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OpenML
OpenML
Supervised Classification on sleuth_case1102

Supervised Classification on sleuth_case1102

Task 3701 Supervised Classification sleuth_case1102 500 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_107 study_15 study_20 study_41 under100k under1m
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500 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4772, f_measure: 0.4306, kappa: -0.1577, kb_relative_information_score: -1.7482, mean_absolute_error: 0.5096, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.4265, predictive_accuracy: 0.4412, prior_entropy: 0.9911, recall: 0.4412, relative_absolute_error: 1.0327, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.5959, root_relative_squared_error: 1.2, scimark_benchmark: 825.5282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5474, f_measure: 0.5282, kappa: 0.1019, kb_relative_information_score: 5.4586, mean_absolute_error: 0.4118, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.5923, predictive_accuracy: 0.5882, prior_entropy: 0.9911, recall: 0.5882, relative_absolute_error: 0.8344, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.6417, root_relative_squared_error: 1.2923, scimark_benchmark: 930.5999, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4007, kb_relative_information_score: 3.4225, mean_absolute_error: 0.4412, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3123, predictive_accuracy: 0.5588, prior_entropy: 0.9911, recall: 0.5588, relative_absolute_error: 0.894, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.6642, root_relative_squared_error: 1.3377, scimark_benchmark: 882.7843, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3561, f_measure: 0.3565, kappa: -0.2982, kb_relative_information_score: -8.794, mean_absolute_error: 0.6176, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3444, predictive_accuracy: 0.3824, prior_entropy: 0.9911, recall: 0.3824, relative_absolute_error: 1.2517, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.7859, root_relative_squared_error: 1.5828, scimark_benchmark: 1386.5717,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4175, f_measure: 0.3725, kappa: -0.1158, kb_relative_information_score: -2.5833, mean_absolute_error: 0.5242, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.2969, predictive_accuracy: 0.5, prior_entropy: 0.9911, recall: 0.5, relative_absolute_error: 1.0622, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.5305, root_relative_squared_error: 1.0684, scimark_benchmark: 887.6719, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4421, f_measure: 0.4405, kappa: -0.1209, kb_relative_information_score: -2.6857, mean_absolute_error: 0.5294, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.4376, predictive_accuracy: 0.4706, prior_entropy: 0.9911, recall: 0.4706, relative_absolute_error: 1.0728, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.7276, root_relative_squared_error: 1.4654, scimark_benchmark: 916.5955,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3614, f_measure: 0.4055, kappa: -0.21, kb_relative_information_score: -3.35, mean_absolute_error: 0.5315, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.4019, predictive_accuracy: 0.4118, prior_entropy: 0.9911, recall: 0.4118, relative_absolute_error: 1.0772, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.5644, root_relative_squared_error: 1.1366, scimark_benchmark: 876.0664, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4316, f_measure: 0.3945, kappa: -0.2274, kb_relative_information_score: -2.3226, mean_absolute_error: 0.5198, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3876, predictive_accuracy: 0.4118, prior_entropy: 0.9911, recall: 0.4118, relative_absolute_error: 1.0534, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.5542, root_relative_squared_error: 1.1161, scimark_benchmark: 1350.9691,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3754, f_measure: 0.4055, kappa: -0.21, kb_relative_information_score: -3.5935, mean_absolute_error: 0.5356, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.4019, predictive_accuracy: 0.4118, prior_entropy: 0.9911, recall: 0.4118, relative_absolute_error: 1.0854, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.5614, root_relative_squared_error: 1.1306, scimark_benchmark: 1315.0767, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3579, f_measure: 0.3529, kappa: -0.2765, kb_relative_information_score: -10.8301, mean_absolute_error: 0.6471, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3628, predictive_accuracy: 0.3529, prior_entropy: 0.9911, recall: 0.3529, relative_absolute_error: 1.3113, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.8044, root_relative_squared_error: 1.62, scimark_benchmark: 1307.4861,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3263, f_measure: 0.3725, kappa: -0.1158, kb_relative_information_score: -2.2978, mean_absolute_error: 0.5218, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.2969, predictive_accuracy: 0.5, prior_entropy: 0.9911, recall: 0.5, relative_absolute_error: 1.0574, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.5318, root_relative_squared_error: 1.0711, scimark_benchmark: 1318.5526,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3895, f_measure: 0.4007, kb_relative_information_score: -0.1808, mean_absolute_error: 0.4953, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3123, predictive_accuracy: 0.5588, prior_entropy: 0.9911, recall: 0.5588, relative_absolute_error: 1.0036, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.499, root_relative_squared_error: 1.0049, scimark_benchmark: 1355.7054,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3316, f_measure: 0.3206, kappa: -0.3254, kb_relative_information_score: -12.8662, mean_absolute_error: 0.6765, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3319, predictive_accuracy: 0.3235, prior_entropy: 0.9911, recall: 0.3235, relative_absolute_error: 1.3709, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.8225, root_relative_squared_error: 1.6564, scimark_benchmark: 1372.2145,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4007, kb_relative_information_score: 3.4225, mean_absolute_error: 0.4412, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3123, predictive_accuracy: 0.5588, prior_entropy: 0.9911, recall: 0.5588, relative_absolute_error: 0.894, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.6642, root_relative_squared_error: 1.3377, scimark_benchmark: 1287.514,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5702, f_measure: 0.531, kappa: 0.0588, kb_relative_information_score: 0.9557, mean_absolute_error: 0.4805, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.5363, predictive_accuracy: 0.5294, prior_entropy: 0.9911, recall: 0.5294, relative_absolute_error: 0.9737, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.5881, root_relative_squared_error: 1.1843, scimark_benchmark: 1392.1129,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3825, f_measure: 0.3783, kappa: -0.2454, kb_relative_information_score: -6.7579, mean_absolute_error: 0.5882, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3663, predictive_accuracy: 0.4118, prior_entropy: 0.9911, recall: 0.4118, relative_absolute_error: 1.1921, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.767, root_relative_squared_error: 1.5446, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3632, f_measure: 0.3706, kappa: -0.2796, kb_relative_information_score: -8.794, mean_absolute_error: 0.6176, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3643, predictive_accuracy: 0.3824, prior_entropy: 0.9911, recall: 0.3824, relative_absolute_error: 1.2517, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.7859, root_relative_squared_error: 1.5828, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3895, f_measure: 0.4007, kb_relative_information_score: -0.2156, mean_absolute_error: 0.4955, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3123, predictive_accuracy: 0.5588, prior_entropy: 0.9911, recall: 0.5588, relative_absolute_error: 1.0042, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.4988, root_relative_squared_error: 1.0046, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4211, f_measure: 0.4649, kappa: -0.089, kb_relative_information_score: -3.2197, mean_absolute_error: 0.5419, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.4624, predictive_accuracy: 0.4706, prior_entropy: 0.9911, recall: 0.4706, relative_absolute_error: 1.0981, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.6448, root_relative_squared_error: 1.2986, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.2035, f_measure: 0.254, kappa: -0.4945, kb_relative_information_score: -14.5408, mean_absolute_error: 0.6905, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.2235, predictive_accuracy: 0.2941, prior_entropy: 0.9911, recall: 0.2941, relative_absolute_error: 1.3992, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.7728, root_relative_squared_error: 1.5564, scimark_benchmark: 931.2336,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3246, f_measure: 0.3107, kappa: -0.4014, kb_relative_information_score: -9.1081, mean_absolute_error: 0.6121, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3021, predictive_accuracy: 0.3235, prior_entropy: 0.9911, recall: 0.3235, relative_absolute_error: 1.2404, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.7029, root_relative_squared_error: 1.4155, scimark_benchmark: 945.6434, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4158, f_measure: 0.3796, kappa: -0.2615, kb_relative_information_score: -4.2083, mean_absolute_error: 0.5451, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3775, predictive_accuracy: 0.3824, prior_entropy: 0.9911, recall: 0.3824, relative_absolute_error: 1.1047, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.6465, root_relative_squared_error: 1.302, scimark_benchmark: 941.7954, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3842, f_measure: 0.3529, kappa: -0.3123, kb_relative_information_score: -5.7098, mean_absolute_error: 0.5658, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3529, predictive_accuracy: 0.3529, prior_entropy: 0.9911, recall: 0.3529, relative_absolute_error: 1.1465, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.6525, root_relative_squared_error: 1.3141, scimark_benchmark: 923.7642, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3842, f_measure: 0.3529, kappa: -0.3123, kb_relative_information_score: -5.7098, mean_absolute_error: 0.5658, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3529, predictive_accuracy: 0.3529, prior_entropy: 0.9911, recall: 0.3529, relative_absolute_error: 1.1465, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.6525, root_relative_squared_error: 1.3141, scimark_benchmark: 894.7455, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3351, f_measure: 0.4055, kappa: -0.21, kb_relative_information_score: -5.6302, mean_absolute_error: 0.57, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.4019, predictive_accuracy: 0.4118, prior_entropy: 0.9911, recall: 0.4118, relative_absolute_error: 1.1551, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.7379, root_relative_squared_error: 1.4861, scimark_benchmark: 936.6206, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3228, f_measure: 0.4306, kappa: -0.1577, kb_relative_information_score: -5.2377, mean_absolute_error: 0.5672, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.4265, predictive_accuracy: 