OpenML
Supervised Classification on soybean

Supervised Classification on soybean

Task 1921 Supervised Classification soybean 178 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9925, f_measure: 0.8702, kappa: 0.8661, kb_relative_information_score: 5994.4568, mean_absolute_error: 0.0143, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.8932, predictive_accuracy: 0.878, prior_entropy: 3.8572, recall: 0.878, relative_absolute_error: 0.1491, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0934, root_relative_squared_error: 0.4262, scimark_benchmark: 1318.6149, usercpu_time_millis: 2790, usercpu_time_millis_testing: 2790,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9744, f_measure: 0.9151, kappa: 0.9099, kb_relative_information_score: 6248.4289, mean_absolute_error: 0.012, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9173, predictive_accuracy: 0.9179, prior_entropy: 3.8572, recall: 0.9179, relative_absolute_error: 0.1246, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0856, root_relative_squared_error: 0.3905, scimark_benchmark: 1340.1351, usercpu_time_millis: 670, usercpu_time_millis_training: 670,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9967, f_measure: 0.9336, kappa: 0.9286, kb_relative_information_score: 6421.2757, mean_absolute_error: 0.0081, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9404, predictive_accuracy: 0.9348, prior_entropy: 3.8572, recall: 0.9348, relative_absolute_error: 0.0841, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0726, root_relative_squared_error: 0.3315, scimark_benchmark: 944.0517, usercpu_time_millis: 2510, usercpu_time_millis_testing: 2350, usercpu_time_millis_training: 160,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9907, f_measure: 0.8531, kappa: 0.8528, kb_relative_information_score: 5649.9954, mean_absolute_error: 0.0284, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.8607, predictive_accuracy: 0.8665, prior_entropy: 3.8572, recall: 0.8665, relative_absolute_error: 0.2954, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.1052, root_relative_squared_error: 0.4801, scimark_benchmark: 892.0148, usercpu_time_millis: 700, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 670,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9899, f_measure: 0.8459, kappa: 0.845, kb_relative_information_score: 5627.2327, mean_absolute_error: 0.0286, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.8524, predictive_accuracy: 0.8594, prior_entropy: 3.8572, recall: 0.8594, relative_absolute_error: 0.2973, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.1067, root_relative_squared_error: 0.4871, scimark_benchmark: 1329.8902, usercpu_time_millis: 210, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.978, f_measure: 0.8314, kappa: 0.8154, kb_relative_information_score: 5443.6591, mean_absolute_error: 0.0321, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.855, predictive_accuracy: 0.8318, prior_entropy: 3.8572, recall: 0.8318, relative_absolute_error: 0.3341, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.1134, root_relative_squared_error: 0.5175, scimark_benchmark: 1342.1678, usercpu_time_millis: 860, usercpu_time_millis_training: 860,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9967, f_measure: 0.9005, kappa: 0.9004, kb_relative_information_score: 5612.9157, mean_absolute_error: 0.0334, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9166, predictive_accuracy: 0.9095, prior_entropy: 3.8572, recall: 0.9095, relative_absolute_error: 0.3476, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.099, root_relative_squared_error: 0.452, scimark_benchmark: 1327.5791, usercpu_time_millis: 930, usercpu_time_millis_testing: 110, usercpu_time_millis_training: 820,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9946, f_measure: 0.9285, kappa: 0.9223, kb_relative_information_score: 6380.6632, mean_absolute_error: 0.0085, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9369, predictive_accuracy: 0.929, prior_entropy: 3.8572, recall: 0.929, relative_absolute_error: 0.0884, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0811, root_relative_squared_error: 0.37, scimark_benchmark: 854.5188, usercpu_time_millis: 30, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9818, f_measure: 0.9164, kappa: 0.9105, kb_relative_information_score: 6200.3255, mean_absolute_error: 0.0135, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9181, predictive_accuracy: 0.9184, prior_entropy: 3.8572, recall: 0.9184, relative_absolute_error: 0.1403, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0857, root_relative_squared_error: 0.3909, scimark_benchmark: 904.3681, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9672, f_measure: 0.9415, kappa: 0.9364, kb_relative_information_score: 6436.9921, mean_absolute_error: 0.0061, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9428, predictive_accuracy: 0.942, prior_entropy: 3.8572, recall: 0.942, relative_absolute_error: 0.0635, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0781, root_relative_squared_error: 0.3565, scimark_benchmark: 1310.6407, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9377, f_measure: 0.8796, kappa: 0.8805, kb_relative_information_score: 6026.2157, mean_absolute_error: 