Task
Supervised Classification on prnn_viruses

Supervised Classification on prnn_viruses

Task 3569 Supervised Classification prnn_viruses 391 runs submitted
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  • study_1 study_107 study_123 study_41 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9981, f_measure: 0.9152, kappa: 0.8417, kb_relative_information_score: 49.3659, mean_absolute_error: 0.0519, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.915, predictive_accuracy: 0.918, prior_entropy: 1.5019, recall: 0.918, relative_absolute_error: 0.1898, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.1476, root_relative_squared_error: 0.4036, scimark_benchmark: 1339.4189, usercpu_time_millis: 230, usercpu_time_millis_training: 230,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9697, f_measure: 0.9286, kappa: 0.8768, kb_relative_information_score: 49.3459, mean_absolute_error: 0.0328, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.9426, predictive_accuracy: 0.9344, prior_entropy: 1.5019, recall: 0.9344, relative_absolute_error: 0.1199, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.1811, root_relative_squared_error: 0.4953, scimark_benchmark: 912.5006,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9767, f_measure: 0.8955, kappa: 0.8098, kb_relative_information_score: 37.9952, mean_absolute_error: 0.1214, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.8923, predictive_accuracy: 0.9016, prior_entropy: 1.5019, recall: 0.9016, relative_absolute_error: 0.4437, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.2136, root_relative_squared_error: 0.5844, scimark_benchmark: 1330.0694,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9895, f_measure: 0.9505, kappa: 0.9082, kb_relative_information_score: 53.3608, mean_absolute_error: 0.0209, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.9518, predictive_accuracy: 0.9508, prior_entropy: 1.5019, recall: 0.9508, relative_absolute_error: 0.0764, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.1327, root_relative_squared_error: 0.363, scimark_benchmark: 937.1527, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9823, f_measure: 0.8631, kappa: 0.7346, kb_relative_information_score: 39.2623, mean_absolute_error: 0.115, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.8718, predictive_accuracy: 0.8689, prior_entropy: 1.5019, recall: 0.8689, relative_absolute_error: 0.4204, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.2105, root_relative_squared_error: 0.5758, scimark_benchmark: 940.0008,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9954, f_measure: 0.8927, kappa: 0.8027, kb_relative_information_score: 43.9809, mean_absolute_error: 0.0922, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.905, predictive_accuracy: 0.9016, prior_entropy: 1.5019, recall: 0.9016, relative_absolute_error: 0.337, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.1741, root_relative_squared_error: 0.4762, scimark_benchmark: 938.0414,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9909, f_measure: 0.9839, kappa: 0.9694, kb_relative_information_score: 56.5321, mean_absolute_error: 0.0082, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.9859, predictive_accuracy: 0.9836, prior_entropy: 1.5019, recall: 0.9836, relative_absolute_error: 0.03, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.0905, root_relative_squared_error: 0.2477, scimark_benchmark: 1321.9426,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9459, f_measure: 0.7977, kappa: 0.7132, kb_relative_information_score: 29.091, mean_absolute_error: 0.1578, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.7653, predictive_accuracy: 0.8525, prior_entropy: 1.5019, recall: 0.8525, relative_absolute_error: 0.5768, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.2414, root_relative_squared_error: 0.6603, scimark_benchmark: 930.5999,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9459, f_measure: 0.7977, kappa: 0.7132, kb_relative_information_score: 29.091, mean_absolute_error: 0.1578, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.7653, predictive_accuracy: 0.8525, prior_entropy: 1.5019, recall: 0.8525, relative_absolute_error: 0.5768, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.2414, root_relative_squared_error: 0.6603, scimark_benchmark: 935.5075,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9459, f_measure: 0.7977, kappa: 0.7132, kb_relative_information_score: 29.091, mean_absolute_error: 0.1578, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.7653, predictive_accuracy: 0.8525, prior_entropy: 1.5019, recall: 0.8525, relative_absolute_error: 0.5768, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.2414, root_relative_squared_error: 0.6603, scimark_benchmark: 1336.2509,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9459, f_measure: 0.7977, kappa: 0.7132, kb_relative_information_score: 29.091, mean_absolute_error: 0.1578, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.7653, predictive_accuracy: 0.8525, prior_entropy: 1.5019, recall: 0.8525, relative_absolute_error: 0.5768, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.2414, root_relative_squared_error: 0.6603, scimark_benchmark: 1321.9426,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9459, f_measure: 0.7977, kappa: 0.7132, kb_relative_information_score: 29.091, mean_absolute_error: 0.1578, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.7653, predictive_accuracy: 0.8525, prior_entropy: 1.5019, recall: 0.8525, relative_absolute_error: 0.5768, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.2414, root_relative_squared_error: 0.6603, scimark_benchmark: 933.3136,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9627, f_measure: 0.857, kappa: 0.7223, kb_relative_information_score: 41.9537, mean_absolute_error: 0.0894, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.8912, predictive_accuracy: 0.8689, prior_entropy: 1.5019, recall: 