Task
Supervised Classification on trains

Supervised Classification on trains

Task 51 Supervised Classification trains 693 runs submitted
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  • basic study_1 study_107 study_123 study_41 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.62, build_cpu_time: 0.0069, build_memory: 104707368, f_measure: 0.4949, kb_relative_information_score: 0.0813, mean_absolute_error: 0.4944, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.5, predictive_accuracy: 0.5, prior_entropy: 1, recall: 0.5, relative_absolute_error: 0.9889, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.6993, root_relative_squared_error: 1.3987, scimark_benchmark: 926.5157,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.56, build_cpu_time: 0.0183, build_memory: 338429937.6, f_measure: 0.4949, kb_relative_information_score: 0.3245, mean_absolute_error: 0.4793, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.5, predictive_accuracy: 0.5, prior_entropy: 1, recall: 0.5, relative_absolute_error: 0.9587, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5599, root_relative_squared_error: 1.1199, scimark_benchmark: 940.8364,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.72, build_cpu_time: 17.0164, build_memory: 174455720, f_measure: 0.6, kappa: 0.2, kb_relative_information_score: 1.8823, mean_absolute_error: 0.4122, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.6, predictive_accuracy: 0.6, prior_entropy: 1, recall: 0.6, relative_absolute_error: 0.8244, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4678, root_relative_squared_error: 0.9355, scimark_benchmark: 946.4687,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.84, build_cpu_time: 0.0094, build_memory: 790948151.2, f_measure: 0.899, kappa: 0.8, kb_relative_information_score: 3.1077, mean_absolute_error: 0.3667, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.9167, predictive_accuracy: 0.9, prior_entropy: 1, recall: 0.9, relative_absolute_error: 0.7333, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4334, root_relative_squared_error: 0.8669, scimark_benchmark: 905.0866,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, build_cpu_time: 0.1659, build_memory: 624354673.6, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 1.506, mean_absolute_error: 0.4369, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.8737, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4713, root_relative_squared_error: 0.9426, scimark_benchmark: 932.7461,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6, build_cpu_time: 0.0017, build_memory: 244634715.2, f_measure: 0.5833, kappa: 0.2, kb_relative_information_score: 0.9755, mean_absolute_error: 0.455, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.619, predictive_accuracy: 0.6, prior_entropy: 1, recall: 0.6, relative_absolute_error: 0.91, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5106, root_relative_squared_error: 1.0213, scimark_benchmark: 941.6532,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6, build_cpu_time: 0.0011, build_memory: 186921692, f_measure: 0.5833, kappa: 0.2, kb_relative_information_score: 0.9755, mean_absolute_error: 0.455, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.619, predictive_accuracy: 0.6, prior_entropy: 1, recall: 0.6, relative_absolute_error: 0.91, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5106, root_relative_squared_error: 1.0213, scimark_benchmark: 926.9727,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, build_cpu_time: 0.0027, build_memory: 1404944777.6, f_measure: 0.5833, kappa: 0.2, kb_relative_information_score: 1.3991, mean_absolute_error: 0.4375, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.619, predictive_accuracy: 0.6, prior_entropy: 1, recall: 0.6, relative_absolute_error: 0.875, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5029, root_relative_squared_error: 1.0059, scimark_benchmark: 785.9104,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, build_cpu_time: 0.003, build_memory: 701235491.2, f_measure: 0.5833, kappa: 0.2, kb_relative_information_score: 1.3991, mean_absolute_error: 0.4375, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.619, predictive_accuracy: 0.6, prior_entropy: 1, recall: 0.6, relative_absolute_error: 0.875, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5029, root_relative_squared_error: 1.0059, scimark_benchmark: 940.6012,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, build_cpu_time: 0.0025, build_memory: 1131395435.2, f_measure: 0.5833, kappa: 0.2, kb_relative_information_score: 1.3991, mean_absolute_error: 0.4375, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.619, predictive_accuracy: 0.6, prior_entropy: 1, recall: 0.6, relative_absolute_error: 0.875, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5029, root_relative_squared_error: 1.0059, scimark_benchmark: 937.52,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, build_cpu_time: 0.0018, build_memory: 307900397.6, f_measure: 0.5833, kappa: 0.2, kb_relative_information_score: 1.3991, mean_absolute_error: 0.4375, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.619, predictive_accuracy: 0.6, prior_entropy: 1, recall: 0.6, relative_absolute_error: 0.875, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5029, root_relative_squared_error: 1.0059, scimark_benchmark: 938.3567,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, build_cpu_time: 0.002, build_memory: 1745381976, f_measure: 0.5833, kappa: 0.2, kb_relative_information_score: 1.3991, mean_absolute_error: 0.4375, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.619, predictive_accuracy: 0.6, prior_entropy: 1, recall: 0.6, relative_absolute_error: 0.875, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5029, root_relative_squared_error: 