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OpenML
Task
Supervised Classification on kdd_ipums_la_97-small

Supervised Classification on kdd_ipums_la_97-small

Task 3856 Supervised Classification kdd_ipums_la_97-small 476 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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476 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9756, f_measure: 0.9497, kappa: 0.8935, kb_relative_information_score: 6028.6512, mean_absolute_error: 0.0664, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9532, predictive_accuracy: 0.9493, prior_entropy: 0.9504, recall: 0.9493, relative_absolute_error: 0.1425, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.2083, root_relative_squared_error: 0.4314, scimark_benchmark: 1363.454, usercpu_time_millis: 51370, usercpu_time_millis_testing: 51370,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9633, f_measure: 0.9647, kappa: 0.9244, kb_relative_information_score: 6470.3693, mean_absolute_error: 0.0353, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9648, predictive_accuracy: 0.9647, prior_entropy: 0.9504, recall: 0.9647, relative_absolute_error: 0.0758, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.188, root_relative_squared_error: 0.3894, scimark_benchmark: 1318.1432, usercpu_time_millis: 15280, usercpu_time_millis_testing: 90, usercpu_time_millis_training: 15190,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9829, f_measure: 0.9786, kappa: 0.9544, kb_relative_information_score: 6684.872, mean_absolute_error: 0.0215, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9797, predictive_accuracy: 0.9785, prior_entropy: 0.9504, recall: 0.9785, relative_absolute_error: 0.0462, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.1467, root_relative_squared_error: 0.3039, scimark_benchmark: 869.6028, usercpu_time_millis: 146170, usercpu_time_millis_testing: 27700, usercpu_time_millis_training: 118470,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9808, f_measure: 0.9777, kappa: 0.9525, kb_relative_information_score: 6671.6038, mean_absolute_error: 0.0224, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9784, predictive_accuracy: 0.9776, prior_entropy: 0.9504, recall: 0.9776, relative_absolute_error: 0.048, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.1496, root_relative_squared_error: 0.3098, scimark_benchmark: 1333.5799, usercpu_time_millis: 19280, usercpu_time_millis_testing: 80, usercpu_time_millis_training: 19200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9904, f_measure: 0.9785, kappa: 0.9541, kb_relative_information_score: 6416.3311, mean_absolute_error: 0.0451, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9794, predictive_accuracy: 0.9783, prior_entropy: 0.9504, recall: 0.9783, relative_absolute_error: 0.0968, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.1419, root_relative_squared_error: 0.294, scimark_benchmark: 1386.5717, usercpu_time_millis: 25060, usercpu_time_millis_testing: 130, usercpu_time_millis_training: 24930,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6455, f_measure: 0.6502, kappa: 0.2761, kb_relative_information_score: 1499.2136, mean_absolute_error: 0.3556, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.6679, predictive_accuracy: 0.6444, prior_entropy: 0.9504, recall: 0.6444, relative_absolute_error: 0.7631, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.5963, root_relative_squared_error: 1.2354, scimark_benchmark: 942.6843, usercpu_time_millis: 3620, usercpu_time_millis_testing: 90, usercpu_time_millis_training: 3530,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9457, f_measure: 0.8485, kappa: 0.6935, kb_relative_information_score: 3736.039, mean_absolute_error: 0.2243, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.885, predictive_accuracy: 0.8458, prior_entropy: 0.9504, recall: 0.8458, relative_absolute_error: 0.4813, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.32, root_relative_squared_error: 0.6629, scimark_benchmark: 916.5955, usercpu_time_millis: 1195640, usercpu_time_millis_testing: 220990, usercpu_time_millis_training: 974650,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5088, f_measure: 0.5054, kappa: 0.022, kb_relative_information_score: 1357.6861, mean_absolute_error: 0.3647, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.6547, predictive_accuracy: 0.6353, prior_entropy: 0.9504, recall: 0.6353, relative_absolute_error: 0.7827, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.6039, root_relative_squared_error: 1.2512, scimark_benchmark: 