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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

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

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

A PHP Error was encountered

Severity: Warning

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

Filename: models/Log.php

Line Number: 37

Backtrace:

File: /var/www/openml/openml_OS/models/Log.php
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
Line: 124
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

A PHP Error was encountered

Severity: Warning

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

Filename: models/Log.php

Line Number: 37

Backtrace:

File: /var/www/openml/openml_OS/models/Log.php
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
Line: 117
Function: query

File: /var/www/openml/openml_OS/helpers/cms_helper.php
Line: 19
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
OpenML
Supervised Classification on spambase

Supervised Classification on spambase

Task 273 Supervised Classification spambase 367 runs submitted
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367 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9456, f_measure: 0.9068, kappa: 0.8031, kb_relative_information_score: 1135.2389, mean_absolute_error: 0.1203, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9068, predictive_accuracy: 0.9071, prior_entropy: 0.9674, recall: 0.9071, relative_absolute_error: 0.2525, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2744, root_relative_squared_error: 0.5629, scimark_benchmark: 889.3151, usercpu_time_millis: 6640, usercpu_time_millis_testing: 6640,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9154, f_measure: 0.9244, kappa: 0.8402, kb_relative_information_score: 1269.2303, mean_absolute_error: 0.0751, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9251, predictive_accuracy: 0.9249, prior_entropy: 0.9674, recall: 0.9249, relative_absolute_error: 0.1576, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.274, root_relative_squared_error: 0.5622, scimark_benchmark: 1313.9994, usercpu_time_millis: 860, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 850,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6512, f_measure: 0.6817, kappa: 0.3439, kb_relative_information_score: 624.1945, mean_absolute_error: 0.274, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.7893, predictive_accuracy: 0.726, prior_entropy: 0.9674, recall: 0.726, relative_absolute_error: 0.5752, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.5235, root_relative_squared_error: 1.0739, scimark_benchmark: 930.5999, usercpu_time_millis: 112130, usercpu_time_millis_testing: 10580, usercpu_time_millis_training: 101550,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8879, f_measure: 0.9031, kappa: 0.7942, kb_relative_information_score: 1203.018, mean_absolute_error: 0.0955, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9065, predictive_accuracy: 0.9045, prior_entropy: 0.9674, recall: 0.9045, relative_absolute_error: 0.2005, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.3091, root_relative_squared_error: 0.634, scimark_benchmark: 916.5955, usercpu_time_millis: 330, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 300,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9781, f_measure: 0.9332, kappa: 0.859, kb_relative_information_score: 1126.2385, mean_absolute_error: 0.1331, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9334, predictive_accuracy: 0.9335, prior_entropy: 0.9674, recall: 0.9335, relative_absolute_error: 0.2793, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2358, root_relative_squared_error: 0.4837, scimark_benchmark: 895.5332, usercpu_time_millis: 5670, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 5650,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8464, f_measure: 0.8687, kappa: 0.7204, kb_relative_information_score: 1098.3599, mean_absolute_error: 0.1278, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.8784, predictive_accuracy: 0.8722, prior_entropy: 0.9674, recall: 0.8722, relative_absolute_error: 0.2683, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.3575, root_relative_squared_error: 0.7333, scimark_benchmark: 939.449, usercpu_time_millis: 860, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 850,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9836, f_measure: 0.9426, kappa: 0.879, kb_relative_information_score: 1237.3519, mean_absolute_error: 0.094, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9426, predictive_accuracy: 0.9427, prior_entropy: 0.9674, recall: 0.9427, relative_absolute_error: 0.1972, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2085, root_relative_squared_error: 0.4277, scimark_benchmark: 1355.9413, usercpu_time_millis: 153800, usercpu_time_millis_testing: 8600, usercpu_time_millis_training: 145200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9604, f_measure: 0.8952, kappa: 0.7782, kb_relative_information_score: 1173.6395, mean_absolute_error: 