Task
Supervised Classification on lymph

Supervised Classification on lymph

Task 1774 Supervised Classification lymph 305 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9204, f_measure: 0.8479, kappa: 0.7119, kb_relative_information_score: 485.9455, mean_absolute_error: 0.0967, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.8489, predictive_accuracy: 0.8486, prior_entropy: 1.2818, recall: 0.8486, relative_absolute_error: 0.3611, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.243, root_relative_squared_error: 0.6676, scimark_benchmark: 1322.7383, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9204, f_measure: 0.8479, kappa: 0.7119, kb_relative_information_score: 485.9455, mean_absolute_error: 0.0967, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.8489, predictive_accuracy: 0.8486, prior_entropy: 1.2818, recall: 0.8486, relative_absolute_error: 0.3611, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.243, root_relative_squared_error: 0.6676, scimark_benchmark: 1343.2125, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7928, f_measure: 0.7557, kappa: 0.5384, kb_relative_information_score: 363.3393, mean_absolute_error: 0.1384, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.756, predictive_accuracy: 0.7554, prior_entropy: 1.2818, recall: 0.7554, relative_absolute_error: 0.5171, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3216, root_relative_squared_error: 0.8836, scimark_benchmark: 1345.7204,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7928, f_measure: 0.7557, kappa: 0.5384, kb_relative_information_score: 363.3393, mean_absolute_error: 0.1384, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.756, predictive_accuracy: 0.7554, prior_entropy: 1.2818, recall: 0.7554, relative_absolute_error: 0.5171, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3216, root_relative_squared_error: 0.8836, scimark_benchmark: 1339.8573,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8957, f_measure: 0.8064, kappa: 0.6307, kb_relative_information_score: 440.3964, mean_absolute_error: 0.1128, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.8077, predictive_accuracy: 0.8068, prior_entropy: 1.2818, recall: 0.8068, relative_absolute_error: 0.4214, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.2639, root_relative_squared_error: 0.7251, scimark_benchmark: 1318.6149, usercpu_time_millis: 80, usercpu_time_millis_testing: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.857, f_measure: 0.7535, kappa: 0.5424, kb_relative_information_score: 303.0913, mean_absolute_error: 0.1676, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.7443, predictive_accuracy: 0.7676, prior_entropy: 1.2818, recall: 0.7676, relative_absolute_error: 0.626, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.2878, root_relative_squared_error: 0.7906, scimark_benchmark: 1329.8902, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.882, f_measure: 0.7646, kappa: 0.5699, kb_relative_information_score: 254.2362, mean_absolute_error: 0.1915, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.7518, predictive_accuracy: 0.7838, prior_entropy: 1.2818, recall: 0.7838, relative_absolute_error: 0.7154, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.2875, root_relative_squared_error: 0.79, scimark_benchmark: 1333.8751, usercpu_time_millis: 80, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.882, f_measure: 0.7599, kappa: 0.5603, kb_relative_information_score: 252.5195, mean_absolute_error: 0.1919, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.7461, predictive_accuracy: 0.7784, prior_entropy: 1.2818, recall: 0.7784, relative_absolute_error: 0.7169, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.2879, root_relative_squared_error: 0.791, scimark_benchmark: 1345.7582, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8823, f_measure: 0.765, kappa: 0.5702, kb_relative_information_score: 245.681, mean_absolute_error: 0.1945, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.7519, predictive_accuracy: 0.7838, prior_entropy: 1.2818, recall: 0.7838, relative_absolute_error: 0.7263, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.2898, root_relative_squared_error: 0.7963, scimark_benchmark: 1342.1678, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9152, f_measure: 0.8227, kappa: 0.6691, kb_relative_information_score: 480.8758, mean_absolute_error: 0.1008, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.825, predictive_accuracy: 0.823, prior_entropy: 1.2818, recall: 0.823, relative_absolute_error: 0.3765, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.2549, root_relative_squared_error: 0.7003, scimark_benchmark: 943.1756, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7928, f_measure: 0.7557, kappa: 0.5384, kb_relative_information_score: 363.3393, mean_absolute_error: 0.1384, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.756, predictive_accuracy: 0.7554, prior_entropy: 1.2818, recall: 0.7554, relative_absolute_error: 0.5171, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3216, root_relative_squared_error: 0.8836, scimark_benchmark: 1327.035,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9027, f_measure: 0.8202, kappa: 0.6601, kb_relative_information_score: 482.2901, mean_absolute_error: 0.0978, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.8212, predictive_accuracy: 0.8203, prior_entropy: 1.2818, recall: 0.8203, relative_absolute_error: 0.3652, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.2629, root_relative_squared_error: 0.7223, scimark_benchmark: 1368.9272, usercpu_time_millis: 170, usercpu_time_millis_training: 170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9165, f_measure: 0.8436, kappa: 0.703, kb_relative_information_score: 