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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: loadpage

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

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

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

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

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

OpenML
Task
Supervised Classification on datatrieve

Supervised Classification on datatrieve

Task 3923 Supervised Classification datatrieve 699 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_41 study_7 under100k under1m
Issue #Downvotes for this reason By


Metric:

699 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6325, f_measure: 0.8828, kappa: 0.1106, kb_relative_information_score: -7.427, mean_absolute_error: 0.1125, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8715, predictive_accuracy: 0.9077, prior_entropy: 0.4395, recall: 0.9077, relative_absolute_error: 0.7023, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2903, root_relative_squared_error: 1.0429, scimark_benchmark: 1304.9611,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.516, f_measure: 0.8597, kappa: 0.0366, kb_relative_information_score: -15.3158, mean_absolute_error: 0.1308, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8509, predictive_accuracy: 0.8692, prior_entropy: 0.4395, recall: 0.8692, relative_absolute_error: 0.8166, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3616, root_relative_squared_error: 1.299, scimark_benchmark: 1312.3073,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.8749, kb_relative_information_score: 33.7895, mean_absolute_error: 0.0846, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8379, predictive_accuracy: 0.9154, prior_entropy: 0.4395, recall: 0.9154, relative_absolute_error: 0.5284, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2909, root_relative_squared_error: 1.0449, scimark_benchmark: 938.9967,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.8749, kb_relative_information_score: 33.7895, mean_absolute_error: 0.0846, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8379, predictive_accuracy: 0.9154, prior_entropy: 0.4395, recall: 0.9154, relative_absolute_error: 0.5284, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2909, root_relative_squared_error: 1.0449, scimark_benchmark: 1250.8301,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.8749, kb_relative_information_score: -604.3696, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8379, predictive_accuracy: 0.9154, prior_entropy: 0.4395, recall: 0.9154, relative_absolute_error: 3.1223, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.5, root_relative_squared_error: 1.7961, scimark_benchmark: 1386.5717, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5474, f_measure: 0.7622, kappa: 0.0466, kb_relative_information_score: -195.3684, mean_absolute_error: 0.3, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8566, predictive_accuracy: 0.7, prior_entropy: 0.4395, recall: 0.7, relative_absolute_error: 1.8734, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.5477, root_relative_squared_error: 1.9675, scimark_benchmark: 938.9967, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8174, f_measure: 0.8781, kappa: 0.0924, kb_relative_information_score: -30.71, mean_absolute_error: 0.1414, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8639, predictive_accuracy: 0.9, prior_entropy: 0.4395, recall: 0.9, relative_absolute_error: 0.8827, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2819, root_relative_squared_error: 1.0127, scimark_benchmark: 916.9356, usercpu_time_millis: 80, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.8749, kb_relative_information_score: 33.7895, mean_absolute_error: 0.0846, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8379, predictive_accuracy: 0.9154, prior_entropy: 0.4395, recall: 0.9154, relative_absolute_error: 0.5284, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2909, root_relative_squared_error: 1.0449, scimark_benchmark: 1331.6907, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3617, f_measure: 0.8711, kappa: -0.0143, kb_relative_information_score: -30.1455, mean_absolute_error: 0.1677, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8373, predictive_accuracy: 0.9077, prior_entropy: 0.4395, recall: 0.9077, relative_absolute_error: 1.0473, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2961, root_relative_squared_error: 1.0637, scimark_benchmark: 1307.4861,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6409, f_measure: 0.8734, kappa: 0.0761, kb_relative_information_score: -69.9736, mean_absolute_error: 