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Supervised Classification on fri_c2_500_5

Supervised Classification on fri_c2_500_5

Task 4362 Supervised Classification fri_c2_500_5 237 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9535, f_measure: 0.8871, kappa: 0.7657, kb_relative_information_score: 3307.2458, mean_absolute_error: 0.1708, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8872, predictive_accuracy: 0.887, prior_entropy: 0.9735, recall: 0.887, relative_absolute_error: 0.3546, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2853, root_relative_squared_error: 0.5815, scimark_benchmark: 1363.454, usercpu_time_millis: 30, usercpu_time_millis_testing: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9429, f_measure: 0.8929, kappa: 0.7774, kb_relative_information_score: 3449.8225, mean_absolute_error: 0.1537, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8928, predictive_accuracy: 0.893, prior_entropy: 0.9735, recall: 0.893, relative_absolute_error: 0.3191, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2906, root_relative_squared_error: 0.5921, scimark_benchmark: 942.9518, usercpu_time_millis: 30, usercpu_time_millis_testing: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6774, f_measure: 0.6671, kappa: 0.3374, kb_relative_information_score: 1458.7426, mean_absolute_error: 0.3356, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.6923, predictive_accuracy: 0.6644, prior_entropy: 0.9735, recall: 0.6644, relative_absolute_error: 0.6968, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.5793, root_relative_squared_error: 1.1806, scimark_benchmark: 1404.1865, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4451, kb_relative_information_score: 737.2083, mean_absolute_error: 0.404, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.3552, predictive_accuracy: 0.596, prior_entropy: 0.9735, recall: 0.596, relative_absolute_error: 0.8388, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.6356, root_relative_squared_error: 1.2953, scimark_benchmark: 1336.3256, usercpu_time_millis: 370, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 340,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7307, f_measure: 0.739, kappa: 0.4593, kb_relative_information_score: 2239.35, mean_absolute_error: 0.2616, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.7397, predictive_accuracy: 0.7384, prior_entropy: 0.9735, recall: 0.7384, relative_absolute_error: 0.5431, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.5115, root_relative_squared_error: 1.0423, scimark_benchmark: 1297.6356, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7228, f_measure: 0.734, kappa: 0.4437, kb_relative_information_score: 818.9913, mean_absolute_error: 0.4178, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.7345, predictive_accuracy: 0.7374, prior_entropy: 0.9735, recall: 0.7374, relative_absolute_error: 0.8674, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.4518, root_relative_squared_error: 0.9206, scimark_benchmark: 918.6005, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6881, f_measure: 0.7014, kappa: 0.3784, kb_relative_information_score: 1859.5951, mean_absolute_error: 0.2976, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.7008, predictive_accuracy: 0.7024, prior_entropy: 0.9735, recall: 0.7024, relative_absolute_error: 0.6179, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.5455, root_relative_squared_error: 1.1117, scimark_benchmark: 869.6028, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8191, f_measure: 0.75, kappa: 0.4812, kb_relative_information_score: 1479.6461, mean_absolute_error: 0.3499, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.7502, predictive_accuracy: 0.7498, prior_entropy: 0.9735, recall: 0.7498, relative_absolute_error: 0.7264, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.4125, root_relative_squared_error: 0.8407, scimark_benchmark: 1368.9272, usercpu_time_millis: 930, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 900,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9734, f_measure: 0.9125, kappa: 0.8175, kb_relative_information_score: 3700.7514, mean_absolute_error: 0.1326, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9132, predictive_accuracy: 0.913, prior_entropy: 0.9735, recall: 0.913, relative_absolute_error: 0.2753, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2487, root_relative_squared_error: 0.5069, scimark_benchmark: 1319.5177, usercpu_time_millis: 90, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8776, f_measure: 0.8818, kappa: 0.7547, kb_relative_information_score: 3752.0405, mean_absolute_error: 0.1182, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8819, predictive_accuracy: 0.8818, prior_entropy: 0.9735, recall: 0.8818, relative_absolute_error: 0.2454, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3438, root_relative_squared_error: 0.7006, scimark_benchmark: 1325.942,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8903, f_measure: 0.8722, kappa: 0.7331, kb_relative_information_score: 3235.7729, mean_absolute_error: 0.1807, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8733, predictive_accuracy: 0.8732, prior_entropy: 0.9735, recall: 0.8732, relative_absolute_error: 0.3751, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3285, root_relative_squared_error: 0.6695, scimark_benchmark: 1361.1055,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8721, f_measure: 0.87, kappa: 0.7285, kb_relative_information_score: 3265.0944, mean_absolute_error: 0.1766, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.871, predictive_accuracy: 0.871, prior_entropy: 0.9735, recall: 0.871, relative_absolute_error: 0.3667, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3383, root_relative_squared_error: 0.6895, scimark_benchmark: 1308.9788, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8643, f_measure: 0.8721, kappa: 0.7336, kb_relative_information_score: 3654.992, mean_absolute_error: 