0.0114, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.8867, predictive_accuracy: 0.8915, prior_entropy: 3.8572, recall: 0.8915, relative_absolute_error: 0.1188, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.1069, root_relative_squared_error: 0.4877, scimark_benchmark: 1322.4968, usercpu_time_millis: 380, usercpu_time_millis_testing: 180, usercpu_time_millis_training: 200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9784, f_measure: 0.5043, kappa: 0.5221, kb_relative_information_score: 3190.116, mean_absolute_error: 0.074, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.5382, predictive_accuracy: 0.5722, prior_entropy: 3.8572, recall: 0.5722, relative_absolute_error: 0.77, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.1872, root_relative_squared_error: 0.8541, scimark_benchmark: 1268.9931, usercpu_time_millis: 990, usercpu_time_millis_testing: 990,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9946, f_measure: 0.9321, kappa: 0.9263, kb_relative_information_score: 6380.0374, mean_absolute_error: 0.0087, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9396, predictive_accuracy: 0.9328, prior_entropy: 3.8572, recall: 0.9328, relative_absolute_error: 0.091, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0784, root_relative_squared_error: 0.3579, scimark_benchmark: 765.566, usercpu_time_millis: 145920, usercpu_time_millis_testing: 145920,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9434, f_measure: 0.8966, kappa: 0.8895, kb_relative_information_score: 6117.8685, mean_absolute_error: 0.0106, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9031, predictive_accuracy: 0.8993, prior_entropy: 3.8572, recall: 0.8993, relative_absolute_error: 0.1103, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.103, root_relative_squared_error: 0.47, scimark_benchmark: 1346.3935, usercpu_time_millis: 410, usercpu_time_millis_testing: 410,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9812, f_measure: 0.8741, kappa: 0.8569, kb_relative_information_score: 2520.1367, mean_absolute_error: 0.0753, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9064, predictive_accuracy: 0.8684, prior_entropy: 3.8572, recall: 0.8684, relative_absolute_error: 0.7829, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.1897, root_relative_squared_error: 0.866, scimark_benchmark: 1340.9497, usercpu_time_millis: 30, usercpu_time_millis_testing: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4842, f_measure: 0.032, kb_relative_information_score: 5.225, mean_absolute_error: 0.0961, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.0181, predictive_accuracy: 0.1347, prior_entropy: 3.8572, recall: 0.1347, relative_absolute_error: 1.0002, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.2191, root_relative_squared_error: 1.0001, scimark_benchmark: 1345.4669,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9626, f_measure: 0.8626, kappa: 0.8496, kb_relative_information_score: 942.7939, mean_absolute_error: 0.0969, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9269, predictive_accuracy: 0.863, prior_entropy: 3.8572, recall: 0.863, relative_absolute_error: 1.0083, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.2179, root_relative_squared_error: 0.9945, scimark_benchmark: 937.5996, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9582, f_measure: 0.9248, kappa: 0.9193, kb_relative_information_score: 6305.6115, mean_absolute_error: 0.0077, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9275, predictive_accuracy: 0.9265, prior_entropy: 3.8572, recall: 0.9265, relative_absolute_error: 0.0805, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.088, root_relative_squared_error: 0.4014, scimark_benchmark: 943.1756, usercpu_time_millis: 23950, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 23910,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7577, f_measure: 0.1168, kappa: 0.1514, kb_relative_information_score: 1692.9749, mean_absolute_error: 0.0868, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.1056, predictive_accuracy: 0.2631, prior_entropy: 3.8572, recall: 0.2631, relative_absolute_error: 0.9031, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.2084, root_relative_squared_error: 0.9511, scimark_benchmark: 904.3681, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9965, f_measure: 0.9012, kappa: 0.9003, kb_relative_information_score: 5605.7336, mean_absolute_error: 0.0335, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9164, predictive_accuracy: 0.9094, prior_entropy: 3.8572, recall: 0.9094, relative_absolute_error: 0.3487, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0996, root_relative_squared_error: 0.4544, scimark_benchmark: 1311.9814, usercpu_time_millis: 420, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 380,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9963, f_measure: 0.9011, kappa: 0.9001, kb_relative_information_score: 5589.4587, mean_absolute_error: 0.0338, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.917, predictive_accuracy: 0.9092, prior_entropy: 3.8572, recall: 0.9092, relative_absolute_error: 0.3515, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.1006, root_relative_squared_error: 0.4592, scimark_benchmark: 885.7425, usercpu_time_millis: 280, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 