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OpenML
Task
Supervised Classification on cmc

Supervised Classification on cmc

Task 23 Supervised Classification cmc 19083 runs submitted
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Visibility: Public
  • at2 basic OpenML-CC18 OpenML100 study_1 study_107 study_123 study_14 study_41 study_50 study_7 study_70 study_98 study_99 under100k under1m
Issue #Downvotes for this reason By


Metric:

19083 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6122, f_measure: 0.4622, kappa: 0.1617, kb_relative_information_score: 288.697, mean_absolute_error: 0.3808, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.4622, predictive_accuracy: 0.4671, prior_entropy: 1.5392, recall: 0.4671, relative_absolute_error: 0.8838, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4966, root_relative_squared_error: 1.0701, scimark_benchmark: 1363.454, usercpu_time_millis: 160, usercpu_time_millis_testing: 160,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5326, f_measure: 0.2729, kappa: 0.0119, kb_relative_information_score: 211.2502, mean_absolute_error: 0.395, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.4588, predictive_accuracy: 0.4304, prior_entropy: 1.5392, recall: 0.4304, relative_absolute_error: 0.9168, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4968, root_relative_squared_error: 1.0704, scimark_benchmark: 1363.434, usercpu_time_millis: 2420, usercpu_time_millis_testing: 710, usercpu_time_millis_training: 1710,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6375, f_measure: 0.4899, kappa: 0.2107, kb_relative_information_score: 324.9233, mean_absolute_error: 0.3773, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.4908, predictive_accuracy: 0.4895, prior_entropy: 1.5392, recall: 0.4895, relative_absolute_error: 0.8758, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.476, root_relative_squared_error: 1.0257, scimark_benchmark: 1321.527, usercpu_time_millis: 550, usercpu_time_millis_training: 550,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6968, f_measure: 0.5126, kappa: 0.2418, kb_relative_information_score: 264.2041, mean_absolute_error: 0.383, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.5125, predictive_accuracy: 0.518, prior_entropy: 1.5392, recall: 0.518, relative_absolute_error: 0.8889, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4383, root_relative_squared_error: 0.9445, scimark_benchmark: 1321.527, usercpu_time_millis: 330, usercpu_time_millis_training: 330,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5535, f_measure: 0.4263, kappa: 0.1081, kb_relative_information_score: 283.067, mean_absolute_error: 0.3711, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.4275, predictive_accuracy: 0.4433, prior_entropy: 1.5392, recall: 0.4433, relative_absolute_error: 0.8614, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.6092, root_relative_squared_error: 1.3126, scimark_benchmark: 1304.9611, usercpu_time_millis: 450, usercpu_time_millis_training: 450,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6972, f_measure: 0.5067, kappa: 0.2472, kb_relative_information_score: 354.3401, mean_absolute_error: 0.3605, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.5212, predictive_accuracy: 0.5017, prior_entropy: 1.5392, recall: 0.5017, relative_absolute_error: 0.8367, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4481, root_relative_squared_error: 0.9655, scimark_benchmark: 1073.494, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7026, f_measure: 0.5118, kappa: 0.2505, kb_relative_information_score: 364.8204, mean_absolute_error: 0.356, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.5201, predictive_accuracy: 0.5078, prior_entropy: 1.5392, recall: 0.5078, relative_absolute_error: 0.8263, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4467, root_relative_squared_error: 0.9626, scimark_benchmark: 1346.9602, usercpu_time_millis: 1070, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 1040,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6828, f_measure: 0.5058, kappa: 0.2327, kb_relative_information_score: 351.7225, mean_absolute_error: 0.3588, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.5048, predictive_accuracy: 0.5078, prior_entropy: 1.5392, recall: 0.5078, relative_absolute_error: 0.8327, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.458, root_relative_squared_error: 0.9868, scimark_benchmark: 1333.5799, usercpu_time_millis: 470, usercpu_time_millis_testing: 130, usercpu_time_millis_training: 340,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6094, f_measure: 0.4825, kappa: 0.1996, kb_relative_information_score: 388.8137, mean_absolute_error: 0.3441, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.4818, predictive_accuracy: 0.4834, prior_entropy: 1.5392, recall: 0.4834, relative_absolute_error: 0.7987, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.5749, root_relative_squared_error: 1.2386, scimark_benchmark: 1315.3881, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6899, f_measure: 0.5202, kappa: 0.2551, kb_relative_information_score: 338.9488, mean_absolute_error: 0.3611, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.5198, predictive_accuracy: 0.5214, prior_entropy: 1.5392, recall: 0.5214, relative_absolute_error: 0.8381, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4461, root_relative_squared_error: 0.9613, scimark_benchmark: 1280.6952,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7021, f_measure: 0.544, kappa: 0.2926, kb_relative_information_score: 