OpenML
Supervised Classification on breast-w

Supervised Classification on breast-w

Task 1779 Supervised Classification breast-w 334 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9923, f_measure: 0.9625, kappa: 0.9169, kb_relative_information_score: 3095.7485, mean_absolute_error: 0.0542, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9625, predictive_accuracy: 0.9625, prior_entropy: 0.9297, recall: 0.9625, relative_absolute_error: 0.12, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1704, root_relative_squared_error: 0.3584, scimark_benchmark: 1324.8395, usercpu_time_millis: 13480, usercpu_time_millis_testing: 70, usercpu_time_millis_training: 13410,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9595, f_measure: 0.9516, kappa: 0.8946, kb_relative_information_score: 3098.8835, mean_absolute_error: 0.0489, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9554, predictive_accuracy: 0.9511, prior_entropy: 0.9297, recall: 0.9511, relative_absolute_error: 0.1083, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2212, root_relative_squared_error: 0.4654, scimark_benchmark: 1310.3951, usercpu_time_millis: 100, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9874, f_measure: 0.9727, kappa: 0.94, kb_relative_information_score: 3261.0731, mean_absolute_error: 0.0293, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9736, predictive_accuracy: 0.9725, prior_entropy: 0.9297, recall: 0.9725, relative_absolute_error: 0.0648, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.161, root_relative_squared_error: 0.3388, scimark_benchmark: 1073.494, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9764, f_measure: 0.9546, kappa: 0.8997, kb_relative_information_score: 3078.0098, mean_absolute_error: 0.0545, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9548, predictive_accuracy: 0.9545, prior_entropy: 0.9297, recall: 0.9545, relative_absolute_error: 0.1206, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1991, root_relative_squared_error: 0.4188, scimark_benchmark: 1355.9413, usercpu_time_millis: 230, usercpu_time_millis_training: 230,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.925, f_measure: 0.9351, kappa: 0.8557, kb_relative_information_score: 2966.8861, mean_absolute_error: 0.0653, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9351, predictive_accuracy: 0.9353, prior_entropy: 0.9297, recall: 0.9353, relative_absolute_error: 0.1446, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.254, root_relative_squared_error: 0.5343, scimark_benchmark: 825.5282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9485, f_measure: 0.9332, kappa: 0.8527, kb_relative_information_score: 2799.3233, mean_absolute_error: 0.0942, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9336, predictive_accuracy: 0.933, prior_entropy: 0.9297, recall: 0.933, relative_absolute_error: 0.2083, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2435, root_relative_squared_error: 0.5123, scimark_benchmark: 1319.6463,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9376, f_measure: 0.9398, kappa: 0.8669, kb_relative_information_score: 2896.1442, mean_absolute_error: 0.0802, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9399, predictive_accuracy: 0.9396, prior_entropy: 0.9297, recall: 0.9396, relative_absolute_error: 0.1774, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2367, root_relative_squared_error: 0.498, scimark_benchmark: 1327.6929, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9555, f_measure: 0.9556, kappa: 0.9022, kb_relative_information_score: 3133.4957, mean_absolute_error: 0.0446, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9562, predictive_accuracy: 0.9554, prior_entropy: 0.9297, recall: 0.9554, relative_absolute_error: 0.0988, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2113, root_relative_squared_error: 0.4445, scimark_benchmark: 1372.2145, usercpu_time_millis: 50, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8092, f_measure: 0.8557, kappa: 0.6728, kb_relative_information_score: 2397.4096, mean_absolute_error: 0.1359, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.8786, predictive_accuracy: 0.8641, prior_entropy: 0.9297, recall: 0.8641, relative_absolute_error: 0.3007, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.3687, root_relative_squared_error: 0.7756, scimark_benchmark: 1368.9272, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9539, f_measure: 0.9438, kappa: 0.8752, kb_relative_information_score: 3000.9437, mean_absolute_error: 0.0631, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9437, predictive_accuracy: 0.9439, prior_entropy: 0.9297, recall: 0.9439, relative_absolute_error: 0.1396, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.227, root_relative_squared_error: 0.4776, scimark_benchmark: 1384.4418, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8858, f_measure: 0.9038, kappa: 0.7854, kb_relative_information_score: 2725.0718, mean_absolute_error: 0.0953, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9042, predictive_accuracy: 0.9047, prior_entropy: 0.9297, recall: 0.9047, relative_absolute_error: 0.2108, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.3087, root_relative_squared_error: 0.6494, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9385, f_measure: 0.9458, kappa: 0.8799, kb_relative_information_score: 3057.3489, mean_absolute_error: 0.0541, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9458, predictive_accuracy: 0.9459, prior_entropy: 0.9297, recall: 0.9459, relative_absolute_error: 0.1197, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2325, root_relative_squared_error: 0.4893, scimark_benchmark: 1028.5889, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.499, f_measure: 0.5187, kb_relative_information_score: -2.7197, mean_absolute_error: 0.4521, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.4293, predictive_accuracy: 