0.1528, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8591, predictive_accuracy: 0.8923, prior_entropy: 0.4395, recall: 0.8923, relative_absolute_error: 0.9545, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3006, root_relative_squared_error: 1.0797, scimark_benchmark: 825.5282, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4866, f_measure: 0.828, kappa: -0.023, kb_relative_information_score: -72.6052, mean_absolute_error: 0.1846, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8414, predictive_accuracy: 0.8154, prior_entropy: 0.4395, recall: 0.8154, relative_absolute_error: 1.1528, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.4297, root_relative_squared_error: 1.5435, scimark_benchmark: 1313.5726,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4045, f_measure: 0.8711, kappa: -0.0143, kb_relative_information_score: -16.0476, mean_absolute_error: 0.1613, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8373, predictive_accuracy: 0.9077, prior_entropy: 0.4395, recall: 0.9077, relative_absolute_error: 1.0072, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2948, root_relative_squared_error: 1.0589, scimark_benchmark: 1369.9744,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4553, f_measure: 0.8749, kb_relative_information_score: 2.3896, mean_absolute_error: 0.155, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8379, predictive_accuracy: 0.9154, prior_entropy: 0.4395, recall: 0.9154, relative_absolute_error: 0.9681, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2785, root_relative_squared_error: 1.0006, scimark_benchmark: 1355.7054,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5202, f_measure: 0.8643, kappa: 0.0485, kb_relative_information_score: -7.1316, mean_absolute_error: 0.1231, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8531, predictive_accuracy: 0.8769, prior_entropy: 0.4395, recall: 0.8769, relative_absolute_error: 0.7686, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3508, root_relative_squared_error: 1.2602, scimark_benchmark: 1291.6995,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5783, f_measure: 0.8915, kappa: 0.2081, kb_relative_information_score: 25.6053, mean_absolute_error: 0.0923, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8833, predictive_accuracy: 0.9077, prior_entropy: 0.4395, recall: 0.9077, relative_absolute_error: 0.5764, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3038, root_relative_squared_error: 1.0914, scimark_benchmark: 1319.9043,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4756, f_measure: 0.8593, kappa: -0.0473, kb_relative_information_score: -28.6818, mean_absolute_error: 0.1619, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8355, predictive_accuracy: 0.8846, prior_entropy: 0.4395, recall: 0.8846, relative_absolute_error: 1.0109, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3185, root_relative_squared_error: 1.1442, scimark_benchmark: 1358.4523,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.628, f_measure: 0.9096, kappa: 0.3401, kb_relative_information_score: 41.9737, mean_absolute_error: 0.0769, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.9076, predictive_accuracy: 0.9231, prior_entropy: 0.4395, recall: 0.9231, relative_absolute_error: 0.4803, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2774, root_relative_squared_error: 0.9963, scimark_benchmark: 1466.6185,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.479, f_measure: 0.8554, kappa: -0.0558, kb_relative_information_score: -7.1316, mean_absolute_error: 0.1231, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8348, predictive_accuracy: 0.8769, prior_entropy: 0.4395, recall: 0.8769, relative_absolute_error: 0.7686, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3508, root_relative_squared_error: 1.2602, scimark_benchmark: 1464.9318,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4553, f_measure: 0.8749, kb_relative_information_score: -5.1939, mean_absolute_error: 0.1608, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8379, predictive_accuracy: 0.9154, prior_entropy: 0.4395, recall: 0.9154, relative_absolute_error: 1.0043, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2786, root_relative_squared_error: 1.0009, scimark_benchmark: 1418.5826,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4473, f_measure: 0.8633, kappa: -0.0376, kb_relative_information_score: -23.1557, mean_absolute_error: 0.1598, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8361, predictive_accuracy: 0.8923, prior_entropy: 0.4395, recall: 0.8923, relative_absolute_error: 0.9979, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3136, root_relative_squared_error: 1.1266, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7235, f_measure: 