0.8689, relative_absolute_error: 0.3268, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.2203, root_relative_squared_error: 0.6027, scimark_benchmark: 940.3347,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9629, f_measure: 0.8963, kappa: 0.8048, kb_relative_information_score: 46.0253, mean_absolute_error: 0.0682, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.9012, predictive_accuracy: 0.9016, prior_entropy: 1.5019, recall: 0.9016, relative_absolute_error: 0.2495, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.1928, root_relative_squared_error: 0.5274, scimark_benchmark: 1318.1432, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4987, kb_relative_information_score: -2.0414, mean_absolute_error: 0.2964, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.4088, predictive_accuracy: 0.6393, prior_entropy: 1.5019, recall: 0.6393, relative_absolute_error: 1.0838, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.379, root_relative_squared_error: 1.0369, scimark_benchmark: 887.6719, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9439, f_measure: 0.9504, kappa: 0.907, kb_relative_information_score: 14.0414, mean_absolute_error: 0.2555, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.954, predictive_accuracy: 0.9508, prior_entropy: 1.5019, recall: 0.9508, relative_absolute_error: 0.934, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.3204, root_relative_squared_error: 0.8766, scimark_benchmark: 933.3136, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9985, f_measure: 0.9662, kappa: 0.9385, kb_relative_information_score: 51.4242, mean_absolute_error: 0.036, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.9696, predictive_accuracy: 0.9672, prior_entropy: 1.5019, recall: 0.9672, relative_absolute_error: 0.1316, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.1073, root_relative_squared_error: 0.2934, scimark_benchmark: 1304.9611, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9823, f_measure: 0.9676, kappa: 0.9391, kb_relative_information_score: 54.8243, mean_absolute_error: 0.0164, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.9737, predictive_accuracy: 0.9672, prior_entropy: 1.5019, recall: 0.9672, relative_absolute_error: 0.0599, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.128, root_relative_squared_error: 0.3502, scimark_benchmark: 1331.6907,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 0.9523, kappa: 0.9091, kb_relative_information_score: 53.5599, mean_absolute_error: 0.0222, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.9663, predictive_accuracy: 0.9508, prior_entropy: 1.5019, recall: 0.9508, relative_absolute_error: 0.0812, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.1189, root_relative_squared_error: 0.3253, scimark_benchmark: 1250.8301,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9944, f_measure: 0.9328, kappa: 0.8745, kb_relative_information_score: 47.968, mean_absolute_error: 0.0506, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.9401, predictive_accuracy: 0.9344, prior_entropy: 1.5019, recall: 0.9344, relative_absolute_error: 0.1851, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.1676, root_relative_squared_error: 0.4584, scimark_benchmark: 1304.6687, usercpu_time_millis: 160, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 150,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9956, f_measure: 0.931, kappa: 0.8714, kb_relative_information_score: 44.1632, mean_absolute_error: 0.0879, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.935, predictive_accuracy: 0.9344, prior_entropy: 1.5019, recall: 0.9344, relative_absolute_error: 0.3214, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.1678, root_relative_squared_error: 0.4592, scimark_benchmark: 1280.6952, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9348, f_measure: 0.8667, kappa: 0.751, kb_relative_information_score: 43.3582, mean_absolute_error: 0.0612, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.8652, predictive_accuracy: 0.8689, prior_entropy: 1.5019, recall: 0.8689, relative_absolute_error: 0.2237, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.2289, root_relative_squared_error: 0.6262, scimark_benchmark: 1346.9602,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9144, f_measure: 0.8351, kappa: 0.693, kb_relative_information_score: 39.5627, mean_absolute_error: 0.0988, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.8506, predictive_accuracy: 0.8361, prior_entropy: 1.5019, recall: 0.8361, relative_absolute_error: 0.3613, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.2643, root_relative_squared_error: 0.7231, scimark_benchmark: 1306.6379,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9956, f_measure: 0.9288, kappa: 0.9064, kb_relative_information_score: 52.0863, mean_absolute_error: 0.0259, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.9109, predictive_accuracy: 0.9508, prior_entropy: 1.5019, recall: 0.9508, relative_absolute_error: 0.0945, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.1365, root_relative_squared_error: 0.3734, scimark_benchmark: 1376.7478, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.911, f_measure: 0.9156, kappa: 0.8415, kb_relative_information_score: 48.993, mean_absolute_error: 0.041, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.9177, predictive_accuracy: 0.918, prior_entropy: 1.5019, recall: 0.918, relative_absolute_error: 0.1498, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.2024, root_relative_squared_error: 0.5538, scimark_benchmark: 1425.1294,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9829, f_measure: 0.9324, kappa: 0.876, kb_relative_information_score: 50.5673, mean_absolute_error: 0.0415, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.9342, predictive_accuracy: 0.9344, prior_entropy: 1.5019, recall: 0.9344, relative_absolute_error: 0.1516, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.155, root_relative_squared_error: 0.424, scimark_benchmark: 