260,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9952, f_measure: 0.8944, kappa: 0.8912, kb_relative_information_score: 5552.2905, mean_absolute_error: 0.0342, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9084, predictive_accuracy: 0.9012, prior_entropy: 3.8572, recall: 0.9012, relative_absolute_error: 0.3555, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.1036, root_relative_squared_error: 0.473, scimark_benchmark: 1292.1375, usercpu_time_millis: 60, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9941, f_measure: 0.9422, kappa: 0.9366, kb_relative_information_score: 6457.3616, mean_absolute_error: 0.0067, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9433, predictive_accuracy: 0.9422, prior_entropy: 3.8572, recall: 0.9422, relative_absolute_error: 0.0694, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0705, root_relative_squared_error: 0.3215, scimark_benchmark: 1346.3935, usercpu_time_millis: 710, usercpu_time_millis_training: 710,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9958, f_measure: 0.9335, kappa: 0.9278, kb_relative_information_score: 6412.0737, mean_absolute_error: 0.0096, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9354, predictive_accuracy: 0.9341, prior_entropy: 3.8572, recall: 0.9341, relative_absolute_error: 0.0996, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0674, root_relative_squared_error: 0.3078, scimark_benchmark: 909.1698, usercpu_time_millis: 170, usercpu_time_millis_training: 170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9908, f_measure: 0.8508, kappa: 0.8502, kb_relative_information_score: 5653.0955, mean_absolute_error: 0.0284, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.8583, predictive_accuracy: 0.8641, prior_entropy: 3.8572, recall: 0.8641, relative_absolute_error: 0.2952, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.105, root_relative_squared_error: 0.4793, scimark_benchmark: 1343.2125, usercpu_time_millis: 1290, usercpu_time_millis_testing: 120, usercpu_time_millis_training: 1170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9904, f_measure: 0.8517, kappa: 0.8516, kb_relative_information_score: 5643.1842, mean_absolute_error: 0.0284, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.859, predictive_accuracy: 0.8654, prior_entropy: 3.8572, recall: 0.8654, relative_absolute_error: 0.2958, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.1057, root_relative_squared_error: 0.4823, scimark_benchmark: 1318.8785, usercpu_time_millis: 480, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 460,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9965, f_measure: 0.9372, kappa: 0.9323, kb_relative_information_score: 6423.1614, mean_absolute_error: 0.0079, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9438, predictive_accuracy: 0.9382, prior_entropy: 3.8572, recall: 0.9382, relative_absolute_error: 0.0825, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0732, root_relative_squared_error: 0.3341, scimark_benchmark: 765.566, usercpu_time_millis: 30, usercpu_time_millis_testing: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9356, f_measure: 0.8642, kappa: 0.8518, kb_relative_information_score: 5917.7443, mean_absolute_error: 0.0151, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.8647, predictive_accuracy: 0.8649, prior_entropy: 3.8572, recall: 0.8649, relative_absolute_error: 0.1567, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.1151, root_relative_squared_error: 0.5254, scimark_benchmark: 1342.7245, usercpu_time_millis: 100, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9356, f_measure: 0.8642, kappa: 0.8518, kb_relative_information_score: 5917.7443, mean_absolute_error: 0.0151, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.8647, predictive_accuracy: 0.8649, prior_entropy: 3.8572, recall: 0.8649, relative_absolute_error: 0.1567, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.1151, root_relative_squared_error: 0.5254, scimark_benchmark: 1341.994, usercpu_time_millis: 130, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9818, f_measure: 0.9164, kappa: 0.9105, kb_relative_information_score: 6200.3255, mean_absolute_error: 0.0135, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9181, predictive_accuracy: 0.9184, prior_entropy: 3.8572, recall: 0.9184, relative_absolute_error: 0.1403, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0857, root_relative_squared_error: 0.3909, scimark_benchmark: 1339.7143, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9945, f_measure: 0.9266, kappa: 0.9202, kb_relative_information_score: 6345.8256, mean_absolute_error: 0.0095, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9357, predictive_accuracy: 0.9272, prior_entropy: 3.8572, recall: 0.9272, relative_absolute_error: 0.0991, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0819, root_relative_squared_error: 0.3738, scimark_benchmark: 922.1419, usercpu_time_millis: 20, usercpu_time_millis_testing: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9256, f_measure: 0.403, kappa: 0.448, kb_relative_information_score: 2070.6752, mean_absolute_error: 0.0802, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.3431, predictive_accuracy: 0.5161, prior_entropy: 3.8572, recall: 0.5161, relative_absolute_error: 