0.1051, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.8958, predictive_accuracy: 0.8959, prior_entropy: 0.9674, recall: 0.8959, relative_absolute_error: 0.2205, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2996, root_relative_squared_error: 0.6146, scimark_benchmark: 1028.5889, usercpu_time_millis: 160, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9634, f_measure: 0.9269, kappa: 0.8464, kb_relative_information_score: 1217.7283, mean_absolute_error: 0.0968, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.927, predictive_accuracy: 0.9269, prior_entropy: 0.9674, recall: 0.9269, relative_absolute_error: 0.2033, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2451, root_relative_squared_error: 0.5029, scimark_benchmark: 1073.494, usercpu_time_millis: 48590, usercpu_time_millis_testing: 140, usercpu_time_millis_training: 48450,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8992, f_measure: 0.9009, kappa: 0.7923, kb_relative_information_score: 1190.2027, mean_absolute_error: 0.0995, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9017, predictive_accuracy: 0.9005, prior_entropy: 0.9674, recall: 0.9005, relative_absolute_error: 0.2088, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.3154, root_relative_squared_error: 0.647, scimark_benchmark: 1315.3881, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9549, f_measure: 0.9105, kappa: 0.8108, kb_relative_information_score: 1109.9495, mean_absolute_error: 0.1362, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.911, predictive_accuracy: 0.9111, prior_entropy: 0.9674, recall: 0.9111, relative_absolute_error: 0.286, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2721, root_relative_squared_error: 0.5581, scimark_benchmark: 1335.4072, usercpu_time_millis: 140, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9367, f_measure: 0.9218, kappa: 0.8345, kb_relative_information_score: 1178.1865, mean_absolute_error: 0.1132, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9225, predictive_accuracy: 0.9223, prior_entropy: 0.9674, recall: 0.9223, relative_absolute_error: 0.2376, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2654, root_relative_squared_error: 0.5444, scimark_benchmark: 1290.1085, usercpu_time_millis: 2420, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 2410,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9169, f_measure: 0.9252, kappa: 0.8418, kb_relative_information_score: 1271.3662, mean_absolute_error: 0.0744, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9256, predictive_accuracy: 0.9256, prior_entropy: 0.9674, recall: 0.9256, relative_absolute_error: 0.1562, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2728, root_relative_squared_error: 0.5597, scimark_benchmark: 1372.2145, usercpu_time_millis: 6200, usercpu_time_millis_testing: 2970, usercpu_time_millis_training: 3230,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5438, f_measure: 0.5374, kappa: 0.105, kb_relative_information_score: 361.4812, mean_absolute_error: 0.3551, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.7615, predictive_accuracy: 0.6449, prior_entropy: 0.9674, recall: 0.6449, relative_absolute_error: 0.7453, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.5959, root_relative_squared_error: 1.2224, scimark_benchmark: 1368.9272, usercpu_time_millis: 130, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9587, f_measure: 0.9278, kappa: 0.8489, kb_relative_information_score: 1261.9605, mean_absolute_error: 0.0799, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9289, predictive_accuracy: 0.9275, prior_entropy: 0.9674, recall: 0.9275, relative_absolute_error: 0.1677, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2399, root_relative_squared_error: 0.4921, scimark_benchmark: 1384.4418, usercpu_time_millis: 1210, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 1200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7736, f_measure: 0.7877, kappa: 0.5516, kb_relative_information_score: 827.1031, mean_absolute_error: 0.2115, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.7872, predictive_accuracy: 0.7885, prior_entropy: 0.9674, recall: 0.7885, relative_absolute_error: 0.4439, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.4599, root_relative_squared_error: 0.9433, scimark_benchmark: 1465.2979, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9156, f_measure: 0.9111, kappa: 0.8151, kb_relative_information_score: 1222.2409, mean_absolute_error: 0.0896, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9151, predictive_accuracy: 0.9104, prior_entropy: 0.9674, recall: 0.9104, relative_absolute_error: 0.1881, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2993, root_relative_squared_error: 0.614, scimark_benchmark: 977.6382, usercpu_time_millis: 1240, usercpu_time_millis_training: 1240,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4639, kb_relative_information_score: -3.4013, mean_absolute_error: 0.477, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.3737, predictive_accuracy: 0.6113, prior_entropy: 0.9674, recall: 