: 0.9937, recall: 0.589, relative_absolute_error: 0.8293, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.6411, root_relative_squared_error: 1.2881,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7254, f_measure: 0.7079, kappa: 0.4092, kb_relative_information_score: 173.9089, mean_absolute_error: 0.3894, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.7109, predictive_accuracy: 0.711, prior_entropy: 0.9937, recall: 0.711, relative_absolute_error: 0.7858, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4601, root_relative_squared_error: 0.9245, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5723, f_measure: 0.5736, kappa: 0.1494, kb_relative_information_score: 126.1867, mean_absolute_error: 0.4082, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5881, predictive_accuracy: 0.5918, prior_entropy: 0.9937, recall: 0.5918, relative_absolute_error: 0.8238, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.6389, root_relative_squared_error: 1.2838, scimark_benchmark: 938.5498,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5723, f_measure: 0.5736, kappa: 0.1494, kb_relative_information_score: 126.1867, mean_absolute_error: 0.4082, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5881, predictive_accuracy: 0.5918, prior_entropy: 0.9937, recall: 0.5918, relative_absolute_error: 0.8238, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.6389, root_relative_squared_error: 1.2838, scimark_benchmark: 974.2014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4748, f_measure: 0.408, kappa: 0.0025, kb_relative_information_score: -0.5851, mean_absolute_error: 0.4959, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5147, predictive_accuracy: 0.5466, prior_entropy: 0.9937, recall: 0.5466, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5046, root_relative_squared_error: 1.0138, scimark_benchmark: 974.2014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4748, f_measure: 0.408, kappa: 0.0025, kb_relative_information_score: -0.5865, mean_absolute_error: 0.4959, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5147, predictive_accuracy: 0.5466, prior_entropy: 0.9937, recall: 0.5466, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5047, root_relative_squared_error: 1.014, scimark_benchmark: 941.3847,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4748, f_measure: 0.408, kappa: 0.0025, kb_relative_information_score: -0.5865, mean_absolute_error: 0.4959, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5147, predictive_accuracy: 0.5466, prior_entropy: 0.9937, recall: 0.5466, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5047, root_relative_squared_error: 1.014, scimark_benchmark: 974.2014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4748, f_measure: 0.408, kappa: 0.0025, kb_relative_information_score: -0.5865, mean_absolute_error: 0.4959, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5147, predictive_accuracy: 0.5466, prior_entropy: 0.9937, recall: 0.5466, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5047, root_relative_squared_error: 1.014, scimark_benchmark: 941.3847,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7254, f_measure: 0.7079, kappa: 0.4092, kb_relative_information_score: 173.9089, mean_absolute_error: 0.3894, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.7109, predictive_accuracy: 0.711, prior_entropy: 0.9937, recall: 0.711, relative_absolute_error: 0.7858, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4601, root_relative_squared_error: 0.9245, scimark_benchmark: 943.1009, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.475, f_measure: 0.408, kappa: 0.0025, kb_relative_information_score: -0.4509, mean_absolute_error: 0.4959, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5147, predictive_accuracy: 0.5466, prior_entropy: 0.9937, recall: 0.5466, relative_absolute_error: 1.0007, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5059, root_relative_squared_error: 1.0164, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5752, f_measure: 0.5801, kappa: 0.1534, kb_relative_information_score: 122.1359, mean_absolute_error: 0.411, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5843, predictive_accuracy: 0.589, prior_entropy: 0.9937, recall: 0.589, relative_absolute_error: 0.8293, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.6411, root_relative_squared_error: 1.2881,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7124, f_measure: 0.6975, kappa: 0.3881, kb_relative_information_score: 174.4787, mean_absolute_error: 0.3891, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.6976, predictive_accuracy: 0.6986, prior_entropy: 0.9937, recall: 0.6986, relative_absolute_error: 0.7852, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4679, root_relative_squared_error: 0.9402, scimark_benchmark: 908.9569,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6934, f_measure: 0.6684, kappa: 0.3292, kb_relative_information_score: 207.5364, mean_absolute_error: 0.3593, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.6685, predictive_accuracy: 0.6699, prior_entropy: 0.9937, recall: 0.6699, relative_absolute_error: 0.7252, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5135, root_relative_squared_error: 1.0318, scimark_benchmark: 940.1541, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5723, f_measure: 0.5736, kappa: 0.1494, kb_relative_information_score: 126.1867, mean_absolute_error: 0.4082, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5881, predictive_accuracy: 0.5918, prior_entropy: 0.9937, recall: 0.5918, relative_absolute_error: 0.8238, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.6389, root_relative_squared_error: 1.2838, scimark_benchmark: 943.6618,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5723, f_measure: 0.5736, kappa: 0.1494, kb_relative_information_score: 126.1867, mean_absolute_error: 0.4082, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5881, predictive_accuracy: 0.5918, prior_entropy: 0.9937, recall: 0.5918, relative_absolute_error: 0.8238, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.6389, root_relative_squared_error: 1.2838, scimark_benchmark: 936.2574, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4748, f_measure: 0.408, kappa: 0.0025, kb_relative_information_score: -0.5865, mean_absolute_error: 0.4959, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5147, predictive_accuracy: 0.5466, prior_entropy: 0.9937, recall: 0.5466, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5047, root_relative_squared_error: 1.014, scimark_benchmark: 930.404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4748, f_measure: 0.408, kappa: 0.0025, kb_relative_information_score: -0.5865, mean_absolute_error: 0.4959, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5147, predictive_accuracy: 0.5466, prior_entropy: 0.9937, recall: 0.5466, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5047, root_relative_squared_error: 1.014, scimark_benchmark: 903.2737,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4748, f_measure: 0.408, kappa: 0.0025, kb_relative_information_score: -0.5865, mean_absolute_error: 0.4959, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5147, predictive_accuracy: 0.5466, prior_entropy: 0.9937, recall: 0.5466, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5047, root_relative_squared_error: 1.014, scimark_benchmark: 933.3455,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7054, f_measure: 0.6808, kappa: 0.3542, kb_relative_information_score: 130.688, mean_absolute_error: 0.4184, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.6824, predictive_accuracy: 0.6836, prior_entropy: 0.9937, recall: 0.6836, relative_absolute_error: 0.8444, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4655, root_relative_squared_error: 0.9354, scimark_benchmark: 903.2737,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.618, f_measure: 0.5943, kappa: 0.1808, kb_relative_information_score: 47.7357, mean_absolute_error: 0.469, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5975, predictive_accuracy: 0.6014, prior_entropy: 0.9937, recall: 0.6014, relative_absolute_error: 0.9464, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4943, root_relative_squared_error: 0.9932, scimark_benchmark: 936.3213, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4748, f_measure: 0.408, kappa: 0.0025, kb_relative_information_score: -0.5865, mean_absolute_error: 0.4959, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5147, predictive_accuracy: 0.5466, prior_entropy: 0.9937, recall: 0.5466, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5047, root_relative_squared_error: 1.014, scimark_benchmark: 944.0133,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5746, f_measure: 0.5962, kappa: 0.2169, kb_relative_information_score: 90.8821, mean_absolute_error: 0.4418, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.6499, predictive_accuracy: 0.6301, prior_entropy: 0.9937, recall: 0.6301, relative_absolute_error: 0.8916, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4939, root_relative_squared_error: 0.9924, scimark_benchmark: 730.6551, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7254, f_measure: 0.7079, kappa: 0.4092, kb_relative_information_score: 173.9089, mean_absolute_error: 0.3894, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.7109, predictive_accuracy: 0.711, prior_entropy: 0.9937, recall: 0.711, relative_absolute_error: 0.7858, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4601, root_relative_squared_error: 0.9245, scimark_benchmark: 936.9595, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6544, f_measure: 0.6031, kappa: 0.2042, kb_relative_information_score: 46.4923, mean_absolute_error: 0.4705, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.6151, predictive_accuracy: 0.6164, prior_entropy: 0.9937, recall: 0.6164, relative_absolute_error: 0.9495, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4826, root_relative_squared_error: 0.9697, scimark_benchmark: 908.9569, usercpu_time_millis: 310, usercpu_time_millis_testing: 180, usercpu_time_millis_training: 130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6481, f_measure: 0.5911, kappa: 0.1823, kb_relative_information_score: 44.1275, mean_absolute_error: 0.4717, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.605, predictive_accuracy: 0.6068, prior_entropy: 0.9937, recall: 0.6068, relative_absolute_error: 0.952, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4841, root_relative_squared_error: 0.9727, scimark_benchmark: 906.5979, usercpu_time_millis: 100, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6449, f_measure: 0.5998, kappa: 0.1981, kb_relative_information_score: 45.2792, mean_absolute_error: 0.4709, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.6122, predictive_accuracy: 0.6137, prior_entropy: 0.9937, recall: 0.6137, relative_absolute_error: 0.9504, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4839, root_relative_squared_error: 0.9723, scimark_benchmark: 905.3417, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6325, f_measure: 0.5881, kappa: 0.1736, kb_relative_information_score: 44.6238, mean_absolute_error: 0.4712, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.598, predictive_accuracy: 0.6014, prior_entropy: 0.9937, recall: 0.6014, relative_absolute_error: 0.9509, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4863, root_relative_squared_error: 0.977, scimark_benchmark: 944.235, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6841, f_measure: 0.6856, kappa: 0.3638, kb_relative_information_score: 224.5845, mean_absolute_error: 0.3502, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.6865, predictive_accuracy: 0.6877, prior_entropy: 0.9937, recall: 0.6877, relative_absolute_error: 0.7067, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5002, root_relative_squared_error: 1.0051, scimark_benchmark: 889.4922, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5723, f_measure: 0.5736, kappa: 0.1494, kb_relative_information_score: 126.1867, mean_absolute_error: 0.4082, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5881, predictive_accuracy: 0.5918, prior_entropy: 0.9937, recall: 0.5918, relative_absolute_error: 0.8238, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.6389, root_relative_squared_error: 1.2838, scimark_benchmark: 1316.3384,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4748, f_measure: 0.408, kappa: 0.0025, kb_relative_information_score: -0.5865, mean_absolute_error: 0.4959, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5147, predictive_accuracy: 0.5466, prior_entropy: 0.9937, recall: 0.5466, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5047, root_relative_squared_error: 1.014, scimark_benchmark: 1340.9749,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.618, f_measure: 0.5943, kappa: 0.1808, kb_relative_information_score: 47.7357, mean_absolute_error: 0.469, mean_prior_absolute_error: 0.4955, number_of_instances: 730, precision: 0.5975, predictive_accuracy: 0.6014, prior_entropy: 0.9937, recall: 0.6014, relative_absolute_error: 0.9464, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4943, root_relative_squared_error: 0.9932, scimark_benchmark: 1332.7986, usercpu_time_millis: 20, usercpu_time_millis_training: 20,

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