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OpenML
Task
Supervised Classification on grub-damage

Supervised Classification on grub-damage

Task 3497 Supervised Classification grub-damage 506 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • study_1 study_107 study_41 study_7 under100k under1m
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506 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6888, f_measure: 0.4244, kappa: 0.2172, kb_relative_information_score: 45.9052, mean_absolute_error: 0.2938, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.4344, predictive_accuracy: 0.4387, prior_entropy: 1.9281, recall: 0.4387, relative_absolute_error: 0.8076, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4297, root_relative_squared_error: 1.0079, scimark_benchmark: 1442.7264,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5686, f_measure: 0.3013, kappa: 0.1382, kb_relative_information_score: 19.6569, mean_absolute_error: 0.3419, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.2645, predictive_accuracy: 0.4065, prior_entropy: 1.9281, recall: 0.4065, relative_absolute_error: 0.9399, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4349, root_relative_squared_error: 1.0202, scimark_benchmark: 934.4732, usercpu_time_millis: 80, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.694, f_measure: 0.4743, kappa: 0.2759, kb_relative_information_score: 36.0517, mean_absolute_error: 0.322, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.4743, predictive_accuracy: 0.4774, prior_entropy: 1.9281, recall: 0.4774, relative_absolute_error: 0.8853, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4096, root_relative_squared_error: 0.9607, scimark_benchmark: 1369.9744, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6879, f_measure: 0.4493, kappa: 0.243, kb_relative_information_score: 37.4321, mean_absolute_error: 0.3092, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.4489, predictive_accuracy: 0.4516, prior_entropy: 1.9281, recall: 0.4516, relative_absolute_error: 0.85, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4222, root_relative_squared_error: 0.9904, scimark_benchmark: 942.9518, usercpu_time_millis: 80, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6098, f_measure: 0.4373, kappa: 0.2219, kb_relative_information_score: 46.0034, mean_absolute_error: 0.2806, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.4396, predictive_accuracy: 0.4387, prior_entropy: 1.9281, recall: 0.4387, relative_absolute_error: 0.7715, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.5298, root_relative_squared_error: 1.2426, scimark_benchmark: 916.9356, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6648, f_measure: 0.4158, kappa: 0.1966, kb_relative_information_score: 39.5739, mean_absolute_error: 0.3052, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.4211, predictive_accuracy: 0.4129, prior_entropy: 1.9281, recall: 0.4129, relative_absolute_error: 0.8389, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4626, root_relative_squared_error: 1.0851, scimark_benchmark: 1337.7959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6992, f_measure: 0.4838, kappa: 0.2973, kb_relative_information_score: 47.27, mean_absolute_error: 0.2877, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.4858, predictive_accuracy: 0.4903, prior_entropy: 1.9281, recall: 0.4903, relative_absolute_error: 0.7908, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4211, root_relative_squared_error: 0.9878, scimark_benchmark: 1335.4072, usercpu_time_millis: 220, usercpu_time_millis_training: 220,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6481, f_measure: 0.3707, kappa: 0.1361, kb_relative_information_score: 30.9588, mean_absolute_error: 0.3254, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.3719, predictive_accuracy: 0.3742, prior_entropy: 1.9281, recall: 0.3742, relative_absolute_error: 0.8944, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4362, root_relative_squared_error: 1.0232, scimark_benchmark: 1315.3881, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5298, f_measure: 0.3274, kappa: 0.0752, kb_relative_information_score: 19.8264, mean_absolute_error: 0.3462, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.3225, predictive_accuracy: 0.3355, prior_entropy: 1.9281, recall: 0.3355, relative_absolute_error: 0.9517, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.5562, root_relative_squared_error: 1.3046, scimark_benchmark: 1346.9602,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6583, f_measure: 0.4066, kappa: 0.1954, kb_relative_information_score: 36.4219, mean_absolute_error: 0.3171, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.4067, predictive_accuracy: 0.4194, prior_entropy: 1.9281, recall: 0.4194, relative_absolute_error: 0.8716, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4343, root_relative_squared_error: 1.0187, scimark_benchmark: 1306.6379,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6283, f_measure: 0.4714, kappa: 0.2898, kb_relative_information_score: 33.3335, mean_absolute_error: 0.3178, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.5013, predictive_accuracy: 0.4968, prior_entropy: 1.9281, recall: 0.4968, relative_absolute_error: 0.8736, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4208, root_relative_squared_error: 0.987, scimark_benchmark: 1346.9602, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5903, f_measure: 0.4044, kappa: 0.1802, kb_relative_information_score: 39.2555, mean_absolute_error: 0.2968, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.4031, predictive_accuracy: 0.4065, prior_entropy: 1.9281, recall: 0.4065, relative_absolute_error: 0.8158, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.5448, root_relative_squared_error: 