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Line: 30
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File: /var/www/openml/index.php
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A PHP Error was encountered

Severity: Warning

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Backtrace:

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Line: 37
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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Function: loadpage

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
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Function: loadpage

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

OpenML
Task
Supervised Classification on monks-problems-2

Supervised Classification on monks-problems-2

Task 3054 Supervised Classification monks-problems-2 352 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5593, f_measure: 0.4847, kappa: -0.1076, kb_relative_information_score: 5.845, mean_absolute_error: 0.4225, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.4615, predictive_accuracy: 0.5505, prior_entropy: 0.9279, recall: 0.5505, relative_absolute_error: 0.9208, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.4943, root_relative_squared_error: 1.0231, scimark_benchmark: 1335.643, usercpu_time_millis: 20, usercpu_time_millis_testing: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.509, f_measure: 0.5513, kappa: 0.0191, kb_relative_information_score: 6.2031, mean_absolute_error: 0.4293, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.5439, predictive_accuracy: 0.5707, prior_entropy: 0.9279, recall: 0.5707, relative_absolute_error: 0.9356, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.6552, root_relative_squared_error: 1.3562, scimark_benchmark: 889.3151,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4886, kb_relative_information_score: 33.9964, mean_absolute_error: 0.3687, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.3986, predictive_accuracy: 0.6313, prior_entropy: 0.9279, recall: 0.6313, relative_absolute_error: 0.8035, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.6072, root_relative_squared_error: 1.2568, scimark_benchmark: 930.5999, usercpu_time_millis: 160, usercpu_time_millis_training: 160,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4886, kb_relative_information_score: 33.9964, mean_absolute_error: 0.3687, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.3986, predictive_accuracy: 0.6313, prior_entropy: 0.9279, recall: 0.6313, relative_absolute_error: 0.8035, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.6072, root_relative_squared_error: 1.2568, scimark_benchmark: 885.0921, usercpu_time_millis: 260, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4886, kb_relative_information_score: 33.9964, mean_absolute_error: 0.3687, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.3986, predictive_accuracy: 0.6313, prior_entropy: 0.9279, recall: 0.6313, relative_absolute_error: 0.8035, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.6072, root_relative_squared_error: 1.2568, scimark_benchmark: 1369.9744, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4886, kb_relative_information_score: -30.4026, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.3986, predictive_accuracy: 0.6313, prior_entropy: 0.9279, recall: 0.6313, relative_absolute_error: 1.0897, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.5, root_relative_squared_error: 1.0349, scimark_benchmark: 942.9518, usercpu_time_millis: 90, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.476, f_measure: 0.474, kappa: -0.0593, kb_relative_information_score: 20.0997, mean_absolute_error: 0.399, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.3913, predictive_accuracy: 0.601, prior_entropy: 0.9279, recall: 0.601, relative_absolute_error: 0.8696, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.6317, root_relative_squared_error: 1.3075, scimark_benchmark: 1304.9611,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8014, f_measure: 0.6543, kappa: 0.2557, kb_relative_information_score: 41.1949, mean_absolute_error: 0.3701, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.704, predictive_accuracy: 0.697, prior_entropy: 0.9279, recall: 0.697, relative_absolute_error: 0.8067, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.4233, root_relative_squared_error: 0.8762, scimark_benchmark: 894.7222, usercpu_time_millis: 3270, usercpu_time_millis_testing: 90, usercpu_time_millis_training: 3180,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7327, f_measure: 0.6076, kappa: 0.165, kb_relative_information_score: 23.5201, mean_absolute_error: 0.4071, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.6625, predictive_accuracy: 0.6667, prior_entropy: 0.9279, recall: 0.6667, relative_absolute_error: 0.8871, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.4487, root_relative_squared_error: 0.9288, scimark_benchmark: 1355.9413,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4886, kb_relative_information_score: 33.9964, mean_absolute_error: 0.3687, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.3986, predictive_accuracy: 0.6313, prior_entropy: 0.9279, recall: 0.6313, relative_absolute_error: 0.8035, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.6072, root_relative_squared_error: 1.2568, scimark_benchmark: 1310.3951, usercpu_time_millis: 110, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5684, f_measure: 0.474, kappa: -0.0593, kb_relative_information_score: 