0.6552, prior_entropy: 0.9297, recall: 0.6552, relative_absolute_error: 1.0003, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.4753, root_relative_squared_error: 1, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.938, f_measure: 0.9368, kappa: 0.8603, kb_relative_information_score: 2903.1142, mean_absolute_error: 0.0776, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9369, predictive_accuracy: 0.9368, prior_entropy: 0.9297, recall: 0.9368, relative_absolute_error: 0.1718, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2432, root_relative_squared_error: 0.5118, scimark_benchmark: 1066.833, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9716, build_cpu_time: 0.1299, build_memory: 591222026.1906, f_measure: 0.9616, kappa: 0.915, kb_relative_information_score: 3106.4765, mean_absolute_error: 0.0509, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9616, predictive_accuracy: 0.9617, prior_entropy: 0.9297, recall: 0.9617, relative_absolute_error: 0.1127, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1935, root_relative_squared_error: 0.407, scimark_benchmark: 939.7691,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9716, build_cpu_time: 0.097, build_memory: 365760365.1159, f_measure: 0.9616, kappa: 0.915, kb_relative_information_score: 3106.4765, mean_absolute_error: 0.0509, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9616, predictive_accuracy: 0.9617, prior_entropy: 0.9297, recall: 0.9617, relative_absolute_error: 0.1127, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1935, root_relative_squared_error: 0.407, scimark_benchmark: 926.638,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9716, build_cpu_time: 0.0949, build_memory: 992753339.9599, f_measure: 0.9616, kappa: 0.915, kb_relative_information_score: 3106.4765, mean_absolute_error: 0.0509, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9616, predictive_accuracy: 0.9617, prior_entropy: 0.9297, recall: 0.9617, relative_absolute_error: 0.1127, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1935, root_relative_squared_error: 0.407, scimark_benchmark: 874.2668,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9716, build_cpu_time: 0.1041, build_memory: 705397680.3342, f_measure: 0.9616, kappa: 0.915, kb_relative_information_score: 3106.4765, mean_absolute_error: 0.0509, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9616, predictive_accuracy: 0.9617, prior_entropy: 0.9297, recall: 0.9617, relative_absolute_error: 0.1127, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1935, root_relative_squared_error: 0.407, scimark_benchmark: 926.9332,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9713, build_cpu_time: 0.1072, build_memory: 703614610.5637, f_measure: 0.9613, kappa: 0.9144, kb_relative_information_score: 3107.8565, mean_absolute_error: 0.0508, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9613, predictive_accuracy: 0.9614, prior_entropy: 0.9297, recall: 0.9614, relative_absolute_error: 0.1123, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1932, root_relative_squared_error: 0.4066, scimark_benchmark: 939.8609,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9836, build_cpu_time: 0.0137, build_memory: 332799318.2695, f_measure: 0.9514, kappa: 0.8924, kb_relative_information_score: 3094.7746, mean_absolute_error: 0.0499, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9514, predictive_accuracy: 0.9514, prior_entropy: 0.9297, recall: 0.9514, relative_absolute_error: 0.1105, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2066, root_relative_squared_error: 0.4348, scimark_benchmark: 925.181,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9831, build_cpu_time: 0.0437, build_memory: 828183736, f_measure: 0.9533, kappa: 0.8967, kb_relative_information_score: 3108.0934, mean_absolute_error: 0.0482, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9533, predictive_accuracy: 0.9534, prior_entropy: 0.9297, recall: 0.9534, relative_absolute_error: 0.1068, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2075, root_relative_squared_error: 0.4367, scimark_benchmark: 941.7891,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9817, build_cpu_time: 0.045, build_memory: 73250181.2921, f_measure: 0.9539, kappa: 0.8979, kb_relative_information_score: 3119.2784, mean_absolute_error: 0.0467, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9539, predictive_accuracy: 0.9539, prior_entropy: 0.9297, recall: 0.9539, relative_absolute_error: 0.1033, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2048, root_relative_squared_error: 0.4309, scimark_benchmark: 919.6575,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9318, build_cpu_time: 0.0065, build_memory: 376211587.6006, f_measure: 0.9411, kappa: 0.8692, kb_relative_information_score: 3016.6463, mean_absolute_error: 0.0591, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9411, predictive_accuracy: 0.9413, prior_entropy: 0.9297, recall: 0.9413, relative_absolute_error: 0.1308, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2417, root_relative_squared_error: 0.5086, scimark_benchmark: 916.3022,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9318, build_cpu_time: 0.0019, build_memory: 403427854.4, f_measure: 0.9411, kappa: 0.8692, kb_relative_information_score: 3016.6463, mean_absolute_error: 0.0591, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9411, predictive_accuracy: 0.9413, prior_entropy: 0.9297, recall: 0.9413, relative_absolute_error: 0.1308, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2417, root_relative_squared_error: 0.5086, scimark_benchmark: 946.9091,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9838, build_cpu_time: 0.1198, build_memory: 1788346765.7408, f_measure: 0.9634, kappa: 0.9191, kb_relative_information_score: 3054.507, mean_absolute_error: 