1.2778, scimark_benchmark: 1306.6379,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.531, f_measure: 0.2817, kappa: 0.0598, kb_relative_information_score: 24.171, mean_absolute_error: 0.329, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.2994, predictive_accuracy: 0.3419, prior_entropy: 1.9281, recall: 0.3419, relative_absolute_error: 0.9045, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.5736, root_relative_squared_error: 1.3455, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.611, f_measure: 0.3349, kappa: 0.0792, kb_relative_information_score: 31.7379, mean_absolute_error: 0.3241, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.3387, predictive_accuracy: 0.3355, prior_entropy: 1.9281, recall: 0.3355, relative_absolute_error: 0.8909, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4657, root_relative_squared_error: 1.0923, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6082, f_measure: 0.4213, kappa: 0.2157, kb_relative_information_score: 44.3507, mean_absolute_error: 0.2839, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.4251, predictive_accuracy: 0.4323, prior_entropy: 1.9281, recall: 0.4323, relative_absolute_error: 0.7803, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.5328, root_relative_squared_error: 1.2497, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6348, f_measure: 0.4122, kappa: 0.1881, kb_relative_information_score: 40.521, mean_absolute_error: 0.2935, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.4138, predictive_accuracy: 0.4129, prior_entropy: 1.9281, recall: 0.4129, relative_absolute_error: 0.8068, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.5344, root_relative_squared_error: 1.2536, scimark_benchmark: 917.4321, usercpu_time_millis: 29180, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 29150,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5828, f_measure: 0.386, kappa: 0.1704, kb_relative_information_score: 39.3621, mean_absolute_error: 0.3032, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.3809, predictive_accuracy: 0.3935, prior_entropy: 1.9281, recall: 0.3935, relative_absolute_error: 0.8335, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.5507, root_relative_squared_error: 1.2916, scimark_benchmark: 1363.434,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4726, f_measure: 0.1519, kb_relative_information_score: 0.1522, mean_absolute_error: 0.3639, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.0999, predictive_accuracy: 0.3161, prior_entropy: 1.9281, recall: 0.3161, relative_absolute_error: 1.0004, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4264, root_relative_squared_error: 1.0003, scimark_benchmark: 1503.3362,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6293, f_measure: 0.3799, kappa: 0.1506, kb_relative_information_score: 35.6518, mean_absolute_error: 0.3171, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.3771, predictive_accuracy: 0.3871, prior_entropy: 1.9281, recall: 0.3871, relative_absolute_error: 0.8715, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4733, root_relative_squared_error: 1.1101, scimark_benchmark: 1605.6303,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6761, f_measure: 0.4875, kappa: 0.2987, kb_relative_information_score: 32.1013, mean_absolute_error: 0.3226, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.4875, predictive_accuracy: 0.4903, prior_entropy: 1.9281, recall: 0.4903, relative_absolute_error: 0.8867, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4187, root_relative_squared_error: 0.982, scimark_benchmark: 945.7621, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6753, f_measure: 0.5073, kappa: 0.3274, kb_relative_information_score: 27.3543, mean_absolute_error: 0.337, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.5098, predictive_accuracy: 0.5097, prior_entropy: 1.9281, recall: 0.5097, relative_absolute_error: 0.9263, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4056, root_relative_squared_error: 0.9515, scimark_benchmark: 943.2817, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6753, f_measure: 0.5073, kappa: 0.3274, kb_relative_information_score: 27.3543, mean_absolute_error: 0.337, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.5098, predictive_accuracy: 0.5097, prior_entropy: 1.9281, recall: 0.5097, relative_absolute_error: 0.9263, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4056, root_relative_squared_error: 0.9515, scimark_benchmark: 943.2817, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6753, f_measure: 0.5073, kappa: 0.3274, kb_relative_information_score: 27.3543, mean_absolute_error: 0.337, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.5098, predictive_accuracy: 0.5097, prior_entropy: 1.9281, recall: 0.5097, relative_absolute_error: 0.9263, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4056, root_relative_squared_error: 0.9515, scimark_benchmark: 943.2817, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5105, f_measure: 0.2655, kappa: 0.0437, kb_relative_information_score: 9.2862, mean_absolute_error: 0.3586, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.2435, predictive_accuracy: 0.329, prior_entropy: 1.9281, recall: 0.329, relative_absolute_error: 0.9858, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4311, root_relative_squared_error: 1.0113, scimark_benchmark: 911.3823,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5105, f_measure: 0.2655, kappa: 0.0437, kb_relative_information_score: 9.2862, mean_absolute_error: 0.3586, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.2435, predictive_accuracy: 0.329, prior_entropy: 1.9281, recall: 0.329, relative_absolute_error: 