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A PHP Error was encountered

Severity: Warning

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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

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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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Function: loadpage

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

OpenML
OpenML
Supervised Classification on fri_c4_100_100

Supervised Classification on fri_c4_100_100

Task 3693 Supervised Classification fri_c4_100_100 536 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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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7995, build_cpu_time: 0.0967, build_memory: 968354051.2, f_measure: 0.6787, kappa: 0.3546, kb_relative_information_score: 38.9696, mean_absolute_error: 0.3013, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.6796, predictive_accuracy: 0.68, prior_entropy: 0.9975, recall: 0.68, relative_absolute_error: 0.6048, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.5256, root_relative_squared_error: 1.0531, scimark_benchmark: 945.0532,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.831, build_cpu_time: 0.2368, build_memory: 654154966.4, f_measure: 0.76, kappa: 0.5183, kb_relative_information_score: 51.8554, mean_absolute_error: 0.2395, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.76, predictive_accuracy: 0.76, prior_entropy: 0.9975, recall: 0.76, relative_absolute_error: 0.4807, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4809, root_relative_squared_error: 0.9634, scimark_benchmark: 923.9118,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8306, build_cpu_time: 0.4944, build_memory: 3397426744, f_measure: 0.7802, kappa: 0.5595, kb_relative_information_score: 55.2698, mean_absolute_error: 0.2223, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.781, predictive_accuracy: 0.78, prior_entropy: 0.9975, recall: 0.78, relative_absolute_error: 0.4461, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4667, root_relative_squared_error: 0.9351, scimark_benchmark: 927.3354,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7824, build_cpu_time: 0.9148, build_memory: 651562739.2, f_measure: 0.7702, kappa: 0.54, kb_relative_information_score: 53.8705, mean_absolute_error: 0.2293, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7718, predictive_accuracy: 0.77, prior_entropy: 0.9975, recall: 0.77, relative_absolute_error: 0.4602, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4742, root_relative_squared_error: 0.9501, scimark_benchmark: 873.8637,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7824, build_cpu_time: 1.7111, build_memory: 2721660592, f_measure: 0.7602, kappa: 0.5206, kb_relative_information_score: 52.5904, mean_absolute_error: 0.2355, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7628, predictive_accuracy: 0.76, prior_entropy: 0.9975, recall: 0.76, relative_absolute_error: 0.4726, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4771, root_relative_squared_error: 0.9558, scimark_benchmark: 931.9671,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4769, build_cpu_time: 0.0189, build_memory: 813959568, f_measure: 0.4792, kappa: -0.0463, kb_relative_information_score: -4.4679, mean_absolute_error: 0.5196, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.4787, predictive_accuracy: 0.48, prior_entropy: 0.9975, recall: 0.48, relative_absolute_error: 1.0428, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.7133, root_relative_squared_error: 1.4292, scimark_benchmark: 907.4175,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4769, build_cpu_time: 0.0245, build_memory: 96417098.4, f_measure: 0.4792, kappa: -0.0463, kb_relative_information_score: -4.4679, mean_absolute_error: 0.5196, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.4787, predictive_accuracy: 0.48, prior_entropy: 0.9975, recall: 0.48, relative_absolute_error: 1.0428, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.7133, root_relative_squared_error: 1.4292, scimark_benchmark: 941.1411,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4769, build_cpu_time: 0.0114, build_memory: 440312498.4, f_measure: 0.4792, kappa: -0.0463, kb_relative_information_score: -4.4679, mean_absolute_error: 0.5196, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.4787, predictive_accuracy: 0.48, prior_entropy: 0.9975, recall: 0.48, relative_absolute_error: 1.0428, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.7133, root_relative_squared_error: 1.4292, scimark_benchmark: 939.7233,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8105, build_cpu_time: 0.5661, build_memory: 