OpenML
Supervised Classification on analcatdata_broadwaymult

Supervised Classification on analcatdata_broadwaymult

Task 3824 Supervised Classification analcatdata_broadwaymult 506 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8385, f_measure: 0.7556, kappa: 0.4935, kb_relative_information_score: 42.3549, mean_absolute_error: 0.4288, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7722, predictive_accuracy: 0.7649, prior_entropy: 0.9789, recall: 0.7649, relative_absolute_error: 0.8836, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.442, root_relative_squared_error: 0.8974, scimark_benchmark: 860.584, usercpu_time_millis: 130, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8504, f_measure: 0.753, kappa: 0.4895, kb_relative_information_score: 46.1668, mean_absolute_error: 0.4237, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.778, predictive_accuracy: 0.7649, prior_entropy: 0.9789, recall: 0.7649, relative_absolute_error: 0.873, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4374, root_relative_squared_error: 0.888, scimark_benchmark: 1363.454, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8541, f_measure: 0.769, kappa: 0.5205, kb_relative_information_score: 63.1071, mean_absolute_error: 0.3977, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.779, predictive_accuracy: 0.7754, prior_entropy: 0.9789, recall: 0.7754, relative_absolute_error: 0.8194, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4192, root_relative_squared_error: 0.8511, scimark_benchmark: 860.584, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6219, f_measure: 0.549, kappa: 0.0674, kb_relative_information_score: 36.3853, mean_absolute_error: 0.4133, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.5476, predictive_accuracy: 0.5509, prior_entropy: 0.9789, recall: 0.5509, relative_absolute_error: 0.8515, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.5431, root_relative_squared_error: 1.1027, scimark_benchmark: 942.6843, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3515, f_measure: 0.4357, kappa: -0.1717, kb_relative_information_score: -39.4619, mean_absolute_error: 0.5401, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.4284, predictive_accuracy: 0.4491, prior_entropy: 0.9789, recall: 0.4491, relative_absolute_error: 1.1129, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.581, root_relative_squared_error: 1.1795, scimark_benchmark: 1339.3974, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7856, f_measure: 0.767, kappa: 0.5161, kb_relative_information_score: 105.6623, mean_absolute_error: 0.317, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7728, predictive_accuracy: 0.7719, prior_entropy: 0.9789, recall: 0.7719, relative_absolute_error: 0.6532, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4006, root_relative_squared_error: 0.8134, scimark_benchmark: 1297.6356,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8168, f_measure: 0.7895, kappa: 0.5661, kb_relative_information_score: 107.8761, mean_absolute_error: 0.3145, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7895, predictive_accuracy: 0.7895, prior_entropy: 0.9789, recall: 0.7895, relative_absolute_error: 0.6481, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.411, root_relative_squared_error: 0.8344, scimark_benchmark: 1318.1432, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8198, f_measure: 0.7892, kappa: 0.565, kb_relative_information_score: 107.182, mean_absolute_error: 0.3156, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.789, predictive_accuracy: 0.7895, prior_entropy: 0.9789, recall: 0.7895, relative_absolute_error: 0.6503, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4091, root_relative_squared_error: 0.8305, scimark_benchmark: 908.2231, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8224, f_measure: 0.7745, kappa: 0.5337, kb_relative_information_score: 107.1468, mean_absolute_error: 0.3159, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7742, predictive_accuracy: 0.7754, prior_entropy: 0.9789, recall: 0.7754, relative_absolute_error: 0.6509, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4072, root_relative_squared_error: 0.8267, scimark_benchmark: 882.7843, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8243, f_measure: 0.7641, kappa: 0.5125, kb_relative_information_score: 108.7316, mean_absolute_error: 0.3133, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7638, predictive_accuracy: 0.7649, prior_entropy: 0.9789, recall: 0.7649, relative_absolute_error: 0.6455, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4049, root_relative_squared_error: 0.822, scimark_benchmark: 942.9518, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8225, f_measure: 0.7641, kappa: 0.5125, kb_relative_information_score: 108.3111, mean_absolute_error: 0.314, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7638, predictive_accuracy: 0.7649, prior_entropy: 0.9789, recall: 0.7649, relative_absolute_error: 0.647, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4055, root_relative_squared_error: 0.8233, scimark_benchmark: 1324.8395, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7222, f_measure: 0.6953, kappa: 0.3672, kb_relative_information_score: 61.5562, mean_absolute_error: 0.3896, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.6984, predictive_accuracy: 0.7018, prior_entropy: 0.9789, recall: 0.7018, relative_absolute_error: 0.8029, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4638, root_relative_squared_error: 