0.8467, kappa: 0.1243, kb_relative_information_score: -55.0436, mean_absolute_error: 0.1667, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8655, predictive_accuracy: 0.8308, prior_entropy: 0.4395, recall: 0.8308, relative_absolute_error: 1.041, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3955, root_relative_squared_error: 1.4208, scimark_benchmark: 931.2336, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6933, f_measure: 0.8597, kappa: 0.0366, kb_relative_information_score: -16.1691, mean_absolute_error: 0.1304, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8509, predictive_accuracy: 0.8692, prior_entropy: 0.4395, recall: 0.8692, relative_absolute_error: 0.8146, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3441, root_relative_squared_error: 1.2359, scimark_benchmark: 945.6434, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7418, f_measure: 0.8633, kappa: -0.0376, kb_relative_information_score: -25.6981, mean_absolute_error: 0.1335, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8361, predictive_accuracy: 0.8923, prior_entropy: 0.4395, recall: 0.8923, relative_absolute_error: 0.8337, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3, root_relative_squared_error: 1.0777, scimark_benchmark: 941.7954, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7998, f_measure: 0.8633, kappa: -0.0376, kb_relative_information_score: -38.9943, mean_absolute_error: 0.1431, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8361, predictive_accuracy: 0.8923, prior_entropy: 0.4395, recall: 0.8923, relative_absolute_error: 0.8935, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2999, root_relative_squared_error: 1.0775, scimark_benchmark: 942.3168, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7998, f_measure: 0.8633, kappa: -0.0376, kb_relative_information_score: -38.9943, mean_absolute_error: 0.1431, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8361, predictive_accuracy: 0.8923, prior_entropy: 0.4395, recall: 0.8923, relative_absolute_error: 0.8935, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2999, root_relative_squared_error: 1.0775, scimark_benchmark: 934.5243, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5768, f_measure: 0.8812, kappa: 0.1674, kb_relative_information_score: 9.5968, mean_absolute_error: 0.107, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8726, predictive_accuracy: 0.8923, prior_entropy: 0.4395, recall: 0.8923, relative_absolute_error: 0.6682, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3224, root_relative_squared_error: 1.1582, scimark_benchmark: 936.7115, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6306, f_measure: 0.8915, kappa: 0.2081, kb_relative_information_score: 22.9057, mean_absolute_error: 0.0915, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8833, predictive_accuracy: 0.9077, prior_entropy: 0.4395, recall: 0.9077, relative_absolute_error: 0.5711, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2937, root_relative_squared_error: 1.055, scimark_benchmark: 943.2817, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6157, f_measure: 0.8969, kappa: 0.232, kb_relative_information_score: 33.2102, mean_absolute_error: 0.0859, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8923, predictive_accuracy: 0.9154, prior_entropy: 0.4395, recall: 0.9154, relative_absolute_error: 0.5364, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2904, root_relative_squared_error: 1.0431, scimark_benchmark: 936.6206, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7296, f_measure: 0.8969, kappa: 0.232, kb_relative_information_score: 33.667, mean_absolute_error: 0.0849, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8923, predictive_accuracy: 0.9154, prior_entropy: 0.4395, recall: 0.9154, relative_absolute_error: 0.5302, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2898, root_relative_squared_error: 1.041, scimark_benchmark: 934.5243, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7215, f_measure: 0.8969, kappa: 0.232, kb_relative_information_score: 33.4551, mean_absolute_error: 0.0854, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8923, predictive_accuracy: 0.9154, prior_entropy: 0.4395, recall: 0.9154, relative_absolute_error: 0.5332, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2906, root_relative_squared_error: 1.044, scimark_benchmark: 923.7642,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7739, f_measure: 0.8597, kappa: 0.0366, kb_relative_information_score: -9.6107, mean_absolute_error: 0.1244, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8509, predictive_accuracy: 0.8692, prior_entropy: 0.4395, recall: 0.8692, relative_absolute_error: 