26471697.6, f_measure: 0.7501, kappa: 0.4988, kb_relative_information_score: 49.3529, mean_absolute_error: 0.253, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7504, predictive_accuracy: 0.75, prior_entropy: 0.9975, recall: 0.75, relative_absolute_error: 0.5079, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4732, root_relative_squared_error: 0.948, scimark_benchmark: 944.4197,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8519, build_cpu_time: 2.2385, build_memory: 1263863284.8, f_measure: 0.8101, kappa: 0.6191, kb_relative_information_score: 59.6667, mean_absolute_error: 0.2017, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.8104, predictive_accuracy: 0.81, prior_entropy: 0.9975, recall: 0.81, relative_absolute_error: 0.4048, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4382, root_relative_squared_error: 0.878, scimark_benchmark: 938.2126,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8481, build_cpu_time: 1.2013, build_memory: 2456055528, f_measure: 0.7802, kappa: 0.5605, kb_relative_information_score: 54.7261, mean_absolute_error: 0.2252, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7828, predictive_accuracy: 0.78, prior_entropy: 0.9975, recall: 0.78, relative_absolute_error: 0.452, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4539, root_relative_squared_error: 0.9094, scimark_benchmark: 938.8854,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8019, build_cpu_time: 0.6505, build_memory: 1822024231.2, f_measure: 0.7092, kappa: 0.4158, kb_relative_information_score: 43.3242, mean_absolute_error: 0.2806, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7097, predictive_accuracy: 0.71, prior_entropy: 0.9975, recall: 0.71, relative_absolute_error: 0.5632, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.5091, root_relative_squared_error: 1.0201, scimark_benchmark: 932.084,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7806, build_cpu_time: 0.3183, build_memory: 1473778169.6, f_measure: 0.72, kappa: 0.438, kb_relative_information_score: 42.1267, mean_absolute_error: 0.2896, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.72, predictive_accuracy: 0.72, prior_entropy: 0.9975, recall: 0.72, relative_absolute_error: 0.5812, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.5053, root_relative_squared_error: 1.0123, scimark_benchmark: 940.4464,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.603, build_cpu_time: 0.3663, build_memory: 61392552.8, f_measure: 0.5497, kappa: 0.0957, kb_relative_information_score: 13.1386, mean_absolute_error: 0.4329, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.5495, predictive_accuracy: 0.55, prior_entropy: 0.9975, recall: 0.55, relative_absolute_error: 0.8689, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.6218, root_relative_squared_error: 1.2458, scimark_benchmark: 919.966,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8202, build_cpu_time: 0.0503, build_memory: 110357855.2, f_measure: 0.7195, kappa: 0.4366, kb_relative_information_score: 40.2198, mean_absolute_error: 0.3055, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7197, predictive_accuracy: 0.72, prior_entropy: 0.9975, recall: 0.72, relative_absolute_error: 0.6131, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4329, root_relative_squared_error: 0.8673, scimark_benchmark: 902.0906,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8324, build_cpu_time: 0.2815, build_memory: 390702227.2, f_measure: 0.7796, kappa: 0.5626, kb_relative_information_score: 42.8871, mean_absolute_error: 0.297, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7894, predictive_accuracy: 0.78, prior_entropy: 0.9975, recall: 0.78, relative_absolute_error: 0.5961, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.3963, root_relative_squared_error: 0.794, scimark_benchmark: 946.662,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8324, build_cpu_time: 0.0071, build_memory: 315838852.8, f_measure: 0.7796, kappa: 0.5626, kb_relative_information_score: 42.847, mean_absolute_error: 0.2972, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7894, predictive_accuracy: 0.78, prior_entropy: 0.9975, recall: 0.78, relative_absolute_error: 0.5966, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.3964, root_relative_squared_error: 0.7943, scimark_benchmark: 942.4411,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.774, build_cpu_time: 0.0467, build_memory: 1134853988, f_measure: 0.6772, kappa: 0.3648, kb_relative_information_score: 12.0654, mean_absolute_error: 0.4507, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7086, predictive_accuracy: 0.69, prior_entropy: 0.9975, recall: 0.69, relative_absolute_error: 0.9046, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4595, root_relative_squared_error: 