OpenML
Supervised Classification on primary-tumor

Supervised Classification on primary-tumor

Task 2065 Supervised Classification primary-tumor 543 runs submitted
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  • study_1 study_107 study_41 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5307, build_cpu_time: 0.0012, build_memory: 1523130896, f_measure: 0.1412, kappa: 0.07, kb_relative_information_score: 54.0317, mean_absolute_error: 0.066, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.1063, predictive_accuracy: 0.2743, prior_entropy: 3.7542, recall: 0.2743, relative_absolute_error: 0.8123, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2568, root_relative_squared_error: 1.2773, scimark_benchmark: 909.5718,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5307, build_cpu_time: 0.003, build_memory: 709313422.6313, f_measure: 0.1412, kappa: 0.07, kb_relative_information_score: 54.0317, mean_absolute_error: 0.066, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.1063, predictive_accuracy: 0.2743, prior_entropy: 3.7542, recall: 0.2743, relative_absolute_error: 0.8123, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2568, root_relative_squared_error: 1.2773, scimark_benchmark: 916.8903,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5307, build_cpu_time: 0.0031, build_memory: 710535366.9145, f_measure: 0.1412, kappa: 0.07, kb_relative_information_score: 54.0317, mean_absolute_error: 0.066, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.1063, predictive_accuracy: 0.2743, prior_entropy: 3.7542, recall: 0.2743, relative_absolute_error: 0.8123, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2568, root_relative_squared_error: 1.2773, scimark_benchmark: 927.3354,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7209, build_cpu_time: 1.9802, build_memory: 1133630522.1947, f_measure: 0.4127, kappa: 0.3512, kb_relative_information_score: 101.2236, mean_absolute_error: 0.061, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4048, predictive_accuracy: 0.4277, prior_entropy: 3.7542, recall: 0.4277, relative_absolute_error: 0.7511, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2001, root_relative_squared_error: 0.9949, scimark_benchmark: 942.3945,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7582, build_cpu_time: 0.0219, build_memory: 1031822641.8879, f_measure: 0.4664, kappa: 0.4408, kb_relative_information_score: 70.7118, mean_absolute_error: 0.0714, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4457, predictive_accuracy: 0.5074, prior_entropy: 3.7542, recall: 0.5074, relative_absolute_error: 0.8797, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.192, root_relative_squared_error: 0.9549, scimark_benchmark: 937.9119,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5307, build_cpu_time: 0.0014, build_memory: 179981795.3982, f_measure: 0.1412, kappa: 0.07, kb_relative_information_score: 54.0317, mean_absolute_error: 0.066, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.1063, predictive_accuracy: 0.2743, prior_entropy: 3.7542, recall: 0.2743, relative_absolute_error: 0.8123, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2568, root_relative_squared_error: 1.2773, scimark_benchmark: 929.5397,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7582, build_cpu_time: 0.0337, build_memory: 843973761.3215, f_measure: 0.4664, kappa: 0.4408, kb_relative_information_score: 70.7118, mean_absolute_error: 0.0714, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4457, predictive_accuracy: 0.5074, prior_entropy: 3.7542, recall: 0.5074, relative_absolute_error: 0.8797, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.192, root_relative_squared_error: 0.9549, scimark_benchmark: 909.5718,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7582, build_cpu_time: 0.0203, build_memory: 619880731.823, f_measure: 0.4664, kappa: 0.4408, kb_relative_information_score: 70.7118, mean_absolute_error: 0.0714, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4457, predictive_accuracy: 0.5074, prior_entropy: 3.7542, recall: 0.5074, relative_absolute_error: 0.8797, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.192, root_relative_squared_error: 0.9549, scimark_benchmark: 908.8705,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5307, build_cpu_time: 0.002, build_memory: 954765765.0501, f_measure: 0.1412, kappa: 0.07, kb_relative_information_score: 54.0317, mean_absolute_error: 0.066, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.1063, predictive_accuracy: 0.2743, prior_entropy: 3.7542, recall: 0.2743, relative_absolute_error: 0.8123, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2568, root_relative_squared_error: 1.2773, scimark_benchmark: 925.481,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7209, build_cpu_time: 1.8977, build_memory: 644908379.7286, f_measure: 0.4127, kappa: 0.3512, kb_relative_information_score: 101.2236, mean_absolute_error: 0.061, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4048, predictive_accuracy: 0.4277, prior_entropy: 3.7542, recall: 0.4277, relative_absolute_error: 0.7511, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2001, root_relative_squared_error: 0.9949, scimark_benchmark: 937.5757,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.767, f_measure: 0.426, kappa: 0.3789, kb_relative_information_score: 89.582, mean_absolute_error: 0.0706, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.413, predictive_accuracy: 0.4543, prior_entropy: 3.7542, recall: 0.4543, relative_absolute_error: 0.8694, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1849, root_relative_squared_error: 0.9194, scimark_benchmark: 929.566, usercpu_time_millis: 1770, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 1750,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7986, f_measure: 0.4113, kappa: 0.397, kb_relative_information_score: 99.9099, mean_absolute_error: 0.0668, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3819, predictive_accuracy: 0.4867, prior_entropy: 3.7542, recall: 0.4867, relative_absolute_error: 