0.4412, prior_entropy: 0.9911, recall: 0.4412, relative_absolute_error: 1.1493, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.7232, root_relative_squared_error: 1.4565, scimark_benchmark: 936.7115, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3877, f_measure: 0.3364, kappa: -0.3173, kb_relative_information_score: -5.6362, mean_absolute_error: 0.567, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3131, predictive_accuracy: 0.3824, prior_entropy: 0.9911, recall: 0.3824, relative_absolute_error: 1.1491, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.7031, root_relative_squared_error: 1.4161, scimark_benchmark: 942.1229,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3561, f_measure: 0.3996, kappa: -0.1919, kb_relative_information_score: -2.7601, mean_absolute_error: 0.5296, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3897, predictive_accuracy: 0.4412, prior_entropy: 0.9911, recall: 0.4412, relative_absolute_error: 1.0733, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.6617, root_relative_squared_error: 1.3326, scimark_benchmark: 922.9039, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4123, f_measure: 0.429, kappa: -0.0421, kb_relative_information_score: -0.3468, mean_absolute_error: 0.4986, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.4535, predictive_accuracy: 0.5294, prior_entropy: 0.9911, recall: 0.5294, relative_absolute_error: 1.0103, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.6334, root_relative_squared_error: 1.2757, scimark_benchmark: 938.9865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3316, f_measure: 0.3706, kappa: -0.2796, kb_relative_information_score: -7.8347, mean_absolute_error: 0.6019, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3643, predictive_accuracy: 0.3824, prior_entropy: 0.9911, recall: 0.3824, relative_absolute_error: 1.2197, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.7558, root_relative_squared_error: 1.522, scimark_benchmark: 938.4285, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3526, f_measure: 0.3945, kappa: -0.2274, kb_relative_information_score: -6.2705, mean_absolute_error: 0.5801, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3876, predictive_accuracy: 0.4118, prior_entropy: 0.9911, recall: 0.4118, relative_absolute_error: 1.1755, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.7215, root_relative_squared_error: 1.453, scimark_benchmark: 924.6116,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3632, f_measure: 0.3796, kappa: -0.2615, kb_relative_information_score: -6.8796, mean_absolute_error: 0.5861, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3775, predictive_accuracy: 0.3824, prior_entropy: 0.9911, recall: 0.3824, relative_absolute_error: 1.1878, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.7004, root_relative_squared_error: 1.4106, scimark_benchmark: 945.6434, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3509, f_measure: 0.4055, kappa: -0.21, kb_relative_information_score: -6.5807, mean_absolute_error: 0.5798, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.4019, predictive_accuracy: 0.4118, prior_entropy: 0.9911, recall: 0.4118, relative_absolute_error: 1.175, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.663, root_relative_squared_error: 1.3352, scimark_benchmark: 947.9494,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3018, f_measure: 0.3796, kappa: -0.2615, kb_relative_information_score: -6.8888, mean_absolute_error: 0.5839, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3775, predictive_accuracy: 0.3824, prior_entropy: 0.9911, recall: 0.3824, relative_absolute_error: 1.1832, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.6483, root_relative_squared_error: 1.3057, scimark_benchmark: 929.566,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3895, f_measure: 0.4007, kb_relative_information_score: -0.2156, mean_absolute_error: 0.4955, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3123, predictive_accuracy: 0.5588, prior_entropy: 0.9911, recall: 0.5588, relative_absolute_error: 1.0042, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.4988, root_relative_squared_error: 1.0046, scimark_benchmark: 943.2817,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3877, build_cpu_time: 0.0453, build_memory: 187818370.1176, f_measure: 0.4138, kappa: -0.1765, kb_relative_information_score: -4.6338, mean_absolute_error: 0.5579, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.4187, predictive_accuracy: 0.4118, prior_entropy: 0.9911, recall: 0.4118, relative_absolute_error: 1.1307, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.7032, root_relative_squared_error: 1.4162, scimark_benchmark: 942.5053,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3491, build_cpu_time: 0.0053, build_memory: 1481381231.0588, f_measure: 0.356, kappa: -0.2639, kb_relative_information_score: -4.1323, mean_absolute_error: 0.543, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3321, predictive_accuracy: 0.4118, prior_entropy: 0.9911, recall: 0.4118, relative_absolute_error: 1.1005, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.5643, root_relative_squared_error: 1.1365, scimark_benchmark: 937.5625,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3491, build_cpu_time: 0.003, build_memory: 398980846.5882, f_measure: 0.356, kappa: -0.2639, kb_relative_information_score: -4.1323, mean_absolute_error: 0.543, mean_prior_absolute_error: 0.4935, number_of_instances: 34, precision: 0.3321, predictive_accuracy: 0.4118, prior_entropy: 0.9911, recall: 0.4118, relative_absolute_error: 1.1005, root_mean_prior_squared_error: 0.4965, root_mean_squared_error: 0.5643, root_relative_squared_error: 1.1365, scimark_benchmark: 913.3372,

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