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Severity: Warning

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Backtrace:

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Function: fopen

File: /var/www/openml/openml_OS/core/MY_Database_Read_Model.php
Line: 30
Function: sql

File: /var/www/openml/openml_OS/views/pages/frontend/t/pre.php
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Function: query

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File: /var/www/openml/index.php
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Function: require_once

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Severity: Warning

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Backtrace:

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Function: fopen

File: /var/www/openml/openml_OS/core/MY_Database_Read_Model.php
Line: 30
Function: sql

File: /var/www/openml/openml_OS/views/pages/frontend/t/pre.php
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Function: query

File: /var/www/openml/openml_OS/helpers/cms_helper.php
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Function: view

File: /var/www/openml/openml_OS/controllers/Frontend.php
Line: 85
Function: loadpage

File: /var/www/openml/index.php
Line: 337
Function: require_once

OpenML
Task
Supervised Classification on haberman

Supervised Classification on haberman

Task 1806 Supervised Classification haberman 359 runs submitted
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359 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5858, f_measure: 0.6589, kappa: 0.0841, kb_relative_information_score: 20.3761, mean_absolute_error: 0.3463, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6459, predictive_accuracy: 0.6824, prior_entropy: 0.836, recall: 0.6824, relative_absolute_error: 0.8879, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4847, root_relative_squared_error: 1.0987, scimark_benchmark: 1363.454, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.516, f_measure: 0.1875, kappa: 0.0175, kb_relative_information_score: -1497.7664, mean_absolute_error: 0.7013, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.7126, predictive_accuracy: 0.2987, prior_entropy: 0.836, recall: 0.2987, relative_absolute_error: 1.7983, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.8374, root_relative_squared_error: 1.8982, scimark_benchmark: 1318.1432, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6231, kb_relative_information_score: 384.6343, mean_absolute_error: 0.2647, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.5407, predictive_accuracy: 0.7353, prior_entropy: 0.836, recall: 0.7353, relative_absolute_error: 0.6787, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5145, root_relative_squared_error: 1.1662, scimark_benchmark: 938.343, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5181, f_measure: 0.6483, kappa: 0.0502, kb_relative_information_score: 378.9984, mean_absolute_error: 0.266, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6731, predictive_accuracy: 0.734, prior_entropy: 0.836, recall: 0.734, relative_absolute_error: 0.6821, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5158, root_relative_squared_error: 1.1691, scimark_benchmark: 939.449, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6032, f_measure: 0.6763, kappa: 0.1168, kb_relative_information_score: -112.7541, mean_absolute_error: 0.3908, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6838, predictive_accuracy: 0.7333, prior_entropy: 0.836, recall: 0.7333, relative_absolute_error: 1.002, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4504, root_relative_squared_error: 1.021, scimark_benchmark: 1318.1432, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5405, f_measure: 0.6099, kappa: 0.0716, kb_relative_information_score: -235.318, mean_absolute_error: 0.4085, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6404, predictive_accuracy: 0.5915, prior_entropy: 0.836, recall: 0.5915, relative_absolute_error: 1.0474, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.6391, root_relative_squared_error: 1.4487, scimark_benchmark: 939.449, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6375, f_measure: 0.702, kappa: 0.1889, kb_relative_information_score: 97.1643, mean_absolute_error: 0.3487, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.7014, predictive_accuracy: 0.7379, prior_entropy: 0.836, recall: 0.7379, relative_absolute_error: 0.894, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4378, root_relative_squared_error: 0.9922, scimark_benchmark: 1325.2092, usercpu_time_millis: 380, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 370,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5781, f_measure: 0.7065, kappa: 0.1988, kb_relative_information_score: 469.1733, mean_absolute_error: 0.2451, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.7271, predictive_accuracy: 0.7549, prior_entropy: 0.836, recall: 0.7549, relative_absolute_error: 0.6285, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4951, root_relative_squared_error: 1.1222, scimark_benchmark: 1073.494, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6053, f_measure: 0.6819, kappa: 0.1323, kb_relative_information_score: 12.3249, mean_absolute_error: 0.3663, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6796, predictive_accuracy: 0.7268, prior_entropy: 0.836, recall: 0.7268, relative_absolute_error: 0.9393, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4428, root_relative_squared_error: 1.0037, scimark_benchmark: 1337.7959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.605, f_measure: 0.6849, kappa: 0.1454, kb_relative_information_score: 43.2432, mean_absolute_error: 0.3562, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6765, predictive_accuracy: 