0.8222, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1783, root_relative_squared_error: 0.8866, scimark_benchmark: 910.8389, usercpu_time_millis: 320, usercpu_time_millis_testing: 150, usercpu_time_millis_training: 170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7179, build_cpu_time: 2.4311, build_memory: 736579835.4218, f_measure: 0.4385, kappa: 0.3976, kb_relative_information_score: 20.9663, mean_absolute_error: 0.0846, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4177, predictive_accuracy: 0.4749, prior_entropy: 3.7542, recall: 0.4749, relative_absolute_error: 1.0417, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2033, root_relative_squared_error: 1.0112, scimark_benchmark: 922.6953,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7104, f_measure: 0.3546, kappa: 0.28, kb_relative_information_score: 15.2236, mean_absolute_error: 0.0853, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3502, predictive_accuracy: 0.3658, prior_entropy: 3.7542, recall: 0.3658, relative_absolute_error: 1.0505, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2049, root_relative_squared_error: 1.0192, scimark_benchmark: 911.3823, usercpu_time_millis: 1030, usercpu_time_millis_training: 1030,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4473, f_measure: 0.0984, kb_relative_information_score: 0.3006, mean_absolute_error: 0.0813, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.0614, predictive_accuracy: 0.2478, prior_entropy: 3.7542, recall: 0.2478, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2012, root_relative_squared_error: 1.0004, scimark_benchmark: 923.3111, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8352, f_measure: 0.423, kappa: 0.3825, kb_relative_information_score: 128.393, mean_absolute_error: 0.0596, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3996, predictive_accuracy: 0.4602, prior_entropy: 3.7542, recall: 0.4602, relative_absolute_error: 0.7337, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1739, root_relative_squared_error: 0.865, scimark_benchmark: 941.7954, usercpu_time_millis: 80, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7672, f_measure: 0.4098, kappa: 0.3545, kb_relative_information_score: 114.8626, mean_absolute_error: 0.061, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4007, predictive_accuracy: 0.4277, prior_entropy: 3.7542, recall: 0.4277, relative_absolute_error: 0.7513, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1925, root_relative_squared_error: 0.9574, scimark_benchmark: 929.566, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.676, f_measure: 0.17, kappa: 0.1196, kb_relative_information_score: 44.4081, mean_absolute_error: 0.0762, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.1289, predictive_accuracy: 0.2832, prior_entropy: 3.7542, recall: 0.2832, relative_absolute_error: 0.9389, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.194, root_relative_squared_error: 0.9649, scimark_benchmark: 901.0726,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7165, f_measure: 0.3361, kappa: 0.3005, kb_relative_information_score: 93.7416, mean_absolute_error: 0.0683, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3102, predictive_accuracy: 0.3982, prior_entropy: 3.7542, recall: 0.3982, relative_absolute_error: 0.8405, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1908, root_relative_squared_error: 0.9489, scimark_benchmark: 942.442,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7976, f_measure: 0.4322, kappa: 0.4081, kb_relative_information_score: 116.4382, mean_absolute_error: 0.0648, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4485, predictive_accuracy: 0.4808, prior_entropy: 3.7542, recall: 0.4808, relative_absolute_error: 0.7974, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1801, root_relative_squared_error: 0.8955, scimark_benchmark: 945.4243,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7106, f_measure: 0.309, kappa: 0.2837, kb_relative_information_score: 100.9346, mean_absolute_error: 0.0655, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.2641, predictive_accuracy: 0.3953, prior_entropy: 3.7542, recall: 0.3953, relative_absolute_error: 0.806, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1927, root_relative_squared_error: 0.9583,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5307, f_measure: 0.1412, kappa: 0.07, kb_relative_information_score: 54.0317, mean_absolute_error: 0.066, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.1063, predictive_accuracy: 0.2743, prior_entropy: 3.7542, recall: 0.2743, relative_absolute_error: 0.8123, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2568, root_relative_squared_error: 1.2773,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8127, f_measure: 0.3705, kappa: 0.3477, kb_relative_information_score: 111.3732, mean_absolute_error: 0.0652, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3373, predictive_accuracy: 0.4425, prior_entropy: 3.7542, recall: 0.4425, relative_absolute_error: 0.8028, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.179, root_relative_squared_error: 0.8904, scimark_benchmark: 898.1745,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.762, f_measure: 0.4616, kappa: 0.4343, kb_relative_information_score: 74.7031, mean_absolute_error: 0.0709, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4396, predictive_accuracy: 0.5015, prior_entropy: 3.7542, recall: 0.5015, relative_absolute_error: 0.873, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1908, root_relative_squared_error: 0.9491, scimark_benchmark: 940.452,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7302, f_measure: 0.3801, kappa: 0.3118, kb_relative_information_score: 88.4638, mean_absolute_error: 0.0656, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3752, predictive_accuracy: 0.3923, prior_entropy: 3.7542, recall: 0.3923, relative_absolute_error: 0.8077, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1938, root_relative_squared_error: 0.9637, scimark_benchmark: 938.6724,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4473, f_measure: 