Task
Supervised Classification on cholesterol

Supervised Classification on cholesterol

Task 4368 Supervised Classification cholesterol 221 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5528, f_measure: 0.5888, kappa: 0.1681, kb_relative_information_score: 158.5002, mean_absolute_error: 0.4753, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5889, predictive_accuracy: 0.5921, prior_entropy: 0.9935, recall: 0.5921, relative_absolute_error: 0.9593, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5128, root_relative_squared_error: 1.0304, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5282, f_measure: 0.5434, kappa: 0.0762, kb_relative_information_score: 21.5895, mean_absolute_error: 0.4927, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5428, predictive_accuracy: 0.5472, prior_entropy: 0.9935, recall: 0.5472, relative_absolute_error: 0.9944, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5131, root_relative_squared_error: 1.0308, scimark_benchmark: 972.587, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5244, f_measure: 0.5385, kappa: 0.0684, kb_relative_information_score: 79.7613, mean_absolute_error: 0.4837, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5398, predictive_accuracy: 0.5469, prior_entropy: 0.9935, recall: 0.5469, relative_absolute_error: 0.9763, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5353, root_relative_squared_error: 1.0754, scimark_benchmark: 934.3687, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4775, f_measure: 0.4539, kappa: -0.0473, kb_relative_information_score: 6.4423, mean_absolute_error: 0.4924, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.4703, predictive_accuracy: 0.5076, prior_entropy: 0.9935, recall: 0.5076, relative_absolute_error: 0.9939, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.7017, root_relative_squared_error: 1.4099, scimark_benchmark: 944.1067, usercpu_time_millis: 60, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4775, f_measure: 0.4539, kappa: -0.0473, kb_relative_information_score: 6.4423, mean_absolute_error: 0.4924, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.4703, predictive_accuracy: 0.5076, prior_entropy: 0.9935, recall: 0.5076, relative_absolute_error: 0.9939, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.7017, root_relative_squared_error: 1.4099, scimark_benchmark: 916.0735, usercpu_time_millis: 70, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5919, f_measure: 0.6097, kappa: 0.2104, kb_relative_information_score: 164.8235, mean_absolute_error: 0.4741, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.6103, predictive_accuracy: 0.6132, prior_entropy: 0.9935, recall: 0.6132, relative_absolute_error: 0.9569, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4983, root_relative_squared_error: 1.0012, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5571, f_measure: 0.5408, kappa: 0.071, kb_relative_information_score: 104.7539, mean_absolute_error: 0.48, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5402, predictive_accuracy: 0.5449, prior_entropy: 0.9935, recall: 0.5449, relative_absolute_error: 0.9687, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5084, root_relative_squared_error: 1.0215, scimark_benchmark: 938.191, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5661, f_measure: 0.5564, kappa: 0.1026, kb_relative_information_score: 166.0793, mean_absolute_error: 0.4716, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5558, predictive_accuracy: 0.5591, prior_entropy: 0.9935, recall: 0.5591, relative_absolute_error: 0.9518, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5231, root_relative_squared_error: 1.051, scimark_benchmark: 932.2692, usercpu_time_millis: 5260, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 5220,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5821, f_measure: 0.5935, kappa: 0.1777, kb_relative_information_score: 209.4843, mean_absolute_error: 0.4658, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5931, predictive_accuracy: 0.5954, prior_entropy: 0.9935, recall: 0.5954, relative_absolute_error: 0.9401, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5193, root_relative_squared_error: 1.0435, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4775, f_measure: 0.4539, kappa: -0.0473, kb_relative_information_score: 6.4423, mean_absolute_error: 0.4924, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.4703, predictive_accuracy: 0.5076, prior_entropy: 0.9935, recall: 0.5076, relative_absolute_error: 0.9939, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.7017, root_relative_squared_error: 1.4099, scimark_benchmark: 941.3847, usercpu_time_millis: 60, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4775, f_measure: 0.4539, kappa: -0.0473, kb_relative_information_score: 6.4423, mean_absolute_error: 0.4924, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.4703, predictive_accuracy: 0.5076, prior_entropy: 0.9935, recall: 0.5076, relative_absolute_error: 0.9939, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.7017, root_relative_squared_error: 1.4099, scimark_benchmark: 941.3847, usercpu_time_millis: 60, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6008, f_measure: 0.6154, kappa: 0.2221, kb_relative_information_score: 191.3545, mean_absolute_error: 0.4705, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.6166, predictive_accuracy: 0.6195, prior_entropy: 0.9935, recall: 0.6195, relative_absolute_error: 0.9497, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4961, root_relative_squared_error: 0.9967, scimark_benchmark: 974.2014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5919, f_measure: 