Task
Supervised Classification on electricity

Supervised Classification on electricity

Task 146012 Supervised Classification electricity 25374 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1302.4669, usercpu_time_millis: 1.615, usercpu_time_millis_testing: 0.057, usercpu_time_millis_training: 1.558,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1281.6228, usercpu_time_millis: 1.327, usercpu_time_millis_testing: 0.038, usercpu_time_millis_training: 1.289,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1305.7694, usercpu_time_millis: 1.709, usercpu_time_millis_testing: 0.051, usercpu_time_millis_training: 1.658,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1302.0297, usercpu_time_millis: 1.88, usercpu_time_millis_testing: 0.059, usercpu_time_millis_training: 1.821,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1283.9621, usercpu_time_millis: 1.613, usercpu_time_millis_testing: 0.039, usercpu_time_millis_training: 1.574,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1300.12, usercpu_time_millis: 2.119, usercpu_time_millis_testing: 0.054, usercpu_time_millis_training: 2.065,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1290.4094, usercpu_time_millis: 2.056, usercpu_time_millis_testing: 0.08, usercpu_time_millis_training: 1.976,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1305.636, usercpu_time_millis: 1.655, usercpu_time_millis_testing: 0.057, usercpu_time_millis_training: 1.598,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1287.661, usercpu_time_millis: 2.215, usercpu_time_millis_testing: 0.057, usercpu_time_millis_training: 2.158,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1293.3818, usercpu_time_millis: 2.533, usercpu_time_millis_testing: 0.064, usercpu_time_millis_training: 2.469,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1287.4496, usercpu_time_millis: 1.892, usercpu_time_millis_testing: 0.07, usercpu_time_millis_training: 1.822,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1308.6829, usercpu_time_millis: 1.015, usercpu_time_millis_testing: 0.035, usercpu_time_millis_training: 0.98,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1308.5721, usercpu_time_millis: 1.135, usercpu_time_millis_testing: 0.036, usercpu_time_millis_training: 1.099,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1306.6642, usercpu_time_millis: 1.759, usercpu_time_millis_testing: 0.06, usercpu_time_millis_training: 1.699,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1297.5178, usercpu_time_millis: 1.986, usercpu_time_millis_testing: 0.052, usercpu_time_millis_training: 1.934,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1295.2665, usercpu_time_millis: 1.288, usercpu_time_millis_testing: 0.045, usercpu_time_millis_training: 1.243,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1306.385, usercpu_time_millis: 1.766, usercpu_time_millis_testing: 0.058, usercpu_time_millis_training: 1.708,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1307.0646, usercpu_time_millis: 1.094, usercpu_time_millis_testing: 0.051, usercpu_time_millis_training: 1.043,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1285.4172, usercpu_time_millis: 2.378, usercpu_time_millis_testing: 0.071, usercpu_time_millis_training: 2.307,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1295.3576, usercpu_time_millis: 1.428, usercpu_time_millis_testing: 0.055, usercpu_time_millis_training: 1.373,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1257.2477, usercpu_time_millis: 1.123, usercpu_time_millis_testing: 0.038, usercpu_time_millis_training: 1.085,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1301.8764, usercpu_time_millis: 0.651, usercpu_time_millis_testing: 0.047, usercpu_time_millis_training: 0.604,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1302.9004, usercpu_time_millis: 1.241, usercpu_time_millis_testing: 0.037, usercpu_time_millis_training: 1.204,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1287.1312, usercpu_time_millis: 1.526, usercpu_time_millis_testing: 0.053, usercpu_time_millis_training: 1.473,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1291.7719, usercpu_time_millis: 1.879, usercpu_time_millis_testing: 0.053, usercpu_time_millis_training: 1.826,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1279.8223, usercpu_time_millis: 1.999, usercpu_time_millis_testing: 0.08, usercpu_time_millis_training: 1.919,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1296.097, usercpu_time_millis: 2.095, usercpu_time_millis_testing: 0.099, usercpu_time_millis_training: 1.996,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1279.7587, usercpu_time_millis: 3.042, usercpu_time_millis_testing: 0.06, usercpu_time_millis_training: 2.982,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1295.1191, usercpu_time_millis: 1.78, usercpu_time_millis_testing: 0.053, usercpu_time_millis_training: 1.727,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1311.8054, usercpu_time_millis: 1.229, usercpu_time_millis_testing: 0.05, usercpu_time_millis_training: 1.179,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1285.4553, usercpu_time_millis: 1.091, usercpu_time_millis_testing: 0.042, usercpu_time_millis_training: 1.049,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1312.1452, usercpu_time_millis: 1.517, usercpu_time_millis_testing: 0.044, usercpu_time_millis_training: 1.473,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7283, f_measure: 0.7486, kappa: 0.484, kb_relative_information_score: 13195.7191, mean_absolute_error: 0.3659, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.7651, predictive_accuracy: 0.7574, prior_entropy: 0.9835, recall: 0.7574, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4277, root_relative_squared_error: 0.8653, scimark_benchmark: 1299.7306, usercpu_time_millis: 1.823, usercpu_time_millis_testing: 0.071, usercpu_time_millis_training: 1.752,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4999, f_measure: 0.4204, kb_relative_information_score: 0.0359, mean_absolute_error: 0.4886, mean_prior_absolute_error: 0.4886, number_of_instances: 45312, precision: 0.3311, predictive_accuracy: 0.5755, prior_entropy: 0.9835, recall: 0.5755, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4943, root_mean_squared_error: 0.4943, root_relative_squared_error: 1, scimark_benchmark: 1296.3927, usercpu_time_millis: 1.124, usercpu_time_millis_testing: 0.04, usercpu_time_millis_training: 1.084,
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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