0.0604, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9635, predictive_accuracy: 0.9634, prior_entropy: 0.9297, recall: 0.9634, relative_absolute_error: 0.1337, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1781, root_relative_squared_error: 0.3747, scimark_benchmark: 943.8094,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9836, build_cpu_time: 0.1485, build_memory: 961891254.0933, f_measure: 0.9631, kappa: 0.9185, kb_relative_information_score: 3052.4779, mean_absolute_error: 0.0607, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9632, predictive_accuracy: 0.9631, prior_entropy: 0.9297, recall: 0.9631, relative_absolute_error: 0.1342, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1787, root_relative_squared_error: 0.3759, scimark_benchmark: 945.5885,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9875, build_cpu_time: 0.0096, build_memory: 506695304.586, f_measure: 0.9483, kappa: 0.8852, kb_relative_information_score: 3038.9426, mean_absolute_error: 0.0588, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9483, predictive_accuracy: 0.9485, prior_entropy: 0.9297, recall: 0.9485, relative_absolute_error: 0.1301, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1994, root_relative_squared_error: 0.4196, scimark_benchmark: 930.1524,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9777, build_cpu_time: 0.1314, build_memory: 653620167.2126, f_measure: 0.9634, kappa: 0.9191, kb_relative_information_score: 3194.5305, mean_absolute_error: 0.0375, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9634, predictive_accuracy: 0.9634, prior_entropy: 0.9297, recall: 0.9634, relative_absolute_error: 0.0829, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1773, root_relative_squared_error: 0.3731, scimark_benchmark: 941.9153,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9794, build_cpu_time: 0.235, build_memory: 575202630.0589, f_measure: 0.9646, kappa: 0.9217, kb_relative_information_score: 3196.9769, mean_absolute_error: 0.0373, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9646, predictive_accuracy: 0.9645, prior_entropy: 0.9297, recall: 0.9645, relative_absolute_error: 0.0825, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1764, root_relative_squared_error: 0.3712, scimark_benchmark: 941.6933,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9798, build_cpu_time: 0.5821, build_memory: 632307754.4881, f_measure: 0.9643, kappa: 0.921, kb_relative_information_score: 3196.2747, mean_absolute_error: 0.0374, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9644, predictive_accuracy: 0.9642, prior_entropy: 0.9297, recall: 0.9642, relative_absolute_error: 0.0828, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1759, root_relative_squared_error: 0.37, scimark_benchmark: 935.7354,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9819, build_cpu_time: 0.8339, build_memory: 788650502.7754, f_measure: 0.9643, kappa: 0.921, kb_relative_information_score: 3195.7214, mean_absolute_error: 0.0375, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9643, predictive_accuracy: 0.9642, prior_entropy: 0.9297, recall: 0.9642, relative_absolute_error: 0.0829, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1758, root_relative_squared_error: 0.3699, scimark_benchmark: 944.9156,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.988, build_cpu_time: 0.1458, build_memory: 1711363200.1419, f_measure: 0.9577, kappa: 0.9063, kb_relative_information_score: 2906.5507, mean_absolute_error: 0.0838, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9577, predictive_accuracy: 0.9577, prior_entropy: 0.9297, recall: 0.9577, relative_absolute_error: 0.1853, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1851, root_relative_squared_error: 0.3894, scimark_benchmark: 938.5838,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9878, build_cpu_time: 0.1046, build_memory: 398925335.6383, f_measure: 0.9557, kappa: 0.9019, kb_relative_information_score: 2905.0481, mean_absolute_error: 0.0837, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9557, predictive_accuracy: 0.9557, prior_entropy: 0.9297, recall: 0.9557, relative_absolute_error: 0.1851, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1861, root_relative_squared_error: 0.3915, scimark_benchmark: 946.7087,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9869, build_cpu_time: 0.0453, build_memory: 1636931878.7914, f_measure: 0.9545, kappa: 0.8993, kb_relative_information_score: 2895.4257, mean_absolute_error: 0.085, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9545, predictive_accuracy: 0.9545, prior_entropy: 0.9297, recall: 0.9545, relative_absolute_error: 0.188, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1878, root_relative_squared_error: 0.3952, scimark_benchmark: 947.4258,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9862, build_cpu_time: 0.0245, build_memory: 1474753566.1001, f_measure: 0.9531, kappa: 0.8963, kb_relative_information_score: 2894.9716, mean_absolute_error: 0.0847, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9532, predictive_accuracy: 0.9531, prior_entropy: 0.9297, recall: 0.9531, relative_absolute_error: 0.1874, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1897, root_relative_squared_error: 0.3991, scimark_benchmark: 941.5201,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9851, build_cpu_time: 0.0091, build_memory: 1117226505.3299, f_measure: 0.9547, kappa: 0.8996, kb_relative_information_score: 3013.2531, mean_absolute_error: 0.0652, mean_prior_absolute_error: 0.452, number_of_instances: 3495, precision: 0.9547, predictive_accuracy: 0.9548, prior_entropy: 0.9297, recall: 0.9548, relative_absolute_error: 0.1442, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1848, root_relative_squared_error: 0.3887, scimark_benchmark: 919.2952,

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