1.5874, mean_absolute_error: 0.4477, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.3913, predictive_accuracy: 0.601, prior_entropy: 0.9279, recall: 0.601, relative_absolute_error: 0.9756, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.485, root_relative_squared_error: 1.0039, scimark_benchmark: 1368.9272, usercpu_time_millis: 170, usercpu_time_millis_training: 170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7231, f_measure: 0.6224, kappa: 0.1775, kb_relative_information_score: 34.0887, mean_absolute_error: 0.3693, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.6189, predictive_accuracy: 0.6313, prior_entropy: 0.9279, recall: 0.6313, relative_absolute_error: 0.8047, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.4576, root_relative_squared_error: 0.9472, scimark_benchmark: 1315.3881, usercpu_time_millis: 60, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6653, f_measure: 0.6932, kappa: 0.3438, kb_relative_information_score: 54.4305, mean_absolute_error: 0.327, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.6947, predictive_accuracy: 0.6919, prior_entropy: 0.9279, recall: 0.6919, relative_absolute_error: 0.7127, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.5545, root_relative_squared_error: 1.1477, scimark_benchmark: 1325.942,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5346, f_measure: 0.5027, kappa: -0.0182, kb_relative_information_score: 4.3782, mean_absolute_error: 0.4381, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.5069, predictive_accuracy: 0.6111, prior_entropy: 0.9279, recall: 0.6111, relative_absolute_error: 0.9549, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.4982, root_relative_squared_error: 1.0313, scimark_benchmark: 1335.4072, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9086, f_measure: 0.7953, kappa: 0.5559, kb_relative_information_score: 111.8388, mean_absolute_error: 0.1994, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.7953, predictive_accuracy: 0.798, prior_entropy: 0.9279, recall: 0.798, relative_absolute_error: 0.4345, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.372, root_relative_squared_error: 0.7701, scimark_benchmark: 1313.5726, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6917, f_measure: 0.719, kappa: 0.3911, kb_relative_information_score: 75.6865, mean_absolute_error: 0.2778, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.7177, predictive_accuracy: 0.7222, prior_entropy: 0.9279, recall: 0.7222, relative_absolute_error: 0.6054, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.527, root_relative_squared_error: 1.0909, scimark_benchmark: 1306.6379, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5027, f_measure: 0.544, kappa: 0.006, kb_relative_information_score: 10.8353, mean_absolute_error: 0.4192, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.5378, predictive_accuracy: 0.5808, prior_entropy: 0.9279, recall: 0.5808, relative_absolute_error: 0.9136, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.6475, root_relative_squared_error: 1.3402, scimark_benchmark: 1466.6185,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8866, f_measure: 0.8129, kappa: 0.5974, kb_relative_information_score: 108.1944, mean_absolute_error: 0.2122, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.8126, predictive_accuracy: 0.8131, prior_entropy: 0.9279, recall: 0.8131, relative_absolute_error: 0.4625, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.3755, root_relative_squared_error: 0.7773, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6655, f_measure: 0.7088, kappa: 0.3653, kb_relative_information_score: 80.3188, mean_absolute_error: 0.2677, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.736, predictive_accuracy: 0.7323, prior_entropy: 0.9279, recall: 0.7323, relative_absolute_error: 0.5834, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.5174, root_relative_squared_error: 1.0709, scimark_benchmark: 1466.6185, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4886, kb_relative_information_score: 33.9964, mean_absolute_error: 0.3687, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.3986, predictive_accuracy: 0.6313, prior_entropy: 0.9279, recall: 0.6313, relative_absolute_error: 0.8035, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.6072, root_relative_squared_error: 1.2568, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4886, kb_relative_information_score: 33.9964, mean_absolute_error: 0.3687, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.3986, predictive_accuracy: 0.6313, prior_entropy: 0.9279, recall: 0.6313, relative_absolute_error: 0.8035, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.6072, root_relative_squared_error: 1.2568, scimark_benchmark: 1380.2233,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4886, kb_relative_information_score: 1.5147, mean_absolute_error: 0.4556, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.3986, predictive_accuracy: 0.6313, prior_entropy: 0.9279, recall: 0.6313, relative_absolute_error: 0.9929, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.4839, root_relative_squared_error: 1.0017, scimark_benchmark: 1503.3362,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4886, kb_relative_information_score: 1.616, mean_absolute_error: 0.4554, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.3986, predictive_accuracy: 0.6313, prior_entropy: 0.9279, recall: 0.6313, relative_absolute_error: 0.9924, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.484, root_relative_squared_error: 