1.0059, scimark_benchmark: 943.2191,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.72, build_cpu_time: 0.0266, build_memory: 178806208, f_measure: 0.6, kappa: 0.2, kb_relative_information_score: 2.3361, mean_absolute_error: 0.397, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.6, predictive_accuracy: 0.6, prior_entropy: 1, recall: 0.6, relative_absolute_error: 0.794, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4517, root_relative_squared_error: 0.9035, scimark_benchmark: 899.912,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.72, build_cpu_time: 0.022, build_memory: 280176294.4, f_measure: 0.6, kappa: 0.2, kb_relative_information_score: 2.3361, mean_absolute_error: 0.397, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.6, predictive_accuracy: 0.6, prior_entropy: 1, recall: 0.6, relative_absolute_error: 0.794, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4517, root_relative_squared_error: 0.9035, scimark_benchmark: 938.3567,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.72, build_cpu_time: 0.037, build_memory: 165895793.6, f_measure: 0.6, kappa: 0.2, kb_relative_information_score: 2.3361, mean_absolute_error: 0.397, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.6, predictive_accuracy: 0.6, prior_entropy: 1, recall: 0.6, relative_absolute_error: 0.794, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4517, root_relative_squared_error: 0.9035, scimark_benchmark: 932.7461,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, build_cpu_time: 0.0056, build_memory: 192587066.4, f_measure: 0.5833, kappa: 0.2, kb_relative_information_score: 1.3498, mean_absolute_error: 0.4375, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.619, predictive_accuracy: 0.6, prior_entropy: 1, recall: 0.6, relative_absolute_error: 0.875, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4969, root_relative_squared_error: 0.9937, scimark_benchmark: 899.912,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, build_cpu_time: 0.0037, build_memory: 1390575622.4, f_measure: 0.5833, kappa: 0.2, kb_relative_information_score: 1.3498, mean_absolute_error: 0.4375, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.619, predictive_accuracy: 0.6, prior_entropy: 1, recall: 0.6, relative_absolute_error: 0.875, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4969, root_relative_squared_error: 0.9937, scimark_benchmark: 942.4281,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.72, build_cpu_time: 0.0026, build_memory: 657613771.2, f_measure: 0.8, kappa: 0.6, kb_relative_information_score: 3.4475, mean_absolute_error: 0.3433, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.8, predictive_accuracy: 0.8, prior_entropy: 1, recall: 0.8, relative_absolute_error: 0.6867, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4478, root_relative_squared_error: 0.8957, scimark_benchmark: 920.6195,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8, build_cpu_time: 0.0003, build_memory: 16933453.6, f_measure: 0.899, kappa: 0.8, kb_relative_information_score: 6.3904, mean_absolute_error: 0.2, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.9167, predictive_accuracy: 0.9, prior_entropy: 1, recall: 0.9, relative_absolute_error: 0.4, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.3464, root_relative_squared_error: 0.6928, scimark_benchmark: 941.4253,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8, build_cpu_time: 0.0003, build_memory: 199393912, f_measure: 0.899, kappa: 0.8, kb_relative_information_score: 6.3904, mean_absolute_error: 0.2, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.9167, predictive_accuracy: 0.9, prior_entropy: 1, recall: 0.9, relative_absolute_error: 0.4, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.3464, root_relative_squared_error: 0.6928, scimark_benchmark: 917.9272,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8, build_cpu_time: 0.0001, build_memory: 176323308.8, f_measure: 0.899, kappa: 0.8, kb_relative_information_score: 6.3904, mean_absolute_error: 0.2, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.9167, predictive_accuracy: 0.9, prior_entropy: 1, recall: 0.9, relative_absolute_error: 0.4, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.3464, root_relative_squared_error: 0.6928, scimark_benchmark: 943.765,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8, build_cpu_time: 0.0003, build_memory: 20035460.8, f_measure: 0.899, kappa: 0.8, kb_relative_information_score: 6.3904, mean_absolute_error: 0.2, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.9167, predictive_accuracy: 0.9, prior_entropy: 1, recall: 0.9, relative_absolute_error: 0.4, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.3464, root_relative_squared_error: 0.6928, scimark_benchmark: 906.3114,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8, build_cpu_time: 0.0035, build_memory: 207894571.2, f_measure: 0.899, kappa: 0.8, kb_relative_information_score: 3.2685, mean_absolute_error: 0.3698, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.9167, predictive_accuracy: 0.9, prior_entropy: 1, recall: 0.9, relative_absolute_error: 0.7395, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4319, root_relative_squared_error: 0.8638, scimark_benchmark: 885.8472,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.52, build_cpu_time: 0.0018, build_memory: 880782176, f_measure: 0.4505, kb_relative_information_score: 0.1045, mean_absolute_error: 0.4947, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.5, predictive_accuracy: 0.5, prior_entropy: 1, recall: 0.5, relative_absolute_error: 0.9895, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.52, root_relative_squared_error: 1.04, scimark_benchmark: 