318.8593, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.5479, predictive_accuracy: 0.5465, prior_entropy: 1.5392, recall: 0.5465, relative_absolute_error: 0.8493, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4326, root_relative_squared_error: 0.9321, scimark_benchmark: 1066.7184, usercpu_time_millis: 420, usercpu_time_millis_training: 420,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5794, f_measure: 0.4565, kappa: 0.158, kb_relative_information_score: 328.8763, mean_absolute_error: 0.3621, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.4561, predictive_accuracy: 0.4569, prior_entropy: 1.5392, recall: 0.4569, relative_absolute_error: 0.8404, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.6017, root_relative_squared_error: 1.2965, scimark_benchmark: 1325.2092, usercpu_time_millis: 480, usercpu_time_millis_testing: 250, usercpu_time_millis_training: 230,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5509, f_measure: 0.3783, kappa: 0.1053, kb_relative_information_score: 275.6811, mean_absolute_error: 0.3779, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.4053, predictive_accuracy: 0.4331, prior_entropy: 1.5392, recall: 0.4331, relative_absolute_error: 0.8772, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.6147, root_relative_squared_error: 1.3246, scimark_benchmark: 1384.4418, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6594, f_measure: 0.4991, kappa: 0.2243, kb_relative_information_score: 380.2551, mean_absolute_error: 0.3498, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.4986, predictive_accuracy: 0.4997, prior_entropy: 1.5392, recall: 0.4997, relative_absolute_error: 0.8119, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4913, root_relative_squared_error: 1.0587, scimark_benchmark: 1466.6185, usercpu_time_millis: 120, usercpu_time_millis_training: 120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.574, f_measure: 0.4239, kappa: 0.1456, kb_relative_information_score: 339.7215, mean_absolute_error: 0.3471, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.4177, predictive_accuracy: 0.4793, prior_entropy: 1.5392, recall: 0.4793, relative_absolute_error: 0.8057, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.5892, root_relative_squared_error: 1.2695, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6894, f_measure: 0.5117, kappa: 0.2446, kb_relative_information_score: 433.3281, mean_absolute_error: 0.3311, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.5104, predictive_accuracy: 0.5139, prior_entropy: 1.5392, recall: 0.5139, relative_absolute_error: 0.7685, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4966, root_relative_squared_error: 1.0701, scimark_benchmark: 945.6434, usercpu_time_millis: 78800, usercpu_time_millis_testing: 90, usercpu_time_millis_training: 78710,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6232, f_measure: 0.5129, kappa: 0.2442, kb_relative_information_score: 446.2038, mean_absolute_error: 0.3218, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.5141, predictive_accuracy: 0.5173, prior_entropy: 1.5392, recall: 0.5173, relative_absolute_error: 0.7469, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.5673, root_relative_squared_error: 1.2223, scimark_benchmark: 1028.5889, usercpu_time_millis: 90, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4975, f_measure: 0.2556, kb_relative_information_score: 0.1997, mean_absolute_error: 0.4308, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.1823, predictive_accuracy: 0.427, prior_entropy: 1.5392, recall: 0.427, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4641, root_relative_squared_error: 1, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6743, f_measure: 0.523, kappa: 0.2604, kb_relative_information_score: 379.3701, mean_absolute_error: 0.3506, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.5224, predictive_accuracy: 0.5241, prior_entropy: 1.5392, recall: 0.5241, relative_absolute_error: 0.8139, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4706, root_relative_squared_error: 1.014, scimark_benchmark: 977.6382, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.654, f_measure: 0.5225, kappa: 0.2726, kb_relative_information_score: 100.6955, mean_absolute_error: 0.4283, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.5372, predictive_accuracy: 0.518, prior_entropy: 1.5392, recall: 0.518, relative_absolute_error: 0.9941, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4587, root_relative_squared_error: 0.9884, scimark_benchmark: 945.6434, usercpu_time_millis: 80, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6336, f_measure: 0.5135, kappa: 0.2588, kb_relative_information_score: 45.0834, mean_absolute_error: 0.4395, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.5297, predictive_accuracy: 0.5085, prior_entropy: 1.5392, recall: 0.5085, relative_absolute_error: 1.0201, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4667, root_relative_squared_error: 1.0055, scimark_benchmark: 911.3823, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6276, f_measure: 0.5118, kappa: 0.2564, kb_relative_information_score: 39.419, mean_absolute_error: 0.4406, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.527, predictive_accuracy: 0.5071, prior_entropy: 1.5392, recall: 0.5071, relative_absolute_error: 1.0228, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4676, root_relative_squared_error: 1.0076, scimark_benchmark: 926.6717, usercpu_time_millis: 60, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6276, f_measure: 0.5118, kappa: 0.2564, kb_relative_information_score: 39.419, mean_absolute_error: 