0.6113, relative_absolute_error: 1.0012, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.4875, root_relative_squared_error: 1.0001, scimark_benchmark: 1054.3694,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9297, f_measure: 0.9285, kappa: 0.849, kb_relative_information_score: 1251.7673, mean_absolute_error: 0.0842, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9289, predictive_accuracy: 0.9289, prior_entropy: 0.9674, recall: 0.9289, relative_absolute_error: 0.1767, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2539, root_relative_squared_error: 0.5207, scimark_benchmark: 1066.833, usercpu_time_millis: 470, usercpu_time_millis_training: 470,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9673, build_cpu_time: 5.217, build_memory: 42801168, f_measure: 0.9082, kappa: 0.8048, kb_relative_information_score: 1124.7345, mean_absolute_error: 0.1292, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9132, predictive_accuracy: 0.9098, prior_entropy: 0.9674, recall: 0.9098, relative_absolute_error: 0.2711, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2596, root_relative_squared_error: 0.5325, scimark_benchmark: 941.9296,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9673, build_cpu_time: 5.298, build_memory: 2322391736, f_measure: 0.9082, kappa: 0.8048, kb_relative_information_score: 1124.7345, mean_absolute_error: 0.1292, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9132, predictive_accuracy: 0.9098, prior_entropy: 0.9674, recall: 0.9098, relative_absolute_error: 0.2711, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2596, root_relative_squared_error: 0.5325, scimark_benchmark: 938.8409,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9673, build_cpu_time: 5.634, build_memory: 243855664, f_measure: 0.9082, kappa: 0.8048, kb_relative_information_score: 1124.7345, mean_absolute_error: 0.1292, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9132, predictive_accuracy: 0.9098, prior_entropy: 0.9674, recall: 0.9098, relative_absolute_error: 0.2711, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2596, root_relative_squared_error: 0.5325, scimark_benchmark: 919.6575,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9673, build_cpu_time: 5.584, build_memory: 907620592, f_measure: 0.9082, kappa: 0.8048, kb_relative_information_score: 1124.7345, mean_absolute_error: 0.1292, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9132, predictive_accuracy: 0.9098, prior_entropy: 0.9674, recall: 0.9098, relative_absolute_error: 0.2711, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2596, root_relative_squared_error: 0.5325, scimark_benchmark: 929.9115,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9627, build_cpu_time: 2.98, build_memory: 1486155232, f_measure: 0.9075, kappa: 0.8034, kb_relative_information_score: 1102.939, mean_absolute_error: 0.1366, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9127, predictive_accuracy: 0.9091, prior_entropy: 0.9674, recall: 0.9091, relative_absolute_error: 0.2866, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2623, root_relative_squared_error: 0.538, scimark_benchmark: 923.564,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9792, build_cpu_time: 1.34, build_memory: 48640232, f_measure: 0.9366, kappa: 0.8661, kb_relative_information_score: 1303.9422, mean_absolute_error: 0.0653, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9367, predictive_accuracy: 0.9368, prior_entropy: 0.9674, recall: 0.9368, relative_absolute_error: 0.1371, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2255, root_relative_squared_error: 0.4626, scimark_benchmark: 926.9332,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9826, build_cpu_time: 3.872, build_memory: 115682344, f_measure: 0.9453, kappa: 0.8849, kb_relative_information_score: 1328.9903, mean_absolute_error: 0.0572, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9453, predictive_accuracy: 0.9453, prior_entropy: 0.9674, recall: 0.9453, relative_absolute_error: 0.12, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2177, root_relative_squared_error: 0.4465, scimark_benchmark: 935.1201,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9824, build_cpu_time: 9.993, build_memory: 716954432, f_measure: 0.9539, kappa: 0.9031, kb_relative_information_score: 1358.1156, mean_absolute_error: 0.0481, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.954, predictive_accuracy: 0.9539, prior_entropy: 0.9674, recall: 0.9539, relative_absolute_error: 0.101, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2054, root_relative_squared_error: 0.4213, scimark_benchmark: 941.7891,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9824, build_cpu_time: 7.502, build_memory: 57186952, f_measure: 0.9539, kappa: 0.9031, kb_relative_information_score: 1358.1156, mean_absolute_error: 0.0481, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.954, predictive_accuracy: 0.9539, prior_entropy: 0.9674, recall: 0.9539, relative_absolute_error: 0.101, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2054, root_relative_squared_error: 