919.2952,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.08, build_cpu_time: 0.0062, build_memory: 1790543116, f_measure: 0.1667, kappa: -0.6, kb_relative_information_score: -2.0783, mean_absolute_error: 0.5825, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.1429, predictive_accuracy: 0.2, prior_entropy: 1, recall: 0.2, relative_absolute_error: 1.1649, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5898, root_relative_squared_error: 1.1796, scimark_benchmark: 943.4766,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.56, f_measure: 0.4949, kb_relative_information_score: 0.7146, mean_absolute_error: 0.4656, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.5, predictive_accuracy: 0.5, prior_entropy: 1, recall: 0.5, relative_absolute_error: 0.9313, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4923, root_relative_squared_error: 0.9845, scimark_benchmark: 1322.7257, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 1342.2845,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.68, f_measure: 0.6, kappa: 0.2, kb_relative_information_score: 2.0312, mean_absolute_error: 0.3965, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.6, predictive_accuracy: 0.6, prior_entropy: 1, recall: 0.6, relative_absolute_error: 0.793, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4875, root_relative_squared_error: 0.9751,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8, f_measure: 0.899, kappa: 0.8, kb_relative_information_score: 6.3904, mean_absolute_error: 0.2, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.9167, predictive_accuracy: 0.9, prior_entropy: 1, recall: 0.9, relative_absolute_error: 0.4, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.3464, root_relative_squared_error: 0.6928,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8, f_measure: 0.899, kappa: 0.8, kb_relative_information_score: 6.3904, mean_absolute_error: 0.2, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.9167, predictive_accuracy: 0.9, prior_entropy: 1, recall: 0.9, relative_absolute_error: 0.4, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.3464, root_relative_squared_error: 0.6928, scimark_benchmark: 906.0979,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 941.3847,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 2.2401, mean_absolute_error: 0.3887, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.7773, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5538, root_relative_squared_error: 1.1076, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.84, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 4.6038, mean_absolute_error: 0.265, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.53, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4741, root_relative_squared_error: 0.9481,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.84, f_measure: 0.6, kappa: 0.2, kb_relative_information_score: 4.0413, mean_absolute_error: 0.2948, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.6, predictive_accuracy: 0.6, prior_entropy: 1, recall: 0.6, relative_absolute_error: 0.5897, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4349, root_relative_squared_error: 0.8698,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7, f_measure: 0.697, kappa: 0.4, kb_relative_information_score: 4, mean_absolute_error: 0.3, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.7083, predictive_accuracy: 0.7, prior_entropy: 1, recall: 0.7, relative_absolute_error: 0.6, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5477, root_relative_squared_error: 1.0954,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.08, f_measure: 0.1667, kappa: -0.6, kb_relative_information_score: -1.3593, mean_absolute_error: 0.5547, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.1429, predictive_accuracy: 0.2, prior_entropy: 1, recall: 0.2, relative_absolute_error: 1.1094, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.561, root_relative_squared_error: 1.1219, scimark_benchmark: 1356.9539,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.24, f_measure: 0.2857, kappa: -0.2, kb_relative_information_score: -1.3636, mean_absolute_error: 0.5578, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.2222, predictive_accuracy: 0.4, prior_entropy: 1, recall: 0.4, relative_absolute_error: 1.1156, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.593, root_relative_squared_error: 1.1859, scimark_benchmark: 1345.1228, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.12, f_measure: 0.2308, kappa: -0.4, kb_relative_information_score: -1.9911, mean_absolute_error: 0.5803, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.1875, predictive_accuracy: 0.3, prior_entropy: 1, recall: 0.3, relative_absolute_error: 1.1606, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5935, root_relative_squared_error: 1.1871, scimark_benchmark: 1327.4647,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.08, f_measure: 0.1667, kappa: -0.6, kb_relative_information_score: -1.9037, mean_absolute_error: 0.5762, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.1429, predictive_accuracy: 0.2, prior_entropy: 1, recall: 0.2, relative_absolute_error: 1.1524, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5858, root_relative_squared_error: 1.1715, scimark_benchmark: 1329.4192, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.72, f_measure: 0.8, kappa: 0.6, kb_relative_information_score: 3.4475, mean_absolute_error: 0.3433, mean_prior_absolute_error: 0.5, number_of_instances: 10, precision: 0.8, predictive_accuracy: 0.8, prior_entropy: 1, recall: 0.8, relative_absolute_error: 0.6867, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4478, root_relative_squared_error: 0.8957, scimark_benchmark: 1339.3974,

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