0.6097, kappa: 0.2104, kb_relative_information_score: 164.8235, mean_absolute_error: 0.4741, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.6103, predictive_accuracy: 0.6132, prior_entropy: 0.9935, recall: 0.6132, relative_absolute_error: 0.9569, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4983, root_relative_squared_error: 1.0012, scimark_benchmark: 941.3847,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5533, f_measure: 0.5376, kappa: 0.065, kb_relative_information_score: 93.305, mean_absolute_error: 0.4817, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5374, predictive_accuracy: 0.5429, prior_entropy: 0.9935, recall: 0.5429, relative_absolute_error: 0.9723, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.51, root_relative_squared_error: 1.0247, scimark_benchmark: 947.1781, usercpu_time_millis: 90, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5528, f_measure: 0.5888, kappa: 0.1681, kb_relative_information_score: 158.5002, mean_absolute_error: 0.4753, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5889, predictive_accuracy: 0.5921, prior_entropy: 0.9935, recall: 0.5921, relative_absolute_error: 0.9593, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5128, root_relative_squared_error: 1.0304, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5282, f_measure: 0.5434, kappa: 0.0762, kb_relative_information_score: 21.5895, mean_absolute_error: 0.4927, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5428, predictive_accuracy: 0.5472, prior_entropy: 0.9935, recall: 0.5472, relative_absolute_error: 0.9944, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5131, root_relative_squared_error: 1.0308, scimark_benchmark: 908.9569, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5244, f_measure: 0.5385, kappa: 0.0684, kb_relative_information_score: 79.7613, mean_absolute_error: 0.4837, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5398, predictive_accuracy: 0.5469, prior_entropy: 0.9935, recall: 0.5469, relative_absolute_error: 0.9763, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5353, root_relative_squared_error: 1.0754, scimark_benchmark: 936.2574, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4775, f_measure: 0.4539, kappa: -0.0473, kb_relative_information_score: 6.4423, mean_absolute_error: 0.4924, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.4703, predictive_accuracy: 0.5076, prior_entropy: 0.9935, recall: 0.5076, relative_absolute_error: 0.9939, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.7017, root_relative_squared_error: 1.4099, scimark_benchmark: 927.2882, usercpu_time_millis: 60, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4775, f_measure: 0.4539, kappa: -0.0473, kb_relative_information_score: 6.4423, mean_absolute_error: 0.4924, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.4703, predictive_accuracy: 0.5076, prior_entropy: 0.9935, recall: 0.5076, relative_absolute_error: 0.9939, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.7017, root_relative_squared_error: 1.4099, scimark_benchmark: 934.5964, usercpu_time_millis: 70, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5919, f_measure: 0.6097, kappa: 0.2104, kb_relative_information_score: 164.8235, mean_absolute_error: 0.4741, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.6103, predictive_accuracy: 0.6132, prior_entropy: 0.9935, recall: 0.6132, relative_absolute_error: 0.9569, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4983, root_relative_squared_error: 1.0012, scimark_benchmark: 933.3455, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5571, f_measure: 0.5408, kappa: 0.071, kb_relative_information_score: 104.7539, mean_absolute_error: 0.48, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5402, predictive_accuracy: 0.5449, prior_entropy: 0.9935, recall: 0.5449, relative_absolute_error: 0.9687, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5084, root_relative_squared_error: 1.0215, scimark_benchmark: 930.404, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5661, f_measure: 0.5564, kappa: 0.1026, kb_relative_information_score: 166.0793, mean_absolute_error: 0.4716, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5558, predictive_accuracy: 0.5591, prior_entropy: 0.9935, recall: 0.5591, relative_absolute_error: 0.9518, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5231, root_relative_squared_error: 1.051, scimark_benchmark: 934.5964, usercpu_time_millis: 3880, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 3860,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5919, f_measure: 0.6097, kappa: 0.2104, kb_relative_information_score: 164.8235, mean_absolute_error: 0.4741, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.6103, predictive_accuracy: 0.6132, prior_entropy: 0.9935, recall: 0.6132, relative_absolute_error: 0.9569, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4983, root_relative_squared_error: 1.0012, scimark_benchmark: 936.9595, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5821, f_measure: 0.5935, kappa: 0.1777, kb_relative_information_score: 209.4843, mean_absolute_error: 0.4658, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5931, predictive_accuracy: 0.5954, prior_entropy: 0.9935, recall: 0.5954, relative_absolute_error: 0.9401, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5193, root_relative_squared_error: 1.0435, scimark_benchmark: 936.9595, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5533, f_measure: 0.5376, kappa: 0.065, kb_relative_information_score: 93.305, mean_absolute_error: 0.4817, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5374, predictive_accuracy: 