0.1274, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8722, predictive_accuracy: 0.8726, prior_entropy: 0.9735, recall: 0.8726, relative_absolute_error: 0.2645, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3569, root_relative_squared_error: 0.7274, scimark_benchmark: 1321.9426, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5115, f_measure: 0.3981, kappa: 0.0197, kb_relative_information_score: -798.6894, mean_absolute_error: 0.5496, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.5391, predictive_accuracy: 0.4504, prior_entropy: 0.9735, recall: 0.4504, relative_absolute_error: 1.1411, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.7414, root_relative_squared_error: 1.5108, scimark_benchmark: 1380.0066, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9111, f_measure: 0.8638, kappa: 0.7165, kb_relative_information_score: 3414.8654, mean_absolute_error: 0.1548, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8637, predictive_accuracy: 0.8642, prior_entropy: 0.9735, recall: 0.8642, relative_absolute_error: 0.3214, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3325, root_relative_squared_error: 0.6775, scimark_benchmark: 1330.0803,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7976, f_measure: 0.8092, kappa: 0.6018, kb_relative_information_score: 2998.8599, mean_absolute_error: 0.1896, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8093, predictive_accuracy: 0.8104, prior_entropy: 0.9735, recall: 0.8104, relative_absolute_error: 0.3937, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.4354, root_relative_squared_error: 0.8874, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8674, f_measure: 0.8753, kappa: 0.7402, kb_relative_information_score: 3688.748, mean_absolute_error: 0.1242, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8754, predictive_accuracy: 0.8758, prior_entropy: 0.9735, recall: 0.8758, relative_absolute_error: 0.2579, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3524, root_relative_squared_error: 0.7182, scimark_benchmark: 1341.2341, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4934, f_measure: 0.4451, kb_relative_information_score: -0.733, mean_absolute_error: 0.4817, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.3552, predictive_accuracy: 0.596, prior_entropy: 0.9735, recall: 0.596, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.4907, root_relative_squared_error: 1, scimark_benchmark: 1335.643,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.901, f_measure: 0.8846, kappa: 0.7598, kb_relative_information_score: 3660.1406, mean_absolute_error: 0.131, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.8845, predictive_accuracy: 0.8848, prior_entropy: 0.9735, recall: 0.8848, relative_absolute_error: 0.2719, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.3251, root_relative_squared_error: 0.6624, scimark_benchmark: 1392.1129,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9705, build_cpu_time: 17.1328, build_memory: 133374851.76, f_measure: 0.9078, kappa: 0.8076, kb_relative_information_score: 3588.8613, mean_absolute_error: 0.1469, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9087, predictive_accuracy: 0.9084, prior_entropy: 0.9735, recall: 0.9084, relative_absolute_error: 0.305, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2559, root_relative_squared_error: 0.5214, scimark_benchmark: 942.5482,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9339, build_cpu_time: 2.5152, build_memory: 270755918.32, f_measure: 0.921, kappa: 0.8357, kb_relative_information_score: 4172.7636, mean_absolute_error: 0.0783, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9211, predictive_accuracy: 0.9212, prior_entropy: 0.9735, recall: 0.9212, relative_absolute_error: 0.1625, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.277, root_relative_squared_error: 0.5645, scimark_benchmark: 890.4487,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9405, build_cpu_time: 1.0128, build_memory: 960553739.68, f_measure: 0.9194, kappa: 0.8323, kb_relative_information_score: 4154.0158, mean_absolute_error: 0.08, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9195, predictive_accuracy: 0.9196, prior_entropy: 0.9735, recall: 0.9196, relative_absolute_error: 0.1661, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2782, root_relative_squared_error: 0.567, scimark_benchmark: 938.0657,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9487, build_cpu_time: 0.6286, build_memory: 703549781.6, f_measure: 0.9185, kappa: 0.8304, kb_relative_information_score: 4141.0899, mean_absolute_error: 0.0813, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9187, predictive_accuracy: 0.9188, prior_entropy: 0.9735, recall: 0.9188, relative_absolute_error: 0.1689, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.279, root_relative_squared_error: 0.5686, scimark_benchmark: 939.9671,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9515, build_cpu_time: 0.2932, build_memory: 48364641.04, f_measure: 0.9139, kappa: 0.8205, kb_relative_information_score: 4079.101, mean_absolute_error: 0.0875, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9141, predictive_accuracy: 0.9142, prior_entropy: 0.9735, recall: 0.9142, relative_absolute_error: 0.1816, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2872, root_relative_squared_error: 0.5852, scimark_benchmark: 942.9632,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9693, build_cpu_time: 0.9463, build_memory: 2338502211.2, f_measure: 0.8979, kappa: 0.7864, kb_relative_information_score: 3623.4238, mean_absolute_error: 0.14, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9014, predictive_accuracy: 0.8992, prior_entropy: 0.9735, recall: 0.8992, relative_absolute_error: 0.2907, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2624, root_relative_squared_error: 0.5348, scimark_benchmark: 946.8017,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9707, build_cpu_time: 2.1293, build_memory: 198747288.4, f_measure: 0.8982, kappa: 0.7871, kb_relative_information_score: 