0.7766, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3428, root_relative_squared_error: 1.2313, scimark_benchmark: 938.4285, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7647, f_measure: 0.8643, kappa: 0.0485, kb_relative_information_score: -18.8385, mean_absolute_error: 0.128, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8531, predictive_accuracy: 0.8769, prior_entropy: 0.4395, recall: 0.8769, relative_absolute_error: 0.7993, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3376, root_relative_squared_error: 1.2126, scimark_benchmark: 943.2817, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.762, f_measure: 0.8812, kappa: 0.1674, kb_relative_information_score: -19.0322, mean_absolute_error: 0.1272, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8726, predictive_accuracy: 0.8923, prior_entropy: 0.4395, recall: 0.8923, relative_absolute_error: 0.7942, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.321, root_relative_squared_error: 1.1532, scimark_benchmark: 945.6434, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7781, f_measure: 0.8863, kappa: 0.1867, kb_relative_information_score: -14.6639, mean_absolute_error: 0.1245, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8772, predictive_accuracy: 0.9, prior_entropy: 0.4395, recall: 0.9, relative_absolute_error: 0.7775, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2956, root_relative_squared_error: 1.062, scimark_benchmark: 945.6434, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7998, build_cpu_time: 0.0121, build_memory: 374507142.4, f_measure: 0.8633, kappa: -0.0376, kb_relative_information_score: -38.9943, mean_absolute_error: 0.1431, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8361, predictive_accuracy: 0.8923, prior_entropy: 0.4395, recall: 0.8923, relative_absolute_error: 0.8935, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2999, root_relative_squared_error: 1.0775, scimark_benchmark: 943.2074,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7998, build_cpu_time: 0.0143, build_memory: 557203561.6, f_measure: 0.8633, kappa: -0.0376, kb_relative_information_score: -38.9943, mean_absolute_error: 0.1431, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8361, predictive_accuracy: 0.8923, prior_entropy: 0.4395, recall: 0.8923, relative_absolute_error: 0.8935, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.2999, root_relative_squared_error: 1.0775, scimark_benchmark: 943.2074,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7135, build_cpu_time: 0.7595, build_memory: 70005148.8, f_measure: 0.8643, kappa: 0.0485, kb_relative_information_score: -13.0936, mean_absolute_error: 0.1264, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8531, predictive_accuracy: 0.8769, prior_entropy: 0.4395, recall: 0.8769, relative_absolute_error: 0.7896, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.331, root_relative_squared_error: 1.1891, scimark_benchmark: 916.8903,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6864, build_cpu_time: 3.2524, build_memory: 850133932.8, f_measure: 0.8643, kappa: 0.0485, kb_relative_information_score: -6.1043, mean_absolute_error: 0.1184, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8531, predictive_accuracy: 0.8769, prior_entropy: 0.4395, recall: 0.8769, relative_absolute_error: 0.7396, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3358, root_relative_squared_error: 1.2064, scimark_benchmark: 940.3132,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5405, build_cpu_time: 5.8087, build_memory: 759351155.2, f_measure: 0.8713, kappa: 0.1341, kb_relative_information_score: -7.0541, mean_absolute_error: 0.1229, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8661, predictive_accuracy: 0.8769, prior_entropy: 0.4395, recall: 0.8769, relative_absolute_error: 0.7674, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3501, root_relative_squared_error: 1.2576, scimark_benchmark: 899.4388,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5202, build_cpu_time: 10.6103, build_memory: 69305963.2, f_measure: 0.8643, kappa: 0.0485, kb_relative_information_score: -7.1316, mean_absolute_error: 0.1231, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8531, predictive_accuracy: 0.8769, prior_entropy: 0.4395, recall: 0.8769, relative_absolute_error: 0.7686, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3508, root_relative_squared_error: 1.2602, scimark_benchmark: 934.9083,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.581, build_cpu_time: 1.3396, build_memory: 64260173.6, f_measure: 0.8664, kappa: 0.1195, kb_relative_information_score: -25.8174, mean_absolute_error: 0.1372, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8637, predictive_accuracy: 0.8692, prior_entropy: 