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A PHP Error was encountered

Severity: Warning

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Filename: models/Log.php

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Backtrace:

File: /var/www/openml/openml_OS/models/Log.php
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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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File: /var/www/openml/index.php
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Function: require_once

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Severity: Warning

Message: fopen(/data/log/sql.log): failed to open stream: Permission denied

Filename: models/Log.php

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Backtrace:

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Function: fopen

File: /var/www/openml/openml_OS/core/MY_Database_Read_Model.php
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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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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
OpenML
Supervised Classification on fri_c3_100_10

Supervised Classification on fri_c3_100_10

Task 3648 Supervised Classification fri_c3_100_10 799 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 study_7 under100k under1m
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799 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7731, build_cpu_time: 0.0825, build_memory: 1375077802.4, f_measure: 0.7094, kappa: 0.3933, kb_relative_information_score: 41.6232, mean_absolute_error: 0.2748, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7089, predictive_accuracy: 0.71, prior_entropy: 0.9721, recall: 0.71, relative_absolute_error: 0.572, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4951, root_relative_squared_error: 1.0106, scimark_benchmark: 902.712,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7704, build_cpu_time: 0.0547, build_memory: 2868863516, f_measure: 0.6986, kappa: 0.3697, kb_relative_information_score: 40.5927, mean_absolute_error: 0.2787, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.6978, predictive_accuracy: 0.7, prior_entropy: 0.9721, recall: 0.7, relative_absolute_error: 0.5801, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.5, root_relative_squared_error: 1.0206, scimark_benchmark: 927.3354,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7935, build_cpu_time: 0.0377, build_memory: 176444652, f_measure: 0.7011, kappa: 0.3802, kb_relative_information_score: 39.9704, mean_absolute_error: 0.2822, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7028, predictive_accuracy: 0.7, prior_entropy: 0.9721, recall: 0.7, relative_absolute_error: 0.5874, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.5024, root_relative_squared_error: 1.0254, scimark_benchmark: 945.0532,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.765, build_cpu_time: 0.022, build_memory: 874543993.6, f_measure: 0.7122, kappa: 0.4082, kb_relative_information_score: 38.3441, mean_absolute_error: 0.2916, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.718, predictive_accuracy: 0.71, prior_entropy: 0.9721, recall: 0.71, relative_absolute_error: 0.6069, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4985, root_relative_squared_error: 1.0176, scimark_benchmark: 930.5854,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8081, build_cpu_time: 0.0204, build_memory: 991443336.8, f_measure: 0.8086, kappa: 0.5992, kb_relative_information_score: 57.2987, mean_absolute_error: 0.2028, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.8088, predictive_accuracy: 0.81, prior_entropy: 0.9721, recall: 0.81, relative_absolute_error: 0.4222, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4365, root_relative_squared_error: 0.891, scimark_benchmark: 934.2858,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8271, build_cpu_time: 0.0251, build_memory: 346276898.4, f_measure: 0.7991, kappa: 0.5798, kb_relative_information_score: 58.3058, mean_absolute_error: 0.1963, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7988, predictive_accuracy: 0.8, prior_entropy: 0.9721, recall: 0.8, relative_absolute_error: 0.4086, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4329, root_relative_squared_error: 0.8837, scimark_benchmark: 943.7751,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8167, build_cpu_time: 0.0533, build_memory: 658307661.6, f_measure: 0.7991, kappa: 0.5798, kb_relative_information_score: 58.0201, mean_absolute_error: 0.1975, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7988, predictive_accuracy: 