0.4406, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.527, predictive_accuracy: 0.5071, prior_entropy: 1.5392, recall: 0.5071, relative_absolute_error: 1.0228, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4676, root_relative_squared_error: 1.0076, scimark_benchmark: 939.7623, usercpu_time_millis: 80, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6276, f_measure: 0.5118, kappa: 0.2564, kb_relative_information_score: 39.419, mean_absolute_error: 0.4406, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.527, predictive_accuracy: 0.5071, prior_entropy: 1.5392, recall: 0.5071, relative_absolute_error: 1.0228, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4676, root_relative_squared_error: 1.0076, scimark_benchmark: 939.7623, usercpu_time_millis: 60, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5495, f_measure: 0.2556, kb_relative_information_score: 91.957, mean_absolute_error: 0.4091, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.1823, predictive_accuracy: 0.427, prior_entropy: 1.5392, recall: 0.427, relative_absolute_error: 0.9496, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4523, root_relative_squared_error: 0.9745, scimark_benchmark: 922.9039, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5495, f_measure: 0.2556, kb_relative_information_score: 91.957, mean_absolute_error: 0.4091, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.1823, predictive_accuracy: 0.427, prior_entropy: 1.5392, recall: 0.427, relative_absolute_error: 0.9496, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4523, root_relative_squared_error: 0.9745, scimark_benchmark: 938.4278,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5495, f_measure: 0.2556, kb_relative_information_score: 91.957, mean_absolute_error: 0.4091, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.1823, predictive_accuracy: 0.427, prior_entropy: 1.5392, recall: 0.427, relative_absolute_error: 0.9496, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4523, root_relative_squared_error: 0.9745, scimark_benchmark: 934.5243, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5495, f_measure: 0.2556, kb_relative_information_score: 91.957, mean_absolute_error: 0.4091, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.1823, predictive_accuracy: 0.427, prior_entropy: 1.5392, recall: 0.427, relative_absolute_error: 0.9496, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4523, root_relative_squared_error: 0.9745, scimark_benchmark: 939.7623,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5495, f_measure: 0.2556, kb_relative_information_score: 91.957, mean_absolute_error: 0.4091, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.1823, predictive_accuracy: 0.427, prior_entropy: 1.5392, recall: 0.427, relative_absolute_error: 0.9496, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4523, root_relative_squared_error: 0.9745, scimark_benchmark: 933.8635,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7333, f_measure: 0.5527, kappa: 0.3063, kb_relative_information_score: 371.7795, mean_absolute_error: 0.352, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.5545, predictive_accuracy: 0.5553, prior_entropy: 1.5392, recall: 0.5553, relative_absolute_error: 0.817, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4272, root_relative_squared_error: 0.9205, scimark_benchmark: 933.8635, usercpu_time_millis: 690, usercpu_time_millis_training: 690,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7355, f_measure: 0.549, kappa: 0.3014, kb_relative_information_score: 367.3738, mean_absolute_error: 0.3531, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.55, predictive_accuracy: 0.5526, prior_entropy: 1.5392, recall: 0.5526, relative_absolute_error: 0.8197, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4262, root_relative_squared_error: 0.9183, scimark_benchmark: 924.6116, usercpu_time_millis: 260, usercpu_time_millis_training: 260,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7366, f_measure: 0.5548, kappa: 0.3107, kb_relative_information_score: 361.0096, mean_absolute_error: 0.3551, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.5571, predictive_accuracy: 0.5587, prior_entropy: 1.5392, recall: 0.5587, relative_absolute_error: 0.8241, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4255, root_relative_squared_error: 0.9169, scimark_benchmark: 910.8389, usercpu_time_millis: 140, usercpu_time_millis_training: 140,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7397, f_measure: 0.553, kappa: 0.3079, kb_relative_information_score: 333.5794, mean_absolute_error: 0.3625, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.5541, predictive_accuracy: 0.5594, prior_entropy: 1.5392, recall: 0.5594, relative_absolute_error: 0.8414, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4243, root_relative_squared_error: 0.9142, scimark_benchmark: 938.9865, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6791, build_cpu_time: 0.2689, build_memory: 234536858.6558, f_measure: 0.5067, kappa: 0.2359, kb_relative_information_score: 398.2911, mean_absolute_error: 0.3426, mean_prior_absolute_error: 0.4308, number_of_instances: 1473, precision: 0.5053, predictive_accuracy: 0.5085, prior_entropy: 1.5392, recall: 0.5085, relative_absolute_error: 0.7952, root_mean_prior_squared_error: 0.4641, root_mean_squared_error: 0.4882, root_relative_squared_error: 1.0518, scimark_benchmark: 902.712,
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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

OpenML bootcamp

From your own software

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

OpenML APIs