0.8339, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.1887, root_relative_squared_error: 0.8611, scimark_benchmark: 937.5996, usercpu_time_millis: 2560, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 2550,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9857, f_measure: 0.9328, kappa: 0.9263, kb_relative_information_score: 6410.4931, mean_absolute_error: 0.0073, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9334, predictive_accuracy: 0.9328, prior_entropy: 3.8572, recall: 0.9328, relative_absolute_error: 0.0757, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0782, root_relative_squared_error: 0.3568, scimark_benchmark: 854.5188, usercpu_time_millis: 26740, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 26720,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9757, f_measure: 0.9124, kappa: 0.9057, kb_relative_information_score: 6234.0596, mean_absolute_error: 0.0121, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9171, predictive_accuracy: 0.9141, prior_entropy: 3.8572, recall: 0.9141, relative_absolute_error: 0.1262, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0878, root_relative_squared_error: 0.4009, scimark_benchmark: 1307.3269, usercpu_time_millis: 80, usercpu_time_millis_testing: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9742, f_measure: 0.8441, kappa: 0.8242, kb_relative_information_score: 3840.4915, mean_absolute_error: 0.0658, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.8791, predictive_accuracy: 0.84, prior_entropy: 3.8572, recall: 0.84, relative_absolute_error: 0.6846, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.1584, root_relative_squared_error: 0.723, scimark_benchmark: 1335.693, usercpu_time_millis: 540, usercpu_time_millis_training: 540,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7971, f_measure: 0.1595, kappa: 0.1942, kb_relative_information_score: 2200.9079, mean_absolute_error: 0.0826, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.1327, predictive_accuracy: 0.2796, prior_entropy: 3.8572, recall: 0.2796, relative_absolute_error: 0.8597, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.2033, root_relative_squared_error: 0.9279, scimark_benchmark: 1353.1316,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9961, build_cpu_time: 7.9025, build_memory: 1624433110.8111, f_measure: 0.9327, kappa: 0.9275, kb_relative_information_score: 6335.5201, mean_absolute_error: 0.0121, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9376, predictive_accuracy: 0.934, prior_entropy: 3.8572, recall: 0.934, relative_absolute_error: 0.1258, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0699, root_relative_squared_error: 0.3192, scimark_benchmark: 942.9216,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9963, build_cpu_time: 1.0467, build_memory: 992137769.7394, f_measure: 0.9349, kappa: 0.9292, kb_relative_information_score: 6265.8418, mean_absolute_error: 0.0145, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9364, predictive_accuracy: 0.9354, prior_entropy: 3.8572, recall: 0.9354, relative_absolute_error: 0.1504, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0751, root_relative_squared_error: 0.3428, scimark_benchmark: 946.8404,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.996, build_cpu_time: 0.5163, build_memory: 858515051.3921, f_measure: 0.9342, kappa: 0.9284, kb_relative_information_score: 6265.6941, mean_absolute_error: 0.0144, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9357, predictive_accuracy: 0.9347, prior_entropy: 3.8572, recall: 0.9347, relative_absolute_error: 0.1502, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0752, root_relative_squared_error: 0.3431, scimark_benchmark: 942.5976,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.996, build_cpu_time: 0.4897, build_memory: 213363168.9288, f_measure: 0.9342, kappa: 0.9284, kb_relative_information_score: 6265.6941, mean_absolute_error: 0.0144, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9357, predictive_accuracy: 0.9347, prior_entropy: 3.8572, recall: 0.9347, relative_absolute_error: 0.1502, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0752, root_relative_squared_error: 0.3431, scimark_benchmark: 931.3016,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9958, build_cpu_time: 0.2511, build_memory: 1832783826.0322, f_measure: 0.9309, kappa: 0.925, kb_relative_information_score: 6261.7771, mean_absolute_error: 0.0145, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9326, predictive_accuracy: 0.9316, prior_entropy: 3.8572, recall: 0.9316, relative_absolute_error: 0.1509, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0758, root_relative_squared_error: 0.3458, scimark_benchmark: 932.8249,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9951, build_cpu_time: 0.1271, build_memory: 471948180.4275, f_measure: 0.9293, kappa: 0.9233, kb_relative_information_score: 6255.7346, mean_absolute_error: 0.0145, mean_prior_absolute_error: 0.0961, number_of_instances: 6830, precision: 0.9312, predictive_accuracy: 0.93, prior_entropy: 3.8572, recall: 0.93, relative_absolute_error: 0.151, root_mean_prior_squared_error: 0.2191, root_mean_squared_error: 0.0767, root_relative_squared_error: 0.3503, scimark_benchmark: 927.8742,

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