0.9208, scimark_benchmark: 892.0716,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7676, build_cpu_time: 0.013, build_memory: 58677679.2, f_measure: 0.7561, kappa: 0.5274, kb_relative_information_score: 40.361, mean_absolute_error: 0.3081, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7935, predictive_accuracy: 0.76, prior_entropy: 0.9975, recall: 0.76, relative_absolute_error: 0.6184, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4228, root_relative_squared_error: 0.8472, scimark_benchmark: 920.2722,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4769, build_cpu_time: 0.0003, build_memory: 676081546.4, f_measure: 0.4792, kappa: -0.0463, kb_relative_information_score: -4.4679, mean_absolute_error: 0.5196, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.4787, predictive_accuracy: 0.48, prior_entropy: 0.9975, recall: 0.48, relative_absolute_error: 1.0428, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.7133, root_relative_squared_error: 1.4292, scimark_benchmark: 938.6628,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5012, build_cpu_time: 0.0081, build_memory: 174313301.6, f_measure: 0.3842, kappa: 0.0025, kb_relative_information_score: 5.519, mean_absolute_error: 0.47, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.5162, predictive_accuracy: 0.53, prior_entropy: 0.9975, recall: 0.53, relative_absolute_error: 0.9433, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.6856, root_relative_squared_error: 1.3736, scimark_benchmark: 943.232,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5761, build_cpu_time: 0.0128, build_memory: 565932960.8, f_measure: 0.5783, kappa: 0.1529, kb_relative_information_score: 15.5691, mean_absolute_error: 0.42, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.5785, predictive_accuracy: 0.58, prior_entropy: 0.9975, recall: 0.58, relative_absolute_error: 0.843, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.6481, root_relative_squared_error: 1.2985, scimark_benchmark: 939.059,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5241, build_cpu_time: 0.0283, build_memory: 772137831.2, f_measure: 0.5256, kappa: 0.0486, kb_relative_information_score: 5.519, mean_absolute_error: 0.47, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.5265, predictive_accuracy: 0.53, prior_entropy: 0.9975, recall: 0.53, relative_absolute_error: 0.9433, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.6856, root_relative_squared_error: 1.3736, scimark_benchmark: 926.8365,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4984, build_cpu_time: 0.0272, build_memory: 80581414.4, f_measure: 0.4903, kappa: -0.0225, kb_relative_information_score: -3.575, mean_absolute_error: 0.5156, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.4906, predictive_accuracy: 0.49, prior_entropy: 0.9975, recall: 0.49, relative_absolute_error: 1.0349, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.7133, root_relative_squared_error: 1.4291, scimark_benchmark: 926.786,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8167, build_cpu_time: 0.0395, build_memory: 884962232, f_measure: 0.7573, kappa: 0.5263, kb_relative_information_score: 41.31, mean_absolute_error: 0.3037, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7857, predictive_accuracy: 0.76, prior_entropy: 0.9975, recall: 0.76, relative_absolute_error: 0.6095, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4021, root_relative_squared_error: 0.8056, scimark_benchmark: 933.4176,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8344, build_cpu_time: 0.0471, build_memory: 28638518.4, f_measure: 0.7802, kappa: 0.5595, kb_relative_information_score: 44.5782, mean_absolute_error: 0.2837, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.781, predictive_accuracy: 0.78, prior_entropy: 0.9975, recall: 0.78, relative_absolute_error: 0.5694, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.419, root_relative_squared_error: 0.8395, scimark_benchmark: 933.4176,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7081, build_cpu_time: 0.0099, build_memory: 203170744, f_measure: 0.7493, kappa: 0.4964, kb_relative_information_score: 48.037, mean_absolute_error: 0.2616, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.75, predictive_accuracy: 0.75, prior_entropy: 0.9975, recall: 0.75, relative_absolute_error: 0.5251, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4928, root_relative_squared_error: 0.9874, scimark_benchmark: 922.2602,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7611, build_cpu_time: 24.1885, build_memory: 1462780505.6, f_measure: 0.6481, kappa: 0.2932, kb_relative_information_score: 26.0808, mean_absolute_error: 0.377, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.6494, predictive_accuracy: 