0.4213, scimark_benchmark: 941.7846,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9806, build_cpu_time: 11.453, build_memory: 97977032, f_measure: 0.9532, kappa: 0.9015, kb_relative_information_score: 1357.4847, mean_absolute_error: 0.0481, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9532, predictive_accuracy: 0.9532, prior_entropy: 0.9674, recall: 0.9532, relative_absolute_error: 0.101, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2101, root_relative_squared_error: 0.4311, scimark_benchmark: 941.8181,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9806, build_cpu_time: 14.941, build_memory: 331356952, f_measure: 0.9532, kappa: 0.9015, kb_relative_information_score: 1357.4847, mean_absolute_error: 0.0481, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9532, predictive_accuracy: 0.9532, prior_entropy: 0.9674, recall: 0.9532, relative_absolute_error: 0.101, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2101, root_relative_squared_error: 0.4311, scimark_benchmark: 895.3841,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.971, build_cpu_time: 6.403, build_memory: 527559080, f_measure: 0.9367, kappa: 0.8668, kb_relative_information_score: 1304.5431, mean_absolute_error: 0.0643, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9367, predictive_accuracy: 0.9368, prior_entropy: 0.9674, recall: 0.9368, relative_absolute_error: 0.1351, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2437, root_relative_squared_error: 0.4999, scimark_benchmark: 939.8609,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9706, build_cpu_time: 3.529, build_memory: 1963731752, f_measure: 0.9341, kappa: 0.8612, kb_relative_information_score: 1297.7171, mean_absolute_error: 0.0665, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9341, predictive_accuracy: 0.9341, prior_entropy: 0.9674, recall: 0.9341, relative_absolute_error: 0.1395, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2479, root_relative_squared_error: 0.5085, scimark_benchmark: 934.6076,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9065, build_cpu_time: 0.001, build_memory: 129058312, f_measure: 0.9064, kappa: 0.803, kb_relative_information_score: 1207.7657, mean_absolute_error: 0.0941, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9064, predictive_accuracy: 0.9065, prior_entropy: 0.9674, recall: 0.9065, relative_absolute_error: 0.1976, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.306, root_relative_squared_error: 0.6278, scimark_benchmark: 875.7999,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7736, build_cpu_time: 0.048, build_memory: 1266146608, f_measure: 0.7877, kappa: 0.5516, kb_relative_information_score: 827.1031, mean_absolute_error: 0.2115, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.7872, predictive_accuracy: 0.7885, prior_entropy: 0.9674, recall: 0.7885, relative_absolute_error: 0.4439, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.4599, root_relative_squared_error: 0.9433, scimark_benchmark: 946.8522,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9297, build_cpu_time: 0.583, build_memory: 544870160, f_measure: 0.9285, kappa: 0.849, kb_relative_information_score: 1251.7673, mean_absolute_error: 0.0842, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.9289, predictive_accuracy: 0.9289, prior_entropy: 0.9674, recall: 0.9289, relative_absolute_error: 0.1767, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.2539, root_relative_squared_error: 0.5207, scimark_benchmark: 940.3415,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, build_cpu_time: 0.001, build_memory: 415379816, f_measure: 0.4639, kb_relative_information_score: -3.4013, mean_absolute_error: 0.477, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.3737, predictive_accuracy: 0.6113, prior_entropy: 0.9674, recall: 0.6113, relative_absolute_error: 1.0012, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.4875, root_relative_squared_error: 1.0001, scimark_benchmark: 949.9767,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7821, build_cpu_time: 0.003, build_memory: 70708728, f_measure: 0.7931, kappa: 0.5644, kb_relative_information_score: 842.0543, mean_absolute_error: 0.2069, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.793, predictive_accuracy: 0.7931, prior_entropy: 0.9674, recall: 0.7931, relative_absolute_error: 0.4342, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.4548, root_relative_squared_error: 0.933, scimark_benchmark: 944.7664,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7821, build_cpu_time: 0.003, build_memory: 82709584, f_measure: 0.7931, kappa: 0.5644, kb_relative_information_score: 842.0543, mean_absolute_error: 0.2069, mean_prior_absolute_error: 0.4764, number_of_instances: 1518, precision: 0.793, predictive_accuracy: 0.7931, prior_entropy: 0.9674, recall: 0.7931, relative_absolute_error: 0.4342, root_mean_prior_squared_error: 0.4875, root_mean_squared_error: 0.4548, root_relative_squared_error: 0.933, scimark_benchmark: 946.523,

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