933.1776, usercpu_time_millis: 2630, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 2620,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5431, f_measure: 0.1503, kappa: 0.0372, kb_relative_information_score: -24.5263, mean_absolute_error: 0.4344, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.642, predictive_accuracy: 0.1311, prior_entropy: 1.5019, recall: 0.1311, relative_absolute_error: 1.5883, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.6591, root_relative_squared_error: 1.803, scimark_benchmark: 1339.4189,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9909, f_measure: 0.9839, kappa: 0.9694, kb_relative_information_score: 56.5321, mean_absolute_error: 0.0082, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.9859, predictive_accuracy: 0.9836, prior_entropy: 1.5019, recall: 0.9836, relative_absolute_error: 0.03, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.0905, root_relative_squared_error: 0.2477, scimark_benchmark: 1339.4189,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9597, f_measure: 0.9128, kappa: 0.8757, kb_relative_information_score: 48.3144, mean_absolute_error: 0.0328, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.8941, predictive_accuracy: 0.9344, prior_entropy: 1.5019, recall: 0.9344, relative_absolute_error: 0.1199, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.1811, root_relative_squared_error: 0.4953, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9597, f_measure: 0.9128, kappa: 0.8757, kb_relative_information_score: 48.3144, mean_absolute_error: 0.0328, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.8941, predictive_accuracy: 0.9344, prior_entropy: 1.5019, recall: 0.9344, relative_absolute_error: 0.1199, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.1811, root_relative_squared_error: 0.4953, scimark_benchmark: 1505.597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4052, f_measure: 0.4987, kb_relative_information_score: -0.3132, mean_absolute_error: 0.2752, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.4088, predictive_accuracy: 0.6393, prior_entropy: 1.5019, recall: 0.6393, relative_absolute_error: 1.0063, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.3672, root_relative_squared_error: 1.0044, scimark_benchmark: 1505.597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9909, f_measure: 0.9839, kappa: 0.9694, kb_relative_information_score: 56.5321, mean_absolute_error: 0.0082, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.9859, predictive_accuracy: 0.9836, prior_entropy: 1.5019, recall: 0.9836, relative_absolute_error: 0.03, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.0905, root_relative_squared_error: 0.2477, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9786, f_measure: 0.9505, kappa: 0.908, kb_relative_information_score: 52.05, mean_absolute_error: 0.0249, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.9577, predictive_accuracy: 0.9508, prior_entropy: 1.5019, recall: 0.9508, relative_absolute_error: 0.091, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.1568, root_relative_squared_error: 0.4291, scimark_benchmark: 942.6953,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9786, f_measure: 0.9505, kappa: 0.908, kb_relative_information_score: 52.05, mean_absolute_error: 0.0249, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.9577, predictive_accuracy: 0.9508, prior_entropy: 1.5019, recall: 0.9508, relative_absolute_error: 0.091, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.1568, root_relative_squared_error: 0.4291, scimark_benchmark: 926.6717, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9786, f_measure: 0.9505, kappa: 0.908, kb_relative_information_score: 52.05, mean_absolute_error: 0.0249, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.9577, predictive_accuracy: 0.9508, prior_entropy: 1.5019, recall: 0.9508, relative_absolute_error: 0.091, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.1568, root_relative_squared_error: 0.4291, scimark_benchmark: 926.6717, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9459, f_measure: 0.7977, kappa: 0.7132, kb_relative_information_score: 29.091, mean_absolute_error: 0.1578, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.7653, predictive_accuracy: 0.8525, prior_entropy: 1.5019, recall: 0.8525, relative_absolute_error: 0.5768, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.2414, root_relative_squared_error: 0.6603, scimark_benchmark: 894.7455,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9459, f_measure: 0.7977, kappa: 0.7132, kb_relative_information_score: 29.091, mean_absolute_error: 0.1578, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.7653, predictive_accuracy: 0.8525, prior_entropy: 1.5019, recall: 0.8525, relative_absolute_error: 0.5768, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.2414, root_relative_squared_error: 0.6603, scimark_benchmark: 943.2817,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9459, f_measure: 0.7977, kappa: 0.7132, kb_relative_information_score: 29.091, mean_absolute_error: 0.1578, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.7653, predictive_accuracy: 0.8525, prior_entropy: 1.5019, recall: 0.8525, relative_absolute_error: 0.5768, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.2414, root_relative_squared_error: 0.6603, scimark_benchmark: 911.3823,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.925, f_measure: 0.7977, kappa: 0.7132, kb_relative_information_score: 31.0051, mean_absolute_error: 0.1234, mean_prior_absolute_error: 0.2735, number_of_instances: 61, precision: 0.7653, predictive_accuracy: 0.8525, prior_entropy: 1.5019, recall: 0.8525, relative_absolute_error: 0.4513, root_mean_prior_squared_error: 0.3656, root_mean_squared_error: 0.2682, root_relative_squared_error: 0.7335, scimark_benchmark: 933.8635,
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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