0.65, prior_entropy: 0.9975, recall: 0.65, relative_absolute_error: 0.7566, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4488, root_relative_squared_error: 0.8992, scimark_benchmark: 944.2618,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8202, build_cpu_time: 0.0588, build_memory: 569354351.2, f_measure: 0.7195, kappa: 0.4366, kb_relative_information_score: 40.2198, mean_absolute_error: 0.3055, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7197, predictive_accuracy: 0.72, prior_entropy: 0.9975, recall: 0.72, relative_absolute_error: 0.6131, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4329, root_relative_squared_error: 0.8673, scimark_benchmark: 946.2416,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8202, build_cpu_time: 0.0438, build_memory: 398203805.6, f_measure: 0.7195, kappa: 0.4366, kb_relative_information_score: 40.2198, mean_absolute_error: 0.3055, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7197, predictive_accuracy: 0.72, prior_entropy: 0.9975, recall: 0.72, relative_absolute_error: 0.6131, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4329, root_relative_squared_error: 0.8673, scimark_benchmark: 945.9825,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8202, build_cpu_time: 0.0577, build_memory: 1284596175.2, f_measure: 0.7195, kappa: 0.4366, kb_relative_information_score: 40.2198, mean_absolute_error: 0.3055, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7197, predictive_accuracy: 0.72, prior_entropy: 0.9975, recall: 0.72, relative_absolute_error: 0.6131, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4329, root_relative_squared_error: 0.8673, scimark_benchmark: 942.0655,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8274, build_cpu_time: 1.0952, build_memory: 391107112, f_measure: 0.7687, kappa: 0.5444, kb_relative_information_score: 35.769, mean_absolute_error: 0.3365, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7865, predictive_accuracy: 0.77, prior_entropy: 0.9975, recall: 0.77, relative_absolute_error: 0.6755, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.3949, root_relative_squared_error: 0.7912, scimark_benchmark: 941.9476,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8246, build_cpu_time: 2.0885, build_memory: 1750740762.4, f_measure: 0.7881, kappa: 0.585, kb_relative_information_score: 37.0383, mean_absolute_error: 0.3305, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.8138, predictive_accuracy: 0.79, prior_entropy: 0.9975, recall: 0.79, relative_absolute_error: 0.6633, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.3923, root_relative_squared_error: 0.7861, scimark_benchmark: 943.063,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8185, build_cpu_time: 0.7924, build_memory: 1290018768.8, f_measure: 0.7381, kappa: 0.4856, kb_relative_information_score: 40.6896, mean_absolute_error: 0.3075, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7582, predictive_accuracy: 0.74, prior_entropy: 0.9975, recall: 0.74, relative_absolute_error: 0.6171, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.3943, root_relative_squared_error: 0.79, scimark_benchmark: 941.87,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8109, build_cpu_time: 0.4688, build_memory: 1200406917.6, f_measure: 0.7396, kappa: 0.4831, kb_relative_information_score: 40.0682, mean_absolute_error: 0.3103, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7487, predictive_accuracy: 0.74, prior_entropy: 0.9975, recall: 0.74, relative_absolute_error: 0.6229, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.3979, root_relative_squared_error: 0.7973, scimark_benchmark: 944.1276,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7933, build_cpu_time: 0.2036, build_memory: 930887413.6, f_measure: 0.7285, kappa: 0.4651, kb_relative_information_score: 40.1071, mean_absolute_error: 0.3091, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7451, predictive_accuracy: 0.73, prior_entropy: 0.9975, recall: 0.73, relative_absolute_error: 0.6205, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4067, root_relative_squared_error: 0.8148, scimark_benchmark: 839.7299,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.782, build_cpu_time: 0.1222, build_memory: 5293127504.8, f_measure: 0.7687, kappa: 0.5444, kb_relative_information_score: 38.5999, mean_absolute_error: 0.3178, mean_prior_absolute_error: 0.4982, number_of_instances: 100, precision: 0.7865, predictive_accuracy: 0.77, prior_entropy: 0.9975, recall: 0.77, relative_absolute_error: 0.6378, root_mean_prior_squared_error: 0.4991, root_mean_squared_error: 0.4143, root_relative_squared_error: 0.8302, scimark_benchmark: 937.4284,

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