3624.2503, mean_absolute_error: 0.1402, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9021, predictive_accuracy: 0.8996, prior_entropy: 0.9735, recall: 0.8996, relative_absolute_error: 0.291, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2615, root_relative_squared_error: 0.5329, scimark_benchmark: 939.7152,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9662, build_cpu_time: 0.3852, build_memory: 103864893.76, f_measure: 0.9043, kappa: 0.8003, kb_relative_information_score: 3682.4865, mean_absolute_error: 0.1332, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9054, predictive_accuracy: 0.905, prior_entropy: 0.9735, recall: 0.905, relative_absolute_error: 0.2766, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2622, root_relative_squared_error: 0.5343, scimark_benchmark: 937.8951,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9662, build_cpu_time: 0.3965, build_memory: 119553318.64, f_measure: 0.9043, kappa: 0.8003, kb_relative_information_score: 3682.4865, mean_absolute_error: 0.1332, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9054, predictive_accuracy: 0.905, prior_entropy: 0.9735, recall: 0.905, relative_absolute_error: 0.2766, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2622, root_relative_squared_error: 0.5343, scimark_benchmark: 940.7554,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9652, build_cpu_time: 0.2135, build_memory: 719271364.64, f_measure: 0.9049, kappa: 0.8016, kb_relative_information_score: 3682.7883, mean_absolute_error: 0.1331, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.906, predictive_accuracy: 0.9056, prior_entropy: 0.9735, recall: 0.9056, relative_absolute_error: 0.2764, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2629, root_relative_squared_error: 0.5358, scimark_benchmark: 946.7913,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9652, build_cpu_time: 0.2008, build_memory: 87671758.88, f_measure: 0.9049, kappa: 0.8016, kb_relative_information_score: 3682.7883, mean_absolute_error: 0.1331, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.906, predictive_accuracy: 0.9056, prior_entropy: 0.9735, recall: 0.9056, relative_absolute_error: 0.2764, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2629, root_relative_squared_error: 0.5358, scimark_benchmark: 936.2783,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9652, build_cpu_time: 0.1785, build_memory: 143057258, f_measure: 0.9049, kappa: 0.8016, kb_relative_information_score: 3682.7883, mean_absolute_error: 0.1331, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.906, predictive_accuracy: 0.9056, prior_entropy: 0.9735, recall: 0.9056, relative_absolute_error: 0.2764, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2629, root_relative_squared_error: 0.5358, scimark_benchmark: 942.1365,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9634, build_cpu_time: 0.1291, build_memory: 162721646, f_measure: 0.9049, kappa: 0.8015, kb_relative_information_score: 3682.1338, mean_absolute_error: 0.1331, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9061, predictive_accuracy: 0.9056, prior_entropy: 0.9735, recall: 0.9056, relative_absolute_error: 0.2762, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2642, root_relative_squared_error: 0.5384, scimark_benchmark: 920.6872,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9634, build_cpu_time: 0.1297, build_memory: 516498992.72, f_measure: 0.9049, kappa: 0.8015, kb_relative_information_score: 3682.1338, mean_absolute_error: 0.1331, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9061, predictive_accuracy: 0.9056, prior_entropy: 0.9735, recall: 0.9056, relative_absolute_error: 0.2762, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2642, root_relative_squared_error: 0.5384, scimark_benchmark: 947.2889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9634, build_cpu_time: 0.1025, build_memory: 1414438741.44, f_measure: 0.9049, kappa: 0.8015, kb_relative_information_score: 3682.1338, mean_absolute_error: 0.1331, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9061, predictive_accuracy: 0.9056, prior_entropy: 0.9735, recall: 0.9056, relative_absolute_error: 0.2762, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2642, root_relative_squared_error: 0.5384, scimark_benchmark: 942.4004,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9604, build_cpu_time: 0.0562, build_memory: 114743417.04, f_measure: 0.9036, kappa: 0.7987, kb_relative_information_score: 3678.4958, mean_absolute_error: 0.1332, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9045, predictive_accuracy: 0.9042, prior_entropy: 0.9735, recall: 0.9042, relative_absolute_error: 0.2765, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2662, root_relative_squared_error: 0.5424, scimark_benchmark: 945.4389,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9604, build_cpu_time: 0.0479, build_memory: 69617678.48, f_measure: 0.9036, kappa: 0.7987, kb_relative_information_score: 3678.4958, mean_absolute_error: 0.1332, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9045, predictive_accuracy: 0.9042, prior_entropy: 0.9735, recall: 0.9042, relative_absolute_error: 0.2765, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2662, root_relative_squared_error: 0.5424, scimark_benchmark: 945.1445,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9604, build_cpu_time: 0.0471, build_memory: 515697429.36, f_measure: 0.9036, kappa: 0.7987, kb_relative_information_score: 3678.4958, mean_absolute_error: 0.1332, mean_prior_absolute_error: 0.4816, number_of_instances: 5000, precision: 0.9045, predictive_accuracy: 0.9042, prior_entropy: 0.9735, recall: 0.9042, relative_absolute_error: 0.2765, root_mean_prior_squared_error: 0.4907, root_mean_squared_error: 0.2662, root_relative_squared_error: 0.5424, scimark_benchmark: 948.9486,

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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)

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