0.717, prior_entropy: 0.836, recall: 0.717, relative_absolute_error: 0.9134, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4529, root_relative_squared_error: 1.0265, scimark_benchmark: 1066.7184, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6275, f_measure: 0.6692, kappa: 0.1249, kb_relative_information_score: 48.4219, mean_absolute_error: 0.3457, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6605, predictive_accuracy: 0.6817, prior_entropy: 0.836, recall: 0.6817, relative_absolute_error: 0.8865, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4707, root_relative_squared_error: 1.067, scimark_benchmark: 1301.9956, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5549, f_measure: 0.6572, kappa: 0.117, kb_relative_information_score: 35.0258, mean_absolute_error: 0.3452, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6563, predictive_accuracy: 0.6582, prior_entropy: 0.836, recall: 0.6582, relative_absolute_error: 0.8851, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5854, root_relative_squared_error: 1.3268, scimark_benchmark: 1321.527,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5516, f_measure: 0.6571, kappa: 0.0682, kb_relative_information_score: 30.4431, mean_absolute_error: 0.3744, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6689, predictive_accuracy: 0.7307, prior_entropy: 0.836, recall: 0.7307, relative_absolute_error: 0.96, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4488, root_relative_squared_error: 1.0172, scimark_benchmark: 1319.6463,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5266, f_measure: 0.6469, kappa: 0.0446, kb_relative_information_score: 11.9222, mean_absolute_error: 0.3841, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6596, predictive_accuracy: 0.7301, prior_entropy: 0.836, recall: 0.7301, relative_absolute_error: 0.9849, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4439, root_relative_squared_error: 1.0061, scimark_benchmark: 1321.6263, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5483, f_measure: 0.6424, kappa: 0.0942, kb_relative_information_score: -35.2425, mean_absolute_error: 0.3621, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6475, predictive_accuracy: 0.6379, prior_entropy: 0.836, recall: 0.6379, relative_absolute_error: 0.9285, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.6017, root_relative_squared_error: 1.3639, scimark_benchmark: 1372.2145,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.566, f_measure: 0.4753, kappa: 0.0875, kb_relative_information_score: -784.8212, mean_absolute_error: 0.5359, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6808, predictive_accuracy: 0.4641, prior_entropy: 0.836, recall: 0.4641, relative_absolute_error: 1.3743, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.7321, root_relative_squared_error: 1.6594, scimark_benchmark: 1368.9272, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5673, f_measure: 0.6805, kappa: 0.1414, kb_relative_information_score: 41.9042, mean_absolute_error: 0.353, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.67, predictive_accuracy: 0.7033, prior_entropy: 0.836, recall: 0.7033, relative_absolute_error: 0.9053, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4897, root_relative_squared_error: 1.11, scimark_benchmark: 1341.2341,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5613, f_measure: 0.6871, kappa: 0.1481, kb_relative_information_score: 342.3648, mean_absolute_error: 0.2745, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6824, predictive_accuracy: 0.7255, prior_entropy: 0.836, recall: 0.7255, relative_absolute_error: 0.7039, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5239, root_relative_squared_error: 1.1876, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5535, f_measure: 0.6809, kappa: 0.1305, kb_relative_information_score: 328.275, mean_absolute_error: 0.2778, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6755, predictive_accuracy: 0.7222, prior_entropy: 0.836, recall: 0.7222, relative_absolute_error: 0.7123, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.527, root_relative_squared_error: 1.1946, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4958, f_measure: 0.6231, kb_relative_information_score: -9.6697, mean_absolute_error: 0.3907, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.5407, predictive_accuracy: 0.7353, prior_entropy: 0.836, recall: 0.7353, relative_absolute_error: 1.0019, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4412, root_relative_squared_error: 1.0001, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5958, f_measure: 0.6841, kappa: 0.1385, kb_relative_information_score: 50.9775, mean_absolute_error: 0.3712, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6817, predictive_accuracy: 0.7275, prior_entropy: 0.836, recall: 0.7275, relative_absolute_error: 0.9518, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4381, root_relative_squared_error: 0.9931, scimark_benchmark: 1066.833,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5855, build_cpu_time: 0.1165, build_memory: 306225149.6, f_measure: 0.6881, kappa: 0.1488, kb_relative_information_score: 50.9192, mean_absolute_error: 0.3571, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6911, predictive_accuracy: 0.7346, prior_entropy: 0.836, recall: 0.7346, relative_absolute_error: 0.9155, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4491, root_relative_squared_error: 1.018, scimark_benchmark: 924.2934,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5855, build_cpu_time: 0.1095, build_memory: 847269148, f_measure: 0.6881, kappa: 0.1488, kb_relative_information_score: 50.9192, mean_absolute_error: 0.3571, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6911, predictive_accuracy: 0.7346, prior_entropy: 