0.8, prior_entropy: 0.9721, recall: 0.8, relative_absolute_error: 0.4111, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4406, root_relative_squared_error: 0.8994, scimark_benchmark: 943.4039,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8265, build_cpu_time: 0.1231, build_memory: 331883079.2, f_measure: 0.7991, kappa: 0.5798, kb_relative_information_score: 58.0021, mean_absolute_error: 0.1973, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7988, predictive_accuracy: 0.8, prior_entropy: 0.9721, recall: 0.8, relative_absolute_error: 0.4107, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4413, root_relative_squared_error: 0.9008, scimark_benchmark: 914.1182,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8138, build_cpu_time: 0.2485, build_memory: 52357747.2, f_measure: 0.7991, kappa: 0.5798, kb_relative_information_score: 57.6303, mean_absolute_error: 0.1996, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7988, predictive_accuracy: 0.8, prior_entropy: 0.9721, recall: 0.8, relative_absolute_error: 0.4155, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4464, root_relative_squared_error: 0.9111, scimark_benchmark: 939.6298,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5833, build_cpu_time: 0.0118, build_memory: 971973927.2, f_measure: 0.6, kappa: 0.1667, kb_relative_information_score: 14.9353, mean_absolute_error: 0.4022, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.6, predictive_accuracy: 0.6, prior_entropy: 0.9721, recall: 0.6, relative_absolute_error: 0.8372, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.6256, root_relative_squared_error: 1.2771, scimark_benchmark: 907.4175,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5833, build_cpu_time: 0.0067, build_memory: 670629280.8, f_measure: 0.6, kappa: 0.1667, kb_relative_information_score: 14.9353, mean_absolute_error: 0.4022, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.6, predictive_accuracy: 0.6, prior_entropy: 0.9721, recall: 0.6, relative_absolute_error: 0.8372, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.6256, root_relative_squared_error: 1.2771, scimark_benchmark: 913.3372,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5833, build_cpu_time: 0.0046, build_memory: 1027439579.2, f_measure: 0.6, kappa: 0.1667, kb_relative_information_score: 14.9353, mean_absolute_error: 0.4022, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.6, predictive_accuracy: 0.6, prior_entropy: 0.9721, recall: 0.6, relative_absolute_error: 0.8372, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.6256, root_relative_squared_error: 1.2771, scimark_benchmark: 939.0159,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8077, build_cpu_time: 0.1408, build_memory: 27852604, f_measure: 0.7872, kappa: 0.5532, kb_relative_information_score: 51.5743, mean_absolute_error: 0.2329, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7886, predictive_accuracy: 0.79, prior_entropy: 0.9721, recall: 0.79, relative_absolute_error: 0.4849, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4322, root_relative_squared_error: 0.8822, scimark_benchmark: 924.6733,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8317, build_cpu_time: 0.409, build_memory: 770251312, f_measure: 0.7895, kappa: 0.5607, kb_relative_information_score: 55.9595, mean_absolute_error: 0.2075, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7892, predictive_accuracy: 0.79, prior_entropy: 0.9721, recall: 0.79, relative_absolute_error: 0.432, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4435, root_relative_squared_error: 0.9053, scimark_benchmark: 923.019,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8504, build_cpu_time: 0.2016, build_memory: 877867855.2, f_measure: 0.798, kappa: 0.5763, kb_relative_information_score: 58.3712, mean_absolute_error: 0.195, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7986, predictive_accuracy: 0.8, prior_entropy: 0.9721, recall: 0.8, relative_absolute_error: 0.4059, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4267, root_relative_squared_error: 0.8711, scimark_benchmark: 947.7459,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8598, build_cpu_time: 0.0833, build_memory: 829099524, f_measure: 0.7819, kappa: 0.5528, kb_relative_information_score: 53.9032, mean_absolute_error: 0.2175, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7894, predictive_accuracy: 0.78, prior_entropy: 0.9721, recall: 0.78, relative_absolute_error: 0.4528, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4437, root_relative_squared_error: 0.9056, scimark_benchmark: 940.9619,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7694, build_cpu_time: 