OpenML
Supervised Classification on hip

Supervised Classification on hip

Task 4466 Supervised Classification hip 239 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8118, f_measure: 0.7476, kappa: 0.4944, kb_relative_information_score: 178.1264, mean_absolute_error: 0.3511, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7486, predictive_accuracy: 0.7481, prior_entropy: 0.9991, recall: 0.7481, relative_absolute_error: 0.7031, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4164, root_relative_squared_error: 0.8333, scimark_benchmark: 1315.395,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7761, f_measure: 0.7186, kappa: 0.4397, kb_relative_information_score: 194.9447, mean_absolute_error: 0.3287, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7288, predictive_accuracy: 0.7222, prior_entropy: 0.9991, recall: 0.7222, relative_absolute_error: 0.6582, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4491, root_relative_squared_error: 0.8989, scimark_benchmark: 939.5205,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8862, f_measure: 0.8369, kappa: 0.6733, kb_relative_information_score: 359.5525, mean_absolute_error: 0.1678, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.8372, predictive_accuracy: 0.837, prior_entropy: 0.9991, recall: 0.837, relative_absolute_error: 0.336, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3935, root_relative_squared_error: 0.7876, scimark_benchmark: 1304.9611, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8974, f_measure: 0.8314, kappa: 0.6623, kb_relative_information_score: 359.9218, mean_absolute_error: 0.1668, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.8315, predictive_accuracy: 0.8315, prior_entropy: 0.9991, recall: 0.8315, relative_absolute_error: 0.3341, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3786, root_relative_squared_error: 0.7578, scimark_benchmark: 915.9693, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8987, f_measure: 0.8387, kappa: 0.6768, kb_relative_information_score: 355.2149, mean_absolute_error: 0.1728, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.8394, predictive_accuracy: 0.8389, prior_entropy: 0.9991, recall: 0.8389, relative_absolute_error: 0.3461, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3659, root_relative_squared_error: 0.7323, scimark_benchmark: 882.7843, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8794, f_measure: 0.8278, kappa: 0.6551, kb_relative_information_score: 322.1855, mean_absolute_error: 0.2071, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.8278, predictive_accuracy: 0.8278, prior_entropy: 0.9991, recall: 0.8278, relative_absolute_error: 0.4147, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3742, root_relative_squared_error: 0.7489, scimark_benchmark: 943.1756, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8574, f_measure: 0.8148, kappa: 0.629, kb_relative_information_score: 291.5658, mean_absolute_error: 0.2403, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.8148, predictive_accuracy: 0.8148, prior_entropy: 0.9991, recall: 0.8148, relative_absolute_error: 0.4812, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3837, root_relative_squared_error: 0.768, scimark_benchmark: 825.5282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7736, f_measure: 0.6084, kappa: 0.2692, kb_relative_information_score: 112.4215, mean_absolute_error: 0.4023, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.6979, predictive_accuracy: 0.6426, prior_entropy: 0.9991, recall: 0.6426, relative_absolute_error: 0.8056, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4761, root_relative_squared_error: 0.9529, scimark_benchmark: 1313.9994,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7755, f_measure: 0.6217, kappa: 0.2889, kb_relative_information_score: 144.8249, mean_absolute_error: 0.3679, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7034, predictive_accuracy: 0.6519, prior_entropy: 0.9991, recall: 0.6519, relative_absolute_error: 0.7367, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4781, root_relative_squared_error: 0.9569, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8044, f_measure: 0.8053, kappa: 0.6099, kb_relative_information_score: 329.5762, mean_absolute_error: 0.1944, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.8059, predictive_accuracy: 0.8056, prior_entropy: 0.9991, recall: 0.8056, relative_absolute_error: 0.3894, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.441, root_relative_squared_error: 0.8825, scimark_benchmark: 1318.1432,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5117, f_measure: 0.3815, kappa: 0.0242, kb_relative_information_score: 31.0271, mean_absolute_error: 0.4704, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.6932, predictive_accuracy: 0.5296, prior_entropy: 0.9991, recall: 0.5296, relative_absolute_error: 0.942, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.6858, root_relative_squared_error: 1.3726, scimark_benchmark: 906.4475, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8254, f_measure: 0.8268, kappa: 0.6536, kb_relative_information_score: 353.6204, mean_absolute_error: 0.1722, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.8315, predictive_accuracy: 0.8278, prior_entropy: 0.9991, recall: 0.8278, relative_absolute_error: 0.3449, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.415, root_relative_squared_error: 0.8306, scimark_benchmark: 825.5282, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8821, f_measure: 0.8297, kappa: 0.6589, kb_relative_information_score: 253.4505, mean_absolute_error: 0.2828, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.8297, predictive_accuracy: 0.8296, prior_entropy: 0.9991, recall: 0.8296, relative_absolute_error: 0.5664, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3699, root_relative_squared_error: 0.7403, scimark_benchmark: 915.6729, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8015, f_measure: 0.8018, kappa: 0.6031, kb_relative_information_score: 325.5688, mean_absolute_error: 