0.9416, scimark_benchmark: 1442.7264, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5773, f_measure: 0.599, kappa: 0.1673, kb_relative_information_score: 25.4228, mean_absolute_error: 0.4434, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.5982, predictive_accuracy: 0.607, prior_entropy: 0.9789, recall: 0.607, relative_absolute_error: 0.9137, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.5247, root_relative_squared_error: 1.0653, scimark_benchmark: 1304.9611,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7562, f_measure: 0.7714, kappa: 0.5254, kb_relative_information_score: 151.3598, mean_absolute_error: 0.2246, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7754, predictive_accuracy: 0.7754, prior_entropy: 0.9789, recall: 0.7754, relative_absolute_error: 0.4627, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4739, root_relative_squared_error: 0.9621, scimark_benchmark: 1363.454, usercpu_time_millis: 90, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7507, f_measure: 0.767, kappa: 0.5161, kb_relative_information_score: 149.273, mean_absolute_error: 0.2281, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7728, predictive_accuracy: 0.7719, prior_entropy: 0.9789, recall: 0.7719, relative_absolute_error: 0.4699, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4776, root_relative_squared_error: 0.9696, scimark_benchmark: 869.6028, usercpu_time_millis: 100, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7728, f_measure: 0.7791, kappa: 0.545, kb_relative_information_score: 153.4466, mean_absolute_error: 0.2211, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7792, predictive_accuracy: 0.7789, prior_entropy: 0.9789, recall: 0.7789, relative_absolute_error: 0.4555, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4702, root_relative_squared_error: 0.9545, scimark_benchmark: 1287.514, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8157, f_measure: 0.7923, kappa: 0.5707, kb_relative_information_score: 106.3666, mean_absolute_error: 0.3181, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7921, predictive_accuracy: 0.793, prior_entropy: 0.9789, recall: 0.793, relative_absolute_error: 0.6554, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4087, root_relative_squared_error: 0.8297, scimark_benchmark: 938.343, usercpu_time_millis: 150, usercpu_time_millis_training: 150,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6665, f_measure: 0.6452, kappa: 0.3132, kb_relative_information_score: 74.1492, mean_absolute_error: 0.3544, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.6875, predictive_accuracy: 0.6456, prior_entropy: 0.9789, recall: 0.6456, relative_absolute_error: 0.7302, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.5953, root_relative_squared_error: 1.2086, scimark_benchmark: 942.6843, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5564, f_measure: 0.5336, kappa: 0.0322, kb_relative_information_score: 4.5694, mean_absolute_error: 0.469, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.5307, predictive_accuracy: 0.5404, prior_entropy: 0.9789, recall: 0.5404, relative_absolute_error: 0.9665, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.5789, root_relative_squared_error: 1.1752, scimark_benchmark: 917.9672, usercpu_time_millis: 240, usercpu_time_millis_testing: 70, usercpu_time_millis_training: 170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7709, f_measure: 0.6959, kappa: 0.369, kb_relative_information_score: 74.4892, mean_absolute_error: 0.3666, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7034, predictive_accuracy: 0.7053, prior_entropy: 0.9789, recall: 0.7053, relative_absolute_error: 0.7555, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4403, root_relative_squared_error: 0.894, scimark_benchmark: 1337.7959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4655, f_measure: 0.5394, kappa: 0.0492, kb_relative_information_score: -16.8478, mean_absolute_error: 0.5156, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.5386, predictive_accuracy: 0.5404, prior_entropy: 0.9789, recall: 0.5404, relative_absolute_error: 1.0623, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.6335, root_relative_squared_error: 1.2861, scimark_benchmark: 1073.494, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4662, f_measure: 0.5471, kappa: 0.066, kb_relative_information_score: -11.3475, mean_absolute_error: 0.5052, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.5468, predictive_accuracy: 0.5474, prior_entropy: 0.9789, recall: 0.5474, relative_absolute_error: 1.0409, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.6312, root_relative_squared_error: 1.2815, scimark_benchmark: 1368.9272,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8046, f_measure: 0.7723, kappa: 0.5317, kb_relative_information_score: 103.1555, mean_absolute_error: 0.322, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7729, predictive_accuracy: 0.7719, prior_entropy: 0.9789, recall: 0.7719, relative_absolute_error: 0.6634, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4206, root_relative_squared_error: 0.8538, scimark_benchmark: 1304.6687, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5752, f_measure: 0.544, kappa: 0.055, kb_relative_information_score: 14.7931, mean_absolute_error: 0.4586, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.5435, predictive_accuracy: 0.5614, prior_entropy: 0.9789, recall: 0.5614, relative_absolute_error: 