0.044, build_memory: 1443731194.4, f_measure: 0.702, kappa: 0.3852, kb_relative_information_score: 35.2617, mean_absolute_error: 0.306, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7062, predictive_accuracy: 0.7, prior_entropy: 0.9721, recall: 0.7, relative_absolute_error: 0.637, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.5122, root_relative_squared_error: 1.0455, scimark_benchmark: 933.9589,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5933, build_cpu_time: 0.1977, build_memory: 806092407.2, f_measure: 0.613, kappa: 0.2041, kb_relative_information_score: 6.1601, mean_absolute_error: 0.4481, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.619, predictive_accuracy: 0.61, prior_entropy: 0.9721, recall: 0.61, relative_absolute_error: 0.9328, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.5229, root_relative_squared_error: 1.0674, scimark_benchmark: 945.7844,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8002, build_cpu_time: 0.0591, build_memory: 1230358674.4, f_measure: 0.741, kappa: 0.4628, kb_relative_information_score: 44.5128, mean_absolute_error: 0.2622, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7425, predictive_accuracy: 0.74, prior_entropy: 0.9721, recall: 0.74, relative_absolute_error: 0.5458, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4944, root_relative_squared_error: 1.0092, scimark_benchmark: 943.521,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.525, build_cpu_time: 0.0007, build_memory: 2048292877.6, f_measure: 0.5232, kappa: 0.0376, kb_relative_information_score: 1.3508, mean_absolute_error: 0.4736, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.5501, predictive_accuracy: 0.59, prior_entropy: 0.9721, recall: 0.59, relative_absolute_error: 0.986, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.5014, root_relative_squared_error: 1.0234, scimark_benchmark: 918.4301,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8535, build_cpu_time: 0.026, build_memory: 140589596.8, f_measure: 0.7885, kappa: 0.557, kb_relative_information_score: 36.1925, mean_absolute_error: 0.3222, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7884, predictive_accuracy: 0.79, prior_entropy: 0.9721, recall: 0.79, relative_absolute_error: 0.6707, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.3843, root_relative_squared_error: 0.7844, scimark_benchmark: 918.4301,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5833, build_cpu_time: 0.0002, build_memory: 602263792, f_measure: 0.6, kappa: 0.1667, kb_relative_information_score: 14.9353, mean_absolute_error: 0.4022, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.6, predictive_accuracy: 0.6, prior_entropy: 0.9721, recall: 0.6, relative_absolute_error: 0.8372, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.6256, root_relative_squared_error: 1.2771, scimark_benchmark: 938.6628,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8225, build_cpu_time: 0.0255, build_memory: 415737677.6, f_measure: 0.7727, kappa: 0.5217, kb_relative_information_score: 28.8868, mean_absolute_error: 0.3545, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7829, predictive_accuracy: 0.78, prior_entropy: 0.9721, recall: 0.78, relative_absolute_error: 0.738, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4076, root_relative_squared_error: 0.832, scimark_benchmark: 943.443,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8194, build_cpu_time: 0.0104, build_memory: 496091000, f_measure: 0.8156, kappa: 0.6121, kb_relative_information_score: 59.5115, mean_absolute_error: 0.1921, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.8228, predictive_accuracy: 0.82, prior_entropy: 0.9721, recall: 0.82, relative_absolute_error: 0.3998, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4243, root_relative_squared_error: 0.8661, scimark_benchmark: 941.5045,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6558, build_cpu_time: 0.0144, build_memory: 136122066.4, f_measure: 0.5891, kappa: 0.1423, kb_relative_information_score: 13.4755, mean_absolute_error: 0.4125, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.5883, predictive_accuracy: 0.59, prior_entropy: 0.9721, recall: 0.59, relative_absolute_error: 0.8587, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4981, root_relative_squared_error: 1.0168, scimark_benchmark: 942.1551,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6954, build_cpu_time: 12.8143, build_memory: 1721270011.2, f_measure: 0.64, kappa: 0.25, kb_relative_information_score: 18.767, mean_absolute_error: 0.3908, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.64, predictive_accuracy: 0.64, prior_entropy: 0.9721, recall: 