0.1981, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.8018, predictive_accuracy: 0.8019, prior_entropy: 0.9991, recall: 0.8019, relative_absolute_error: 0.3968, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4451, root_relative_squared_error: 0.8909, scimark_benchmark: 908.2231,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9099, f_measure: 0.8407, kappa: 0.681, kb_relative_information_score: 298.3874, mean_absolute_error: 0.2404, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.8407, predictive_accuracy: 0.8407, prior_entropy: 0.9991, recall: 0.8407, relative_absolute_error: 0.4814, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3346, root_relative_squared_error: 0.6697, scimark_benchmark: 939.5088, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8606, f_measure: 0.7667, kappa: 0.5339, kb_relative_information_score: 260.7087, mean_absolute_error: 0.2654, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.773, predictive_accuracy: 0.7685, prior_entropy: 0.9991, recall: 0.7685, relative_absolute_error: 0.5316, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4, root_relative_squared_error: 0.8006, scimark_benchmark: 1304.9611,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8771, f_measure: 0.796, kappa: 0.5912, kb_relative_information_score: 255.4798, mean_absolute_error: 0.2774, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7967, predictive_accuracy: 0.7963, prior_entropy: 0.9991, recall: 0.7963, relative_absolute_error: 0.5555, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3695, root_relative_squared_error: 0.7396, scimark_benchmark: 1072.3689, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7514, f_measure: 0.746, kappa: 0.4911, kb_relative_information_score: 243.7982, mean_absolute_error: 0.2766, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7463, predictive_accuracy: 0.7463, prior_entropy: 0.9991, recall: 0.7463, relative_absolute_error: 0.5538, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4879, root_relative_squared_error: 0.9764, scimark_benchmark: 825.5282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7219, f_measure: 0.6781, kappa: 0.3558, kb_relative_information_score: 153.7115, mean_absolute_error: 0.3657, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.6804, predictive_accuracy: 0.6796, prior_entropy: 0.9991, recall: 0.6796, relative_absolute_error: 0.7323, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4785, root_relative_squared_error: 0.9577, scimark_benchmark: 1318.5526,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7732, f_measure: 0.6961, kappa: 0.3925, kb_relative_information_score: 192.4537, mean_absolute_error: 0.3261, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7001, predictive_accuracy: 0.6981, prior_entropy: 0.9991, recall: 0.6981, relative_absolute_error: 0.6531, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4764, root_relative_squared_error: 0.9534, scimark_benchmark: 1319.6463,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.776, f_measure: 0.7771, kappa: 0.5536, kb_relative_information_score: 299.5209, mean_absolute_error: 0.2222, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.779, predictive_accuracy: 0.7778, prior_entropy: 0.9991, recall: 0.7778, relative_absolute_error: 0.445, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4714, root_relative_squared_error: 0.9435, scimark_benchmark: 1280.6952,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6504, f_measure: 0.6271, kappa: 0.2959, kb_relative_information_score: 153.2519, mean_absolute_error: 0.3574, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.6842, predictive_accuracy: 0.6426, prior_entropy: 0.9991, recall: 0.6426, relative_absolute_error: 0.7158, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5978, root_relative_squared_error: 1.1965, scimark_benchmark: 1317.1452,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.753, f_measure: 0.7373, kappa: 0.4747, kb_relative_information_score: 203.1665, mean_absolute_error: 0.3237, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7413, predictive_accuracy: 0.7389, prior_entropy: 0.9991, recall: 0.7389, relative_absolute_error: 0.6482, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.453, root_relative_squared_error: 0.9067, scimark_benchmark: 1330.0803,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6065, f_measure: 0.6072, kappa: 0.2131, kb_relative_information_score: 115.1819, mean_absolute_error: 0.3926, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.6071, predictive_accuracy: 0.6074, prior_entropy: 0.9991, recall: 0.6074, relative_absolute_error: 0.7862, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.6266, root_relative_squared_error: 1.254, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7118, f_measure: 0.7126, kappa: 0.4243, kb_relative_information_score: 229.3919, mean_absolute_error: 0.287, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7129, predictive_accuracy: 0.713, prior_entropy: 0.9991, recall: 0.713, relative_absolute_error: 0.5748, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5358, root_relative_squared_error: 1.0723, scimark_benchmark: 1392.1129,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4231, f_measure: 0.3541, kb_relative_information_score: -1.5941, mean_absolute_error: 0.5004, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.2689, predictive_accuracy: 0.5185, prior_entropy: 0.9991, recall: 0.5185, relative_absolute_error: 1.0021, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5007, root_relative_squared_error: 1.0022, scimark_benchmark: 1445.