0.5429, prior_entropy: 0.9935, recall: 0.5429, relative_absolute_error: 0.9723, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.51, root_relative_squared_error: 1.0247, scimark_benchmark: 730.6551, usercpu_time_millis: 120, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5853, f_measure: 0.5652, kappa: 0.1232, kb_relative_information_score: 134.5415, mean_absolute_error: 0.4777, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5685, predictive_accuracy: 0.5743, prior_entropy: 0.9935, recall: 0.5743, relative_absolute_error: 0.9642, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4962, root_relative_squared_error: 0.9969, scimark_benchmark: 934.695, usercpu_time_millis: 2890, usercpu_time_millis_testing: 1300, usercpu_time_millis_training: 1590,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5806, f_measure: 0.5672, kappa: 0.1265, kb_relative_information_score: 128.2515, mean_absolute_error: 0.4785, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5698, predictive_accuracy: 0.5752, prior_entropy: 0.9935, recall: 0.5752, relative_absolute_error: 0.9658, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4973, root_relative_squared_error: 0.9991, scimark_benchmark: 933.3455, usercpu_time_millis: 1110, usercpu_time_millis_testing: 340, usercpu_time_millis_training: 770,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5845, f_measure: 0.5802, kappa: 0.1529, kb_relative_information_score: 140.8418, mean_absolute_error: 0.4769, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5834, predictive_accuracy: 0.5881, prior_entropy: 0.9935, recall: 0.5881, relative_absolute_error: 0.9625, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4964, root_relative_squared_error: 0.9973, scimark_benchmark: 942.5233, usercpu_time_millis: 570, usercpu_time_millis_testing: 160, usercpu_time_millis_training: 410,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5791, f_measure: 0.5724, kappa: 0.1367, kb_relative_information_score: 134.4344, mean_absolute_error: 0.4775, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5748, predictive_accuracy: 0.5799, prior_entropy: 0.9935, recall: 0.5799, relative_absolute_error: 0.9637, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4986, root_relative_squared_error: 1.0017, scimark_benchmark: 945.0448, usercpu_time_millis: 260, usercpu_time_millis_testing: 70, usercpu_time_millis_training: 190,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5656, f_measure: 0.5526, kappa: 0.0962, kb_relative_information_score: 119.948, mean_absolute_error: 0.4791, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5538, predictive_accuracy: 0.5597, prior_entropy: 0.9935, recall: 0.5597, relative_absolute_error: 0.9669, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5037, root_relative_squared_error: 1.0121, scimark_benchmark: 921.466, usercpu_time_millis: 150, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5478, f_measure: 0.5426, kappa: 0.0749, kb_relative_information_score: 103.4415, mean_absolute_error: 0.4797, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5418, predictive_accuracy: 0.5442, prior_entropy: 0.9935, recall: 0.5442, relative_absolute_error: 0.9682, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5235, root_relative_squared_error: 1.0518, scimark_benchmark: 889.4922, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5478, f_measure: 0.5426, kappa: 0.0749, kb_relative_information_score: 103.4415, mean_absolute_error: 0.4797, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5418, predictive_accuracy: 0.5442, prior_entropy: 0.9935, recall: 0.5442, relative_absolute_error: 0.9682, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5235, root_relative_squared_error: 1.0518, scimark_benchmark: 889.4922, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5478, f_measure: 0.5426, kappa: 0.0749, kb_relative_information_score: 103.4415, mean_absolute_error: 0.4797, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5418, predictive_accuracy: 0.5442, prior_entropy: 0.9935, recall: 0.5442, relative_absolute_error: 0.9682, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5235, root_relative_squared_error: 1.0518, scimark_benchmark: 929.0296, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5483, f_measure: 0.5423, kappa: 0.0743, kb_relative_information_score: 104.8513, mean_absolute_error: 0.4795, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5415, predictive_accuracy: 0.5439, prior_entropy: 0.9935, recall: 0.5439, relative_absolute_error: 0.9678, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.5233, root_relative_squared_error: 1.0513, scimark_benchmark: 936.1714, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5541, f_measure: 0.5577, kappa: 0.1051, kb_relative_information_score: 112.2717, mean_absolute_error: 0.4789, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.5571, predictive_accuracy: 0.5604, prior_entropy: 0.9935, recall: 0.5604, relative_absolute_error: 0.9665, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.516, root_relative_squared_error: 1.0368, scimark_benchmark: 929.0296, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.485, f_measure: 0.3878, kb_relative_information_score: -0.5009, mean_absolute_error: 0.4955, mean_prior_absolute_error: 0.4955, number_of_instances: 3030, precision: 0.3001, predictive_accuracy: 0.5479, prior_entropy: 0.9935, recall: 0.5479, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.4977, root_mean_squared_error: 0.4977, root_relative_squared_error: 1.0001, scimark_benchmark: 941.9549,
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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