0.945, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4942, root_relative_squared_error: 1.0034, scimark_benchmark: 1280.6952, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3526, f_measure: 0.3526, kappa: -0.2163, kb_relative_information_score: -59.3501, mean_absolute_error: 0.5775, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.3845, predictive_accuracy: 0.3614, prior_entropy: 0.9789, recall: 0.3614, relative_absolute_error: 1.1899, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.675, root_relative_squared_error: 1.3704, scimark_benchmark: 825.5282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4869, f_measure: 0.433, kb_relative_information_score: 0.0293, mean_absolute_error: 0.4853, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.3434, predictive_accuracy: 0.586, prior_entropy: 0.9789, recall: 0.586, relative_absolute_error: 0.9999, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4926, root_relative_squared_error: 1.0001, scimark_benchmark: 1306.6379,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7239, f_measure: 0.7161, kappa: 0.4112, kb_relative_information_score: 93.2819, mean_absolute_error: 0.3333, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7165, predictive_accuracy: 0.7193, prior_entropy: 0.9789, recall: 0.7193, relative_absolute_error: 0.6867, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4784, root_relative_squared_error: 0.9713, scimark_benchmark: 1310.8451, usercpu_time_millis: 140, usercpu_time_millis_training: 140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6731, f_measure: 0.6877, kappa: 0.3524, kb_relative_information_score: 101.2772, mean_absolute_error: 0.3088, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.6876, predictive_accuracy: 0.6912, prior_entropy: 0.9789, recall: 0.6912, relative_absolute_error: 0.6362, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.5557, root_relative_squared_error: 1.1281, scimark_benchmark: 1341.5768, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4493, f_measure: 0.372, kappa: -0.0906, kb_relative_information_score: -67.7513, mean_absolute_error: 0.593, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.4425, predictive_accuracy: 0.407, prior_entropy: 0.9789, recall: 0.407, relative_absolute_error: 1.2218, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.7701, root_relative_squared_error: 1.5634, scimark_benchmark: 1308.9788, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7665, f_measure: 0.6704, kappa: 0.3585, kb_relative_information_score: 84.3347, mean_absolute_error: 0.3403, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7097, predictive_accuracy: 0.6702, prior_entropy: 0.9789, recall: 0.6702, relative_absolute_error: 0.7012, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4223, root_relative_squared_error: 0.8574, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7507, f_measure: 0.767, kappa: 0.5161, kb_relative_information_score: 149.273, mean_absolute_error: 0.2281, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7728, predictive_accuracy: 0.7719, prior_entropy: 0.9789, recall: 0.7719, relative_absolute_error: 0.4699, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4776, root_relative_squared_error: 0.9696, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7492, f_measure: 0.76, kappa: 0.5033, kb_relative_information_score: 143.0127, mean_absolute_error: 0.2386, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7598, predictive_accuracy: 0.7614, prior_entropy: 0.9789, recall: 0.7614, relative_absolute_error: 0.4916, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4885, root_relative_squared_error: 0.9917, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4869, f_measure: 0.433, kb_relative_information_score: -0.0631, mean_absolute_error: 0.4854, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.3434, predictive_accuracy: 0.586, prior_entropy: 0.9789, recall: 0.586, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4926, root_relative_squared_error: 1.0001, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7544, f_measure: 0.7694, kappa: 0.5274, kb_relative_information_score: 114.4002, mean_absolute_error: 0.3014, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7715, predictive_accuracy: 0.7684, prior_entropy: 0.9789, recall: 0.7684, relative_absolute_error: 0.621, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4371, root_relative_squared_error: 0.8875, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7413, f_measure: 0.7181, kappa: 0.4171, kb_relative_information_score: 114.599, mean_absolute_error: 0.2876, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7176, predictive_accuracy: 0.7193, prior_entropy: 0.9789, recall: 0.7193, relative_absolute_error: 0.5927, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.5078, root_relative_squared_error: 1.0309, scimark_benchmark: 927.0753, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6509, f_measure: 0.6476, kappa: 0.2686, kb_relative_information_score: 72.3111, mean_absolute_error: 0.3596, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.6472, predictive_accuracy: 0.6526, prior_entropy: 0.9789, recall: 0.6526, relative_absolute_error: 0.7409, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.5622, root_relative_squared_error: 1.1413, scimark_benchmark: 941.7954, usercpu_time_millis: 60, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6111, f_measure: 0.6088, kappa: 0.1884, kb_relative_information_score: 