0.0984, kb_relative_information_score: 0.3006, mean_absolute_error: 0.0813, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.0614, predictive_accuracy: 0.2478, prior_entropy: 3.7542, recall: 0.2478, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2012, root_relative_squared_error: 1.0004, scimark_benchmark: 945.3119,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5307, f_measure: 0.1412, kappa: 0.07, kb_relative_information_score: 54.0317, mean_absolute_error: 0.066, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.1063, predictive_accuracy: 0.2743, prior_entropy: 3.7542, recall: 0.2743, relative_absolute_error: 0.8123, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2568, root_relative_squared_error: 1.2773,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5307, f_measure: 0.1412, kappa: 0.07, kb_relative_information_score: 54.0317, mean_absolute_error: 0.066, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.1063, predictive_accuracy: 0.2743, prior_entropy: 3.7542, recall: 0.2743, relative_absolute_error: 0.8123, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2568, root_relative_squared_error: 1.2773, scimark_benchmark: 944.9338,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6371, f_measure: 0.1864, kappa: 0.152, kb_relative_information_score: 55.41, mean_absolute_error: 0.0746, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.151, predictive_accuracy: 0.2891, prior_entropy: 3.7542, recall: 0.2891, relative_absolute_error: 0.9182, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1935, root_relative_squared_error: 0.9624, scimark_benchmark: 925.4753,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6185, f_measure: 0.2743, kappa: 0.2249, kb_relative_information_score: 67.2716, mean_absolute_error: 0.07, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.2418, predictive_accuracy: 0.3746, prior_entropy: 3.7542, recall: 0.3746, relative_absolute_error: 0.8621, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1944, root_relative_squared_error: 0.9668, scimark_benchmark: 946.2036,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7753, f_measure: 0.4095, kappa: 0.3456, kb_relative_information_score: 26.1339, mean_absolute_error: 0.0837, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4105, predictive_accuracy: 0.4218, prior_entropy: 3.7542, recall: 0.4218, relative_absolute_error: 1.031, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2027, root_relative_squared_error: 1.0078, scimark_benchmark: 908.6779,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.757, f_measure: 0.3974, kappa: 0.3447, kb_relative_information_score: 116.01, mean_absolute_error: 0.0618, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3835, predictive_accuracy: 0.4218, prior_entropy: 3.7542, recall: 0.4218, relative_absolute_error: 0.7614, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1936, root_relative_squared_error: 0.9629,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7172, f_measure: 0.3494, kappa: 0.3098, kb_relative_information_score: 108.2828, mean_absolute_error: 0.0635, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3189, predictive_accuracy: 0.4012, prior_entropy: 3.7542, recall: 0.4012, relative_absolute_error: 0.7813, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1944, root_relative_squared_error: 0.9669, scimark_benchmark: 940.202,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.757, f_measure: 0.3839, kappa: 0.3115, kb_relative_information_score: 77.96, mean_absolute_error: 0.0714, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3807, predictive_accuracy: 0.3894, prior_entropy: 3.7542, recall: 0.3894, relative_absolute_error: 0.8797, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1878, root_relative_squared_error: 0.9338, scimark_benchmark: 947.3192,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4812, f_measure: 0.0984, kb_relative_information_score: 7.9553, mean_absolute_error: 0.0844, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.0614, predictive_accuracy: 0.2478, prior_entropy: 3.7542, recall: 0.2478, relative_absolute_error: 1.0388, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2043, root_relative_squared_error: 1.0159, scimark_benchmark: 929.9831,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7837, f_measure: 0.4283, kappa: 0.3962, kb_relative_information_score: 123.7883, mean_absolute_error: 0.0621, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4178, predictive_accuracy: 0.4661, prior_entropy: 3.7542, recall: 0.4661, relative_absolute_error: 0.7652, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1818, root_relative_squared_error: 0.9041, scimark_benchmark: 946.0328,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8103, f_measure: 0.3677, kappa: 0.342, kb_relative_information_score: 110.0993, mean_absolute_error: 0.0653, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3331, predictive_accuracy: 0.4366, prior_entropy: 3.7542, recall: 0.4366, relative_absolute_error: 0.8037, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1795, root_relative_squared_error: 0.8928,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.782, f_measure: 0.4141, kappa: 0.3616, kb_relative_information_score: 112.7724, mean_absolute_error: 0.0577, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3982, predictive_accuracy: 0.4366, prior_entropy: 3.7542, recall: 0.4366, relative_absolute_error: 0.71, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1914, root_relative_squared_error: 0.9521, scimark_benchmark: 915.7636,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6414, f_measure: 0.1864, kappa: 0.152, kb_relative_information_score: 55.6617, mean_absolute_error: 0.0746, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.151, predictive_accuracy: 0.2891, prior_entropy: 3.7542, recall: 0.2891, relative_absolute_error: 0.9182, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1935, root_relative_squared_error: 0.9623, scimark_benchmark: 885.6917,

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