934.0566, usercpu_time_millis: 171040, usercpu_time_millis_testing: 28750, usercpu_time_millis_training: 142290,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9729, f_measure: 0.9259, kappa: 0.8423, kb_relative_information_score: 5864.4523, mean_absolute_error: 0.0743, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9279, predictive_accuracy: 0.9253, prior_entropy: 0.9504, recall: 0.9253, relative_absolute_error: 0.1595, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.2639, root_relative_squared_error: 0.5467, scimark_benchmark: 918.6491, usercpu_time_millis: 190, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.977, f_measure: 0.9429, kappa: 0.8787, kb_relative_information_score: 6074.7967, mean_absolute_error: 0.0619, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9455, predictive_accuracy: 0.9424, prior_entropy: 0.9504, recall: 0.9424, relative_absolute_error: 0.1328, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.2252, root_relative_squared_error: 0.4666, scimark_benchmark: 934.0566, usercpu_time_millis: 440, usercpu_time_millis_testing: 300, usercpu_time_millis_training: 140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9802, f_measure: 0.9614, kappa: 0.9182, kb_relative_information_score: 5453.1524, mean_absolute_error: 0.1182, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9645, predictive_accuracy: 0.9611, prior_entropy: 0.9504, recall: 0.9611, relative_absolute_error: 0.2537, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.2067, root_relative_squared_error: 0.4283, scimark_benchmark: 1336.2509, usercpu_time_millis: 3940, usercpu_time_millis_testing: 780, usercpu_time_millis_training: 3160,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9061, f_measure: 0.8967, kappa: 0.7786, kb_relative_information_score: 5296.3318, mean_absolute_error: 0.1139, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.8968, predictive_accuracy: 0.8966, prior_entropy: 0.9504, recall: 0.8966, relative_absolute_error: 0.2444, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3051, root_relative_squared_error: 0.6321, scimark_benchmark: 1319.9043, usercpu_time_millis: 70, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9666, f_measure: 0.9622, kappa: 0.9198, kb_relative_information_score: 6079.848, mean_absolute_error: 0.0691, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9653, predictive_accuracy: 0.9618, prior_entropy: 0.9504, recall: 0.9618, relative_absolute_error: 0.1484, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.1862, root_relative_squared_error: 0.3857, scimark_benchmark: 1316.0472, usercpu_time_millis: 290, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 280,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9683, f_measure: 0.9623, kappa: 0.9201, kb_relative_information_score: 3813.2773, mean_absolute_error: 0.2382, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9655, predictive_accuracy: 0.962, prior_entropy: 0.9504, recall: 0.962, relative_absolute_error: 0.5111, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.3006, root_relative_squared_error: 0.6227, scimark_benchmark: 1339.7143, usercpu_time_millis: 44140, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 44130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9745, f_measure: 0.9723, kappa: 0.9409, kb_relative_information_score: 6587.5718, mean_absolute_error: 0.0278, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9729, predictive_accuracy: 0.9722, prior_entropy: 0.9504, recall: 0.9722, relative_absolute_error: 0.0596, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.1667, root_relative_squared_error: 0.3453, scimark_benchmark: 1307.4861, usercpu_time_millis: 9030, usercpu_time_millis_testing: 3920, usercpu_time_millis_training: 5110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5241, f_measure: 0.5282, kappa: 0.0598, kb_relative_information_score: 1545.6524, mean_absolute_error: 0.3526, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.739, predictive_accuracy: 0.6474, prior_entropy: 0.9504, recall: 0.6474, relative_absolute_error: 0.7567, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.5938, root_relative_squared_error: 1.2302, scimark_benchmark: 1280.6952, usercpu_time_millis: 141950, usercpu_time_millis_testing: 27640, usercpu_time_millis_training: 114310,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9699, f_measure: 0.962, kappa: 0.9195, kb_relative_information_score: 6079.4338, mean_absolute_error: 0.0691, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9652, predictive_accuracy: 0.9617, prior_entropy: 