0.64, relative_absolute_error: 0.8135, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.474, root_relative_squared_error: 0.9676, scimark_benchmark: 931.2177,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5923, build_cpu_time: 0.1341, build_memory: 88644477.6, f_measure: 0.5982, kappa: 0.1597, kb_relative_information_score: 10.054, mean_absolute_error: 0.4286, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.5968, predictive_accuracy: 0.6, prior_entropy: 0.9721, recall: 0.6, relative_absolute_error: 0.8921, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.5466, root_relative_squared_error: 1.1157, scimark_benchmark: 943.8359,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7663, build_cpu_time: 0.0051, build_memory: 722485692.8, f_measure: 0.7198, kappa: 0.4105, kb_relative_information_score: 20.5004, mean_absolute_error: 0.394, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7291, predictive_accuracy: 0.73, prior_entropy: 0.9721, recall: 0.73, relative_absolute_error: 0.8201, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4367, root_relative_squared_error: 0.8915, scimark_benchmark: 944.3501,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.64, build_cpu_time: 0.1598, build_memory: 2277411324.8, f_measure: 0.5891, kappa: 0.1423, kb_relative_information_score: 16.0056, mean_absolute_error: 0.3945, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.5883, predictive_accuracy: 0.59, prior_entropy: 0.9721, recall: 0.59, relative_absolute_error: 0.8211, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.5688, root_relative_squared_error: 1.1611, scimark_benchmark: 938.259,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7592, build_cpu_time: 0.0025, build_memory: 683427855.2, f_measure: 0.7132, kappa: 0.3966, kb_relative_information_score: 21.4975, mean_absolute_error: 0.3885, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7162, predictive_accuracy: 0.72, prior_entropy: 0.9721, recall: 0.72, relative_absolute_error: 0.8087, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.438, root_relative_squared_error: 0.8941, scimark_benchmark: 941.0301,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7429, build_cpu_time: 0.0024, build_memory: 133391672, f_measure: 0.6695, kappa: 0.3043, kb_relative_information_score: 20.0803, mean_absolute_error: 0.3904, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.6733, predictive_accuracy: 0.68, prior_entropy: 0.9721, recall: 0.68, relative_absolute_error: 0.8126, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4493, root_relative_squared_error: 0.917, scimark_benchmark: 944.9147,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7933, build_cpu_time: 0.4126, build_memory: 975995060.8, f_measure: 0.7171, kappa: 0.4068, kb_relative_information_score: 34.9537, mean_absolute_error: 0.3164, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7167, predictive_accuracy: 0.72, prior_entropy: 0.9721, recall: 0.72, relative_absolute_error: 0.6587, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.4268, root_relative_squared_error: 0.8712, scimark_benchmark: 942.6348,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8329, build_cpu_time: 0.711, build_memory: 1128826610.4, f_measure: 0.7589, kappa: 0.4958, kb_relative_information_score: 37.177, mean_absolute_error: 0.3111, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7584, predictive_accuracy: 0.76, prior_entropy: 0.9721, recall: 0.76, relative_absolute_error: 0.6475, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.3988, root_relative_squared_error: 0.8141, scimark_benchmark: 939.0518,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8425, build_cpu_time: 1.4429, build_memory: 194527033.6, f_measure: 0.7482, kappa: 0.4726, kb_relative_information_score: 36.8083, mean_absolute_error: 0.3134, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7477, predictive_accuracy: 0.75, prior_entropy: 0.9721, recall: 0.75, relative_absolute_error: 0.6525, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.3938, root_relative_squared_error: 0.8039, scimark_benchmark: 943.4191,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8308, build_cpu_time: 3.1759, build_memory: 1065197321.6, f_measure: 0.7388, kappa: 0.4538, kb_relative_information_score: 35.1676, mean_absolute_error: 0.322, mean_prior_absolute_error: 0.4804, number_of_instances: 100, precision: 0.7382, predictive_accuracy: 0.74, prior_entropy: 0.9721, recall: 0.74, relative_absolute_error: 0.6704, root_mean_prior_squared_error: 0.4899, root_mean_squared_error: 0.401, root_relative_squared_error: 0.8184, scimark_benchmark: 942.9632,

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