1.0018, scimark_benchmark: 1466.6185,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7247, f_measure: 0.6494, kappa: 0.2408, kb_relative_information_score: 29.329, mean_absolute_error: 0.3923, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.682, predictive_accuracy: 0.6869, prior_entropy: 0.9279, recall: 0.6869, relative_absolute_error: 0.8549, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.449, root_relative_squared_error: 0.9293, scimark_benchmark: 942.4414, usercpu_time_millis: 310, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 300,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7247, build_cpu_time: 0.248, build_memory: 384299896, f_measure: 0.6494, kappa: 0.2408, kb_relative_information_score: 29.329, mean_absolute_error: 0.3923, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.682, predictive_accuracy: 0.6869, prior_entropy: 0.9279, recall: 0.6869, relative_absolute_error: 0.8549, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.449, root_relative_squared_error: 0.9293, scimark_benchmark: 874.2668,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7247, build_cpu_time: 0.263, build_memory: 57395480, f_measure: 0.6494, kappa: 0.2408, kb_relative_information_score: 29.329, mean_absolute_error: 0.3923, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.682, predictive_accuracy: 0.6869, prior_entropy: 0.9279, recall: 0.6869, relative_absolute_error: 0.8549, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.449, root_relative_squared_error: 0.9293, scimark_benchmark: 937.3768,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7247, build_cpu_time: 0.223, build_memory: 890423872, f_measure: 0.6494, kappa: 0.2408, kb_relative_information_score: 29.329, mean_absolute_error: 0.3923, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.682, predictive_accuracy: 0.6869, prior_entropy: 0.9279, recall: 0.6869, relative_absolute_error: 0.8549, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.449, root_relative_squared_error: 0.9293, scimark_benchmark: 940.159,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6155, build_cpu_time: 0.012, build_memory: 407226216, f_measure: 0.6094, kappa: 0.1513, kb_relative_information_score: 17.0843, mean_absolute_error: 0.411, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.6058, predictive_accuracy: 0.6162, prior_entropy: 0.9279, recall: 0.6162, relative_absolute_error: 0.8956, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.5405, root_relative_squared_error: 1.1187, scimark_benchmark: 943.1873,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6706, build_cpu_time: 0.037, build_memory: 1070974072, f_measure: 0.6491, kappa: 0.2361, kb_relative_information_score: 35.2894, mean_absolute_error: 0.3743, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.6464, predictive_accuracy: 0.6566, prior_entropy: 0.9279, recall: 0.6566, relative_absolute_error: 0.8158, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.5232, root_relative_squared_error: 1.083, scimark_benchmark: 947.2691,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5722, build_cpu_time: 0.01, build_memory: 716256304, f_measure: 0.4664, kappa: -0.0881, kb_relative_information_score: 2.2604, mean_absolute_error: 0.4463, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.3875, predictive_accuracy: 0.5859, prior_entropy: 0.9279, recall: 0.5859, relative_absolute_error: 0.9727, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.4852, root_relative_squared_error: 1.0043, scimark_benchmark: 947.116,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6389, build_cpu_time: 0.014, build_memory: 1024807328, f_measure: 0.5671, kappa: 0.083, kb_relative_information_score: 13.5925, mean_absolute_error: 0.4251, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.6033, predictive_accuracy: 0.6364, prior_entropy: 0.9279, recall: 0.6364, relative_absolute_error: 0.9265, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.4754, root_relative_squared_error: 0.9841, scimark_benchmark: 933.4176,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, build_memory: 534430424, f_measure: 0.4886, kb_relative_information_score: 1.5147, mean_absolute_error: 0.4556, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.3986, predictive_accuracy: 0.6313, prior_entropy: 0.9279, recall: 0.6313, relative_absolute_error: 0.9929, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.4839, root_relative_squared_error: 1.0017, scimark_benchmark: 946.9694,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, build_cpu_time: 0.001, build_memory: 1071332056, f_measure: 0.4886, kb_relative_information_score: 1.5147, mean_absolute_error: 0.4556, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.3986, predictive_accuracy: 0.6313, prior_entropy: 0.9279, recall: 0.6313, relative_absolute_error: 0.9929, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.4839, root_relative_squared_error: 1.0017, scimark_benchmark: 943.2554,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, build_memory: 376033464, f_measure: 0.4886, kb_relative_information_score: 1.5147, mean_absolute_error: 0.4556, mean_prior_absolute_error: 0.4588, number_of_instances: 198, precision: 0.3986, predictive_accuracy: 0.6313, prior_entropy: 0.9279, recall: 0.6313, relative_absolute_error: 0.9929, root_mean_prior_squared_error: 0.4831, root_mean_squared_error: 0.4839, root_relative_squared_error: 1.0017, scimark_benchmark: 940.3415,

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