0.4395, recall: 0.8692, relative_absolute_error: 0.8565, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3606, root_relative_squared_error: 1.2952, scimark_benchmark: 936.914,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.584, build_cpu_time: 0.7858, build_memory: 700185332.8, f_measure: 0.8664, kappa: 0.1195, kb_relative_information_score: -15.9752, mean_absolute_error: 0.1315, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8637, predictive_accuracy: 0.8692, prior_entropy: 0.4395, recall: 0.8692, relative_absolute_error: 0.8211, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3576, root_relative_squared_error: 1.2846, scimark_benchmark: 923.3659,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6138, build_cpu_time: 0.071, build_memory: 509101733.6, f_measure: 0.8713, kappa: 0.1341, kb_relative_information_score: -8.563, mean_absolute_error: 0.1241, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8661, predictive_accuracy: 0.8769, prior_entropy: 0.4395, recall: 0.8769, relative_absolute_error: 0.7747, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3464, root_relative_squared_error: 1.2443, scimark_benchmark: 942.3919,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5848, build_cpu_time: 0.1379, build_memory: 401592859.2, f_measure: 0.8713, kappa: 0.1341, kb_relative_information_score: -7.7948, mean_absolute_error: 0.1244, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8661, predictive_accuracy: 0.8769, prior_entropy: 0.4395, recall: 0.8769, relative_absolute_error: 0.7766, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3482, root_relative_squared_error: 1.2509, scimark_benchmark: 908.8705,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5126, build_cpu_time: 0.2975, build_memory: 235490733.6, f_measure: 0.8597, kappa: 0.0366, kb_relative_information_score: -15.3158, mean_absolute_error: 0.1308, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8509, predictive_accuracy: 0.8692, prior_entropy: 0.4395, recall: 0.8692, relative_absolute_error: 0.8166, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3616, root_relative_squared_error: 1.299, scimark_benchmark: 942.0692,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5164, build_cpu_time: 0.5315, build_memory: 355588989.6, f_measure: 0.8643, kappa: 0.0485, kb_relative_information_score: -12.3872, mean_absolute_error: 0.1262, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8531, predictive_accuracy: 0.8769, prior_entropy: 0.4395, recall: 0.8769, relative_absolute_error: 0.7882, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3527, root_relative_squared_error: 1.2668, scimark_benchmark: 920.2874,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5164, build_cpu_time: 1.2669, build_memory: 1097484992.8, f_measure: 0.8643, kappa: 0.0485, kb_relative_information_score: -7.1316, mean_absolute_error: 0.1231, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8531, predictive_accuracy: 0.8769, prior_entropy: 0.4395, recall: 0.8769, relative_absolute_error: 0.7686, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.3508, root_relative_squared_error: 1.2602, scimark_benchmark: 942.0692,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6547, build_cpu_time: 0.0355, build_memory: 733378601.6, f_measure: 0.8554, kappa: -0.0558, kb_relative_information_score: -14.736, mean_absolute_error: 0.125, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8348, predictive_accuracy: 0.8769, prior_entropy: 0.4395, recall: 0.8769, relative_absolute_error: 0.7808, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.341, root_relative_squared_error: 1.2248, scimark_benchmark: 945.0554,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6547, build_cpu_time: 0.0254, build_memory: 1162031222.4, f_measure: 0.8554, kappa: -0.0558, kb_relative_information_score: -14.736, mean_absolute_error: 0.125, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8348, predictive_accuracy: 0.8769, prior_entropy: 0.4395, recall: 0.8769, relative_absolute_error: 0.7808, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.341, root_relative_squared_error: 1.2248, scimark_benchmark: 913.3372,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6547, build_cpu_time: 0.023, build_memory: 870216497.6, f_measure: 0.8554, kappa: -0.0558, kb_relative_information_score: -14.736, mean_absolute_error: 0.125, mean_prior_absolute_error: 0.1601, number_of_instances: 130, precision: 0.8348, predictive_accuracy: 0.8769, prior_entropy: 0.4395, recall: 0.8769, relative_absolute_error: 0.7808, root_mean_prior_squared_error: 0.2784, root_mean_squared_error: 0.341, root_relative_squared_error: 1.2248, scimark_benchmark: 923.9118,

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