0.836, recall: 0.7346, relative_absolute_error: 0.9155, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4491, root_relative_squared_error: 1.018, scimark_benchmark: 895.3841,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5858, build_cpu_time: 0.0733, build_memory: 971459831.2, f_measure: 0.6881, kappa: 0.1488, kb_relative_information_score: 50.3827, mean_absolute_error: 0.3571, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6911, predictive_accuracy: 0.7346, prior_entropy: 0.836, recall: 0.7346, relative_absolute_error: 0.9158, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4491, root_relative_squared_error: 1.018, scimark_benchmark: 938.8409,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5849, build_cpu_time: 0.0659, build_memory: 832291046.4, f_measure: 0.6881, kappa: 0.1488, kb_relative_information_score: 46.2287, mean_absolute_error: 0.3579, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6911, predictive_accuracy: 0.7346, prior_entropy: 0.836, recall: 0.7346, relative_absolute_error: 0.9178, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4495, root_relative_squared_error: 1.0189, scimark_benchmark: 932.9956,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5837, build_cpu_time: 0.0523, build_memory: 862930305.6, f_measure: 0.685, kappa: 0.1405, kb_relative_information_score: 42.6898, mean_absolute_error: 0.3592, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6866, predictive_accuracy: 0.732, prior_entropy: 0.836, recall: 0.732, relative_absolute_error: 0.921, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4491, root_relative_squared_error: 1.018, scimark_benchmark: 940.572,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6195, build_cpu_time: 0.0034, build_memory: 641617009.6, f_measure: 0.6878, kappa: 0.1529, kb_relative_information_score: 85.6412, mean_absolute_error: 0.3416, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6803, predictive_accuracy: 0.7203, prior_entropy: 0.836, recall: 0.7203, relative_absolute_error: 0.8759, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4565, root_relative_squared_error: 1.0347, scimark_benchmark: 925.181,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6151, build_cpu_time: 0.005, build_memory: 927331178.4, f_measure: 0.6849, kappa: 0.145, kb_relative_information_score: 75.816, mean_absolute_error: 0.3432, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6767, predictive_accuracy: 0.7176, prior_entropy: 0.836, recall: 0.7176, relative_absolute_error: 0.8799, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4595, root_relative_squared_error: 1.0416, scimark_benchmark: 926.4124,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6151, build_cpu_time: 0.0044, build_memory: 505643380, f_measure: 0.6849, kappa: 0.145, kb_relative_information_score: 75.816, mean_absolute_error: 0.3432, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6767, predictive_accuracy: 0.7176, prior_entropy: 0.836, recall: 0.7176, relative_absolute_error: 0.8799, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4595, root_relative_squared_error: 1.0416, scimark_benchmark: 932.9956,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6151, build_cpu_time: 0.0051, build_memory: 1373027016, f_measure: 0.6849, kappa: 0.145, kb_relative_information_score: 75.816, mean_absolute_error: 0.3432, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6767, predictive_accuracy: 0.7176, prior_entropy: 0.836, recall: 0.7176, relative_absolute_error: 0.8799, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4595, root_relative_squared_error: 1.0416, scimark_benchmark: 927.1482,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6151, build_cpu_time: 0.0078, build_memory: 70433102.4, f_measure: 0.6849, kappa: 0.145, kb_relative_information_score: 75.816, mean_absolute_error: 0.3432, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6767, predictive_accuracy: 0.7176, prior_entropy: 0.836, recall: 0.7176, relative_absolute_error: 0.8799, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.4595, root_relative_squared_error: 1.0416, scimark_benchmark: 935.8685,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5946, build_cpu_time: 0.0537, build_memory: 106056827.2, f_measure: 0.6637, kappa: 0.1245, kb_relative_information_score: 99.1336, mean_absolute_error: 0.3306, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6594, predictive_accuracy: 0.6686, prior_entropy: 0.836, recall: 0.6686, relative_absolute_error: 0.8478, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5665, root_relative_squared_error: 1.2841, scimark_benchmark: 907.1899,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5928, build_cpu_time: 0.0447, build_memory: 1704981790.4, f_measure: 0.664, kappa: 0.126, kb_relative_information_score: 96.8249, mean_absolute_error: 0.3307, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6599, predictive_accuracy: 0.6686, prior_entropy: 0.836, recall: 0.6686, relative_absolute_error: 0.8481, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5658, root_relative_squared_error: 1.2826, scimark_benchmark: 934.6076,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5937, build_cpu_time: 0.0142, build_memory: 3039653856, f_measure: 0.6621, kappa: 0.1215, kb_relative_information_score: 93.0905, mean_absolute_error: 0.3315, mean_prior_absolute_error: 0.39, number_of_instances: 1530, precision: 0.6582, predictive_accuracy: 0.6667, prior_entropy: 0.836, recall: 0.6667, relative_absolute_error: 0.85, root_mean_prior_squared_error: 0.4412, root_mean_squared_error: 0.5663, root_relative_squared_error: 1.2836, scimark_benchmark: 946.9091,
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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

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