0.9504, recall: 0.9617, relative_absolute_error: 0.1483, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.1865, root_relative_squared_error: 0.3864, scimark_benchmark: 1465.2979, usercpu_time_millis: 86900, usercpu_time_millis_testing: 240, usercpu_time_millis_training: 86660,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9786, f_measure: 0.9759, kappa: 0.9485, kb_relative_information_score: 6642.856, mean_absolute_error: 0.0242, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9765, predictive_accuracy: 0.9758, prior_entropy: 0.9504, recall: 0.9758, relative_absolute_error: 0.052, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.1556, root_relative_squared_error: 0.3224, scimark_benchmark: 1465.2979, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9802, f_measure: 0.9763, kappa: 0.9495, kb_relative_information_score: 6649.4901, mean_absolute_error: 0.0238, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9773, predictive_accuracy: 0.9762, prior_entropy: 0.9504, recall: 0.9762, relative_absolute_error: 0.0511, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.1542, root_relative_squared_error: 0.3196, scimark_benchmark: 1353.5686, usercpu_time_millis: 480, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 470,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4993, f_measure: 0.4875, kb_relative_information_score: -0.1389, mean_absolute_error: 0.466, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.3974, predictive_accuracy: 0.6304, prior_entropy: 0.9504, recall: 0.6304, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4827, root_relative_squared_error: 1, scimark_benchmark: 1330.0803, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9666, f_measure: 0.9623, kappa: 0.9201, kb_relative_information_score: 6082.1294, mean_absolute_error: 0.069, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9655, predictive_accuracy: 0.962, prior_entropy: 0.9504, recall: 0.962, relative_absolute_error: 0.1481, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.1858, root_relative_squared_error: 0.3849, scimark_benchmark: 1353.5686, usercpu_time_millis: 2350, usercpu_time_millis_training: 2350,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8041, f_measure: 0.7104, kappa: 0.4628, kb_relative_information_score: 2495.0466, mean_absolute_error: 0.2927, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.8251, predictive_accuracy: 0.7114, prior_entropy: 0.9504, recall: 0.7114, relative_absolute_error: 0.6281, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.5252, root_relative_squared_error: 1.0881, scimark_benchmark: 931.2336, usercpu_time_millis: 3790, usercpu_time_millis_testing: 1250, usercpu_time_millis_training: 2540,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7988, f_measure: 0.709, kappa: 0.4614, kb_relative_information_score: 1405.8138, mean_absolute_error: 0.3827, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.8259, predictive_accuracy: 0.7102, prior_entropy: 0.9504, recall: 0.7102, relative_absolute_error: 0.8214, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4514, root_relative_squared_error: 0.9352, scimark_benchmark: 941.7954, usercpu_time_millis: 2700, usercpu_time_millis_testing: 750, usercpu_time_millis_training: 1950,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7988, f_measure: 0.709, kappa: 0.4614, kb_relative_information_score: 1405.8138, mean_absolute_error: 0.3827, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.8259, predictive_accuracy: 0.7102, prior_entropy: 0.9504, recall: 0.7102, relative_absolute_error: 0.8214, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4514, root_relative_squared_error: 0.9352, scimark_benchmark: 923.7642, usercpu_time_millis: 2600, usercpu_time_millis_testing: 730, usercpu_time_millis_training: 1870,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7988, f_measure: 0.709, kappa: 0.4614, kb_relative_information_score: 1405.8138, mean_absolute_error: 0.3827, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.8259, predictive_accuracy: 0.7102, prior_entropy: 0.9504, recall: 0.7102, relative_absolute_error: 0.8214, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.4514, root_relative_squared_error: 0.9352, scimark_benchmark: 894.7455, usercpu_time_millis: 2610, usercpu_time_millis_testing: 740, usercpu_time_millis_training: 1870,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9923, f_measure: 0.9759, kappa: 0.9485, kb_relative_information_score: 6643.3001, mean_absolute_error: 0.0242, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9765, predictive_accuracy: 