480.551, mean_absolute_error: 0.0986, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.8451, predictive_accuracy: 0.8446, prior_entropy: 1.2818, recall: 0.8446, relative_absolute_error: 0.3683, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.2436, root_relative_squared_error: 0.6694, scimark_benchmark: 854.5188, usercpu_time_millis: 30, usercpu_time_millis_testing: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7928, f_measure: 0.7557, kappa: 0.5384, kb_relative_information_score: 363.3393, mean_absolute_error: 0.1384, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.756, predictive_accuracy: 0.7554, prior_entropy: 1.2818, recall: 0.7554, relative_absolute_error: 0.5171, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3216, root_relative_squared_error: 0.8836, scimark_benchmark: 1314.7093,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7928, f_measure: 0.7557, kappa: 0.5384, kb_relative_information_score: 363.3393, mean_absolute_error: 0.1384, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.756, predictive_accuracy: 0.7554, prior_entropy: 1.2818, recall: 0.7554, relative_absolute_error: 0.5171, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3216, root_relative_squared_error: 0.8836, scimark_benchmark: 1322.4968,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7556, f_measure: 0.7169, kappa: 0.4693, kb_relative_information_score: 334.9572, mean_absolute_error: 0.1454, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.7193, predictive_accuracy: 0.7162, prior_entropy: 1.2818, recall: 0.7162, relative_absolute_error: 0.5432, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3622, root_relative_squared_error: 0.9952, scimark_benchmark: 1316.7714, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7928, f_measure: 0.7557, kappa: 0.5384, kb_relative_information_score: 363.3393, mean_absolute_error: 0.1384, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.756, predictive_accuracy: 0.7554, prior_entropy: 1.2818, recall: 0.7554, relative_absolute_error: 0.5171, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3216, root_relative_squared_error: 0.8836, scimark_benchmark: 1316.5986,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8342, f_measure: 0.8291, kappa: 0.6753, kb_relative_information_score: 476.5821, mean_absolute_error: 0.0845, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.8323, predictive_accuracy: 0.8311, prior_entropy: 1.2818, recall: 0.8311, relative_absolute_error: 0.3155, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.2906, root_relative_squared_error: 0.7985, scimark_benchmark: 1330.6247, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8056, f_measure: 0.7879, kappa: 0.5953, kb_relative_information_score: 409.3204, mean_absolute_error: 0.1218, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.7912, predictive_accuracy: 0.7878, prior_entropy: 1.2818, recall: 0.7878, relative_absolute_error: 0.4548, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3144, root_relative_squared_error: 0.8637, scimark_benchmark: 1331.5882,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7906, f_measure: 0.7831, kappa: 0.5873, kb_relative_information_score: 431.5245, mean_absolute_error: 0.1088, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.788, predictive_accuracy: 0.7824, prior_entropy: 1.2818, recall: 0.7824, relative_absolute_error: 0.4063, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3298, root_relative_squared_error: 0.9062, scimark_benchmark: 996.6105, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5957, f_measure: 0.5694, kappa: 0.2127, kb_relative_information_score: -119.496, mean_absolute_error: 0.3294, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.6499, predictive_accuracy: 0.6257, prior_entropy: 1.2818, recall: 0.6257, relative_absolute_error: 1.2302, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.389, root_relative_squared_error: 1.0688, scimark_benchmark: 1330.6247,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7037, f_measure: 0.6395, kappa: 0.3195, kb_relative_information_score: 167.9675, mean_absolute_error: 0.2114, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.626, predictive_accuracy: 0.6541, prior_entropy: 1.2818, recall: 0.6541, relative_absolute_error: 0.7895, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3551, root_relative_squared_error: 0.9757, scimark_benchmark: 1339.4964,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8937, f_measure: 0.8238, kappa: 0.6665, kb_relative_information_score: 489.549, mean_absolute_error: 0.0883, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.824, predictive_accuracy: 0.8243, prior_entropy: 1.2818, recall: 0.8243, relative_absolute_error: 0.3299, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.2855, root_relative_squared_error: 0.7845, scimark_benchmark: 1330.6247, usercpu_time_millis: 90, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9007, f_measure: 0.8198, kappa: 0.6595, kb_relative_information_score: 488.4817, mean_absolute_error: 0.0895, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.82, predictive_accuracy: 0.8203, prior_entropy: 1.2818, recall: 0.8203, relative_absolute_error: 0.3344, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.2821, root_relative_squared_error: 0.7751, scimark_benchmark: 1349.1028, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7791, f_measure: 0.7663, kappa: 0.5729, kb_relative_information_score: 385.8419, mean_absolute_error: 0.1061, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.7633, predictive_accuracy: 0.7878, prior_entropy: 1.2818, recall: 0.7878, relative_absolute_error: 0.3962, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3257, root_relative_squared_error: 