0.9858, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4311, root_relative_squared_error: 1.0113, scimark_benchmark: 936.6206,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5105, f_measure: 0.2655, kappa: 0.0437, kb_relative_information_score: 9.2862, mean_absolute_error: 0.3586, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.2435, predictive_accuracy: 0.329, prior_entropy: 1.9281, recall: 0.329, relative_absolute_error: 0.9858, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4311, root_relative_squared_error: 1.0113, scimark_benchmark: 945.6434,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5105, f_measure: 0.2655, kappa: 0.0437, kb_relative_information_score: 9.2862, mean_absolute_error: 0.3586, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.2435, predictive_accuracy: 0.329, prior_entropy: 1.9281, recall: 0.329, relative_absolute_error: 0.9858, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4311, root_relative_squared_error: 1.0113, scimark_benchmark: 938.2848,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5105, f_measure: 0.2655, kappa: 0.0437, kb_relative_information_score: 9.2862, mean_absolute_error: 0.3586, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.2435, predictive_accuracy: 0.329, prior_entropy: 1.9281, recall: 0.329, relative_absolute_error: 0.9858, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4311, root_relative_squared_error: 1.0113, scimark_benchmark: 938.4285,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6829, f_measure: 0.4659, kappa: 0.2625, kb_relative_information_score: 44.5726, mean_absolute_error: 0.2921, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.4688, predictive_accuracy: 0.4645, prior_entropy: 1.9281, recall: 0.4645, relative_absolute_error: 0.8029, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4561, root_relative_squared_error: 1.0699, scimark_benchmark: 945.7621, usercpu_time_millis: 80, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6903, f_measure: 0.432, kappa: 0.2143, kb_relative_information_score: 43.9538, mean_absolute_error: 0.2933, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.4348, predictive_accuracy: 0.4323, prior_entropy: 1.9281, recall: 0.4323, relative_absolute_error: 0.8063, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4434, root_relative_squared_error: 1.04, scimark_benchmark: 945.6434, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6973, f_measure: 0.4451, kappa: 0.232, kb_relative_information_score: 43.3931, mean_absolute_error: 0.297, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.4478, predictive_accuracy: 0.4452, prior_entropy: 1.9281, recall: 0.4452, relative_absolute_error: 0.8164, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4301, root_relative_squared_error: 1.0087, scimark_benchmark: 943.2817, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7012, f_measure: 0.4515, kappa: 0.2356, kb_relative_information_score: 42.8787, mean_absolute_error: 0.3005, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.4632, predictive_accuracy: 0.4516, prior_entropy: 1.9281, recall: 0.4516, relative_absolute_error: 0.826, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4171, root_relative_squared_error: 0.9785, scimark_benchmark: 910.8389, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6971, f_measure: 0.4366, kappa: 0.2224, kb_relative_information_score: 40.478, mean_absolute_error: 0.306, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.4367, predictive_accuracy: 0.4387, prior_entropy: 1.9281, recall: 0.4387, relative_absolute_error: 0.8412, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4112, root_relative_squared_error: 0.9646, scimark_benchmark: 931.2336,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6298, build_cpu_time: 0.0031, build_memory: 844532821.6774, f_measure: 0.3767, kappa: 0.142, kb_relative_information_score: 25.0519, mean_absolute_error: 0.3371, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.3745, predictive_accuracy: 0.3806, prior_entropy: 1.9281, recall: 0.3806, relative_absolute_error: 0.9268, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4382, root_relative_squared_error: 1.0278, scimark_benchmark: 936.1433,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6298, build_cpu_time: 0.0027, build_memory: 834466608, f_measure: 0.3767, kappa: 0.142, kb_relative_information_score: 25.0519, mean_absolute_error: 0.3371, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.3745, predictive_accuracy: 0.3806, prior_entropy: 1.9281, recall: 0.3806, relative_absolute_error: 0.9268, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.4382, root_relative_squared_error: 1.0278, scimark_benchmark: 943.4039,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5631, build_cpu_time: 0.0144, build_memory: 304835063.8968, f_measure: 0.3707, kappa: 0.1381, kb_relative_information_score: 31.9897, mean_absolute_error: 0.3192, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.369, predictive_accuracy: 0.3742, prior_entropy: 1.9281, recall: 0.3742, relative_absolute_error: 0.8776, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.5467, root_relative_squared_error: 1.2824, scimark_benchmark: 925.481,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5631, build_cpu_time: 0.0645, build_memory: 202287805.2129, f_measure: 0.3707, kappa: 0.1381, kb_relative_information_score: 31.9897, mean_absolute_error: 0.3192, mean_prior_absolute_error: 0.3638, number_of_instances: 155, precision: 0.369, predictive_accuracy: 0.3742, prior_entropy: 1.9281, recall: 0.3742, relative_absolute_error: 0.8776, root_mean_prior_squared_error: 0.4263, root_mean_squared_error: 0.5467, root_relative_squared_error: 1.2824, scimark_benchmark: 923.8078,

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