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7668, f_measure: 0.7124, kappa: 0.4257, kb_relative_information_score: 188.7835, mean_absolute_error: 0.3333, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7181, predictive_accuracy: 0.7148, prior_entropy: 0.9991, recall: 0.7148, relative_absolute_error: 0.6675, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4592, root_relative_squared_error: 0.9191, scimark_benchmark: 1392.1129,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8323, build_cpu_time: 0.0287, build_memory: 960435076.2963, f_measure: 0.796, kappa: 0.5914, kb_relative_information_score: 263.8642, mean_absolute_error: 0.266, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7965, predictive_accuracy: 0.7963, prior_entropy: 0.9991, recall: 0.7963, relative_absolute_error: 0.5327, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4083, root_relative_squared_error: 0.8171, scimark_benchmark: 947.0987,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8324, build_cpu_time: 0.017, build_memory: 653949617.1556, f_measure: 0.796, kappa: 0.5914, kb_relative_information_score: 264.1408, mean_absolute_error: 0.2657, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7965, predictive_accuracy: 0.7963, prior_entropy: 0.9991, recall: 0.7963, relative_absolute_error: 0.532, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4082, root_relative_squared_error: 0.8169, scimark_benchmark: 941.5865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8308, build_cpu_time: 0.0157, build_memory: 471772267.6296, f_measure: 0.7942, kappa: 0.5877, kb_relative_information_score: 263.9346, mean_absolute_error: 0.2658, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7946, predictive_accuracy: 0.7944, prior_entropy: 0.9991, recall: 0.7944, relative_absolute_error: 0.5323, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4096, root_relative_squared_error: 0.8197, scimark_benchmark: 945.6653,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8353, build_cpu_time: 0.0087, build_memory: 125970357.7926, f_measure: 0.796, kappa: 0.5914, kb_relative_information_score: 266.6587, mean_absolute_error: 0.2632, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7965, predictive_accuracy: 0.7963, prior_entropy: 0.9991, recall: 0.7963, relative_absolute_error: 0.5271, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4059, root_relative_squared_error: 0.8124, scimark_benchmark: 945.2151,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8338, build_cpu_time: 0.0129, build_memory: 52020181.9704, f_measure: 0.7943, kappa: 0.5878, kb_relative_information_score: 263.2586, mean_absolute_error: 0.2667, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7945, predictive_accuracy: 0.7944, prior_entropy: 0.9991, recall: 0.7944, relative_absolute_error: 0.5341, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4074, root_relative_squared_error: 0.8154, scimark_benchmark: 942.3742,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8338, build_cpu_time: 0.011, build_memory: 262156481.0963, f_measure: 0.7943, kappa: 0.5878, kb_relative_information_score: 263.2586, mean_absolute_error: 0.2667, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7945, predictive_accuracy: 0.7944, prior_entropy: 0.9991, recall: 0.7944, relative_absolute_error: 0.5341, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4074, root_relative_squared_error: 0.8154, scimark_benchmark: 940.9202,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8872, build_cpu_time: 0.0477, build_memory: 3308642030.4148, f_measure: 0.8052, kappa: 0.6098, kb_relative_information_score: 237.0735, mean_absolute_error: 0.2994, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.8061, predictive_accuracy: 0.8056, prior_entropy: 0.9991, recall: 0.8056, relative_absolute_error: 0.5995, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3687, root_relative_squared_error: 0.7379, scimark_benchmark: 944.5338,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8883, build_cpu_time: 0.0984, build_memory: 497412149.5111, f_measure: 0.7959, kappa: 0.5911, kb_relative_information_score: 237.3251, mean_absolute_error: 0.2989, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7969, predictive_accuracy: 0.7963, prior_entropy: 0.9991, recall: 0.7963, relative_absolute_error: 0.5986, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3677, root_relative_squared_error: 0.7359, scimark_benchmark: 943.8741,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8495, build_cpu_time: 0.0353, build_memory: 1228239596.8889, f_measure: 0.7862, kappa: 0.572, kb_relative_information_score: 222.1478, mean_absolute_error: 0.3111, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7888, predictive_accuracy: 0.787, prior_entropy: 0.9991, recall: 0.787, relative_absolute_error: 0.623, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3908, root_relative_squared_error: 0.7821, scimark_benchmark: 906.1952,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.849, build_cpu_time: 0.0444, build_memory: 1383191595.0667, f_measure: 0.7918, kappa: 0.5832, kb_relative_information_score: 222.8906, mean_absolute_error: 0.3103, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7942, predictive_accuracy: 0.7926, prior_entropy: 0.9991, recall: 0.7926, relative_absolute_error: 0.6214, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3913, root_relative_squared_error: 0.7831, scimark_benchmark: 941.7127,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8465, build_cpu_time: 0.0111, build_memory: 1528856291.1556, f_measure: 0.7809, kappa: 0.5612, kb_relative_information_score: 222.5708, mean_absolute_error: 0.31, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7824, predictive_accuracy: 0.7815, prior_entropy: 0.9991, recall: 0.7815, relative_absolute_error: 0.6208, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3934, root_relative_squared_error: 0.7874, scimark_benchmark: 942.3232,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8403, build_cpu_time: 0.0071, build_memory: 1585446773.7482, f_measure: 0.7736, kappa: 0.5465, kb_relative_information_score: 219.5238, mean_absolute_error: 0.3121, mean_prior_absolute_error: 0.4993, number_of_instances: 540, precision: 0.7745, predictive_accuracy: 0.7741, prior_entropy: 0.9991, recall: 0.7741, relative_absolute_error: 0.6251, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3982, root_relative_squared_error: 0.7969, scimark_benchmark: 943.3967,

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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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