0.9758, prior_entropy: 0.9504, recall: 0.9758, relative_absolute_error: 0.0519, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.1549, root_relative_squared_error: 0.3209, scimark_benchmark: 936.7115, usercpu_time_millis: 10450, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 10400,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9926, f_measure: 0.9759, kappa: 0.9485, kb_relative_information_score: 6643.525, mean_absolute_error: 0.0242, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9765, predictive_accuracy: 0.9758, prior_entropy: 0.9504, recall: 0.9758, relative_absolute_error: 0.0518, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.1543, root_relative_squared_error: 0.3197, scimark_benchmark: 936.6206, usercpu_time_millis: 4770, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 4730,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9911, f_measure: 0.9759, kappa: 0.9485, kb_relative_information_score: 6642.9216, mean_absolute_error: 0.0242, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9765, predictive_accuracy: 0.9758, prior_entropy: 0.9504, recall: 0.9758, relative_absolute_error: 0.052, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.1554, root_relative_squared_error: 0.322, scimark_benchmark: 942.1229, usercpu_time_millis: 2240, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 2230,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9881, f_measure: 0.9759, kappa: 0.9485, kb_relative_information_score: 6642.9034, mean_absolute_error: 0.0242, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9765, predictive_accuracy: 0.9758, prior_entropy: 0.9504, recall: 0.9758, relative_absolute_error: 0.052, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.1554, root_relative_squared_error: 0.322, scimark_benchmark: 934.5243, usercpu_time_millis: 1140, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 1130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9828, f_measure: 0.9759, kappa: 0.9485, kb_relative_information_score: 6642.8659, mean_absolute_error: 0.0242, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9765, predictive_accuracy: 0.9758, prior_entropy: 0.9504, recall: 0.9758, relative_absolute_error: 0.052, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.1556, root_relative_squared_error: 0.3224, scimark_benchmark: 938.4285, usercpu_time_millis: 530, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 520,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9908, build_cpu_time: 17.4212, build_memory: 971855598.5844, f_measure: 0.9719, kappa: 0.9399, kb_relative_information_score: 6538.01, mean_absolute_error: 0.032, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9723, predictive_accuracy: 0.9718, prior_entropy: 0.9504, recall: 0.9718, relative_absolute_error: 0.0686, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.1557, root_relative_squared_error: 0.3225, scimark_benchmark: 919.5971,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9777, build_cpu_time: 265.1509, build_memory: 1596434550.4647, f_measure: 0.9524, kappa: 0.8983, kb_relative_information_score: 6194.345, mean_absolute_error: 0.0551, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9533, predictive_accuracy: 0.9521, prior_entropy: 0.9504, recall: 0.9521, relative_absolute_error: 0.1183, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.2022, root_relative_squared_error: 0.4189, scimark_benchmark: 916.8516,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9375, build_cpu_time: 39.918, build_memory: 433096029.3842, f_measure: 0.9376, kappa: 0.8667, kb_relative_information_score: 6045.4732, mean_absolute_error: 0.0628, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9384, predictive_accuracy: 0.9373, prior_entropy: 0.9504, recall: 0.9373, relative_absolute_error: 0.1347, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.2501, root_relative_squared_error: 0.5182, scimark_benchmark: 937.6343,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9375, build_cpu_time: 46.8919, build_memory: 495276184.8981, f_measure: 0.9376, kappa: 0.8667, kb_relative_information_score: 6045.4732, mean_absolute_error: 0.0628, mean_prior_absolute_error: 0.466, number_of_instances: 7019, precision: 0.9384, predictive_accuracy: 0.9373, prior_entropy: 0.9504, recall: 0.9373, relative_absolute_error: 0.1347, root_mean_prior_squared_error: 0.4827, root_mean_squared_error: 0.2501, root_relative_squared_error: 0.5182, scimark_benchmark: 945.0554,

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

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