0.8949, scimark_benchmark: 1262.9237, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9204, f_measure: 0.8479, kappa: 0.7119, kb_relative_information_score: 485.9455, mean_absolute_error: 0.0967, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.8489, predictive_accuracy: 0.8486, prior_entropy: 1.2818, recall: 0.8486, relative_absolute_error: 0.3611, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.243, root_relative_squared_error: 0.6676, scimark_benchmark: 1348.8637,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7556, f_measure: 0.7169, kappa: 0.4693, kb_relative_information_score: 334.9572, mean_absolute_error: 0.1454, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.7193, predictive_accuracy: 0.7162, prior_entropy: 1.2818, recall: 0.7162, relative_absolute_error: 0.5432, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3622, root_relative_squared_error: 0.9952, scimark_benchmark: 1337.2572,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7928, f_measure: 0.7557, kappa: 0.5384, kb_relative_information_score: 363.3393, mean_absolute_error: 0.1384, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.756, predictive_accuracy: 0.7554, prior_entropy: 1.2818, recall: 0.7554, relative_absolute_error: 0.5171, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3216, root_relative_squared_error: 0.8836, scimark_benchmark: 1341.994,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9048, f_measure: 0.8129, kappa: 0.6456, kb_relative_information_score: 459.2656, mean_absolute_error: 0.1011, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.8134, predictive_accuracy: 0.8149, prior_entropy: 1.2818, recall: 0.8149, relative_absolute_error: 0.3776, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.2665, root_relative_squared_error: 0.7322, scimark_benchmark: 922.1419,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.905, f_measure: 0.8142, kappa: 0.6486, kb_relative_information_score: 459.8944, mean_absolute_error: 0.1007, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.8148, predictive_accuracy: 0.8162, prior_entropy: 1.2818, recall: 0.8162, relative_absolute_error: 0.3763, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.2666, root_relative_squared_error: 0.7324, scimark_benchmark: 1350.9691,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9181, f_measure: 0.8024, kappa: 0.6451, kb_relative_information_score: 277.0861, mean_absolute_error: 0.1707, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.787, predictive_accuracy: 0.8203, prior_entropy: 1.2818, recall: 0.8203, relative_absolute_error: 0.6376, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.2651, root_relative_squared_error: 0.7285, scimark_benchmark: 1334.9657, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8222, f_measure: 0.7615, kappa: 0.549, kb_relative_information_score: 401.4876, mean_absolute_error: 0.1204, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.7617, predictive_accuracy: 0.7622, prior_entropy: 1.2818, recall: 0.7622, relative_absolute_error: 0.4496, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3415, root_relative_squared_error: 0.9382, scimark_benchmark: 1419.2433, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7937, f_measure: 0.7345, kappa: 0.498, kb_relative_information_score: 143.947, mean_absolute_error: 0.2349, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.751, predictive_accuracy: 0.7311, prior_entropy: 1.2818, recall: 0.7311, relative_absolute_error: 0.8774, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3245, root_relative_squared_error: 0.8917, scimark_benchmark: 1344.7246, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7208, f_measure: 0.6895, kappa: 0.4185, kb_relative_information_score: 224.012, mean_absolute_error: 0.1881, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.6756, predictive_accuracy: 0.7054, prior_entropy: 1.2818, recall: 0.7054, relative_absolute_error: 0.7024, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3448, root_relative_squared_error: 0.9473, scimark_benchmark: 1316.7863, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.773, f_measure: 0.7252, kappa: 0.4801, kb_relative_information_score: 314.8321, mean_absolute_error: 0.1523, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.7306, predictive_accuracy: 0.7297, prior_entropy: 1.2818, recall: 0.7297, relative_absolute_error: 0.5687, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3376, root_relative_squared_error: 0.9277, scimark_benchmark: 1355.9413, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8673, f_measure: 0.8083, kappa: 0.6383, kb_relative_information_score: 471.2881, mean_absolute_error: 0.0991, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.8091, predictive_accuracy: 0.8081, prior_entropy: 1.2818, recall: 0.8081, relative_absolute_error: 0.3701, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.2835, root_relative_squared_error: 0.7789, scimark_benchmark: 918.6005, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.866, f_measure: 0.7749, kappa: 0.5762, kb_relative_information_score: 383.6639, mean_absolute_error: 0.1222, mean_prior_absolute_error: 0.2677, number_of_instances: 740, precision: 0.7728, predictive_accuracy: 0.7797, prior_entropy: 1.2818, recall: 0.7797, relative_absolute_error: 0.4563, root_mean_prior_squared_error: 0.3639, root_mean_squared_error: 0.3057, root_relative_squared_error: 0.84, scimark_benchmark: 1367.8403, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
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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

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From your own software

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

OpenML APIs