48.3856, mean_absolute_error: 0.4, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.6075, predictive_accuracy: 0.614, prior_entropy: 0.9789, recall: 0.614, relative_absolute_error: 0.8241, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.5755, root_relative_squared_error: 1.1684, scimark_benchmark: 923.7642, usercpu_time_millis: 90, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5973, f_measure: 0.5906, kappa: 0.1504, kb_relative_information_score: 42.4276, mean_absolute_error: 0.4089, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.5889, predictive_accuracy: 0.5965, prior_entropy: 0.9789, recall: 0.5965, relative_absolute_error: 0.8425, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.5823, root_relative_squared_error: 1.1822, scimark_benchmark: 894.7455, usercpu_time_millis: 80, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8123, f_measure: 0.7782, kappa: 0.5416, kb_relative_information_score: 147.008, mean_absolute_error: 0.2353, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7779, predictive_accuracy: 0.7789, prior_entropy: 0.9789, recall: 0.7789, relative_absolute_error: 0.4849, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4445, root_relative_squared_error: 0.9025, scimark_benchmark: 936.7115, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.606, build_cpu_time: 0.0041, build_memory: 336799991.6351, f_measure: 0.5696, kappa: 0.116, kb_relative_information_score: 16.2482, mean_absolute_error: 0.4565, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.5712, predictive_accuracy: 0.5684, prior_entropy: 0.9789, recall: 0.5684, relative_absolute_error: 0.9407, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.5562, root_relative_squared_error: 1.1292, scimark_benchmark: 943.5504,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6445, build_cpu_time: 0.0116, build_memory: 1115508733.3053, f_measure: 0.6379, kappa: 0.2481, kb_relative_information_score: 64.2027, mean_absolute_error: 0.3757, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.6388, predictive_accuracy: 0.6456, prior_entropy: 0.9789, recall: 0.6456, relative_absolute_error: 0.7742, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.5431, root_relative_squared_error: 1.1025, scimark_benchmark: 929.5397,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6059, build_cpu_time: 0.0186, build_memory: 763335286.9614, f_measure: 0.5887, kappa: 0.1461, kb_relative_information_score: 45.3641, mean_absolute_error: 0.4036, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.5874, predictive_accuracy: 0.5965, prior_entropy: 0.9789, recall: 0.5965, relative_absolute_error: 0.8317, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.5737, root_relative_squared_error: 1.1647, scimark_benchmark: 929.5397,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5959, build_cpu_time: 0.0228, build_memory: 667433867.4246, f_measure: 0.5825, kappa: 0.1335, kb_relative_information_score: 40.6418, mean_absolute_error: 0.4114, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.5809, predictive_accuracy: 0.5895, prior_entropy: 0.9789, recall: 0.5895, relative_absolute_error: 0.8477, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.5832, root_relative_squared_error: 1.184, scimark_benchmark: 929.5397,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5923, build_cpu_time: 0.0274, build_memory: 574114444.9965, f_measure: 0.5825, kappa: 0.1335, kb_relative_information_score: 39.6061, mean_absolute_error: 0.4133, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.5809, predictive_accuracy: 0.5895, prior_entropy: 0.9789, recall: 0.5895, relative_absolute_error: 0.8516, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.5854, root_relative_squared_error: 1.1884, scimark_benchmark: 943.2074,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5923, build_cpu_time: 0.0311, build_memory: 1721516010.9754, f_measure: 0.5825, kappa: 0.1335, kb_relative_information_score: 39.6061, mean_absolute_error: 0.4133, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.5809, predictive_accuracy: 0.5895, prior_entropy: 0.9789, recall: 0.5895, relative_absolute_error: 0.8516, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.5854, root_relative_squared_error: 1.1884, scimark_benchmark: 943.5504,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8063, build_cpu_time: 1.61, build_memory: 728450257.1228, f_measure: 0.7446, kappa: 0.4754, kb_relative_information_score: 128.376, mean_absolute_error: 0.2672, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.7457, predictive_accuracy: 0.7439, prior_entropy: 0.9789, recall: 0.7439, relative_absolute_error: 0.5506, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4474, root_relative_squared_error: 0.9084, scimark_benchmark: 943.7751,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8033, build_cpu_time: 3.4212, build_memory: 30598409.7684, f_measure: 0.7822, kappa: 0.5505, kb_relative_information_score: 140.3595, mean_absolute_error: 0.2468, mean_prior_absolute_error: 0.4853, number_of_instances: 285, precision: 0.782, predictive_accuracy: 0.7825, prior_entropy: 0.9789, recall: 0.7825, relative_absolute_error: 0.5085, root_mean_prior_squared_error: 0.4926, root_mean_squared_error: 0.4513, root_relative_squared_error: 0.9163, scimark_benchmark: 939.521,

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

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From your own software

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

OpenML APIs