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Severity: Warning

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Function: fopen

File: /var/www/openml/openml_OS/core/MY_Database_Read_Model.php
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Function: sql

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

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Function: fopen

File: /var/www/openml/openml_OS/core/MY_Database_Read_Model.php
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Function: sql

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Function: loadpage

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

OpenML
OpenML
Supervised Classification on ecoli

Supervised Classification on ecoli

Task 1802 Supervised Classification ecoli 321 runs submitted
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321 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9392, f_measure: 0.8381, kappa: 0.7845, kb_relative_information_score: 1237.179, mean_absolute_error: 0.053, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.835, predictive_accuracy: 0.8446, prior_entropy: 2.2353, recall: 0.8446, relative_absolute_error: 0.2901, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.1791, root_relative_squared_error: 0.5938, scimark_benchmark: 940.3347, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5015, f_measure: 0.2541, kb_relative_information_score: 11.1091, mean_absolute_error: 0.1986, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.1811, predictive_accuracy: 0.4256, prior_entropy: 2.2353, recall: 0.4256, relative_absolute_error: 1.0863, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.3096, root_relative_squared_error: 1.0266, scimark_benchmark: 1372.2145, usercpu_time_millis: 170, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.938, f_measure: 0.7662, kappa: 0.7329, kb_relative_information_score: 211.8823, mean_absolute_error: 0.19, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.8049, predictive_accuracy: 0.8113, prior_entropy: 2.2353, recall: 0.8113, relative_absolute_error: 1.0394, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.2954, root_relative_squared_error: 0.9795, scimark_benchmark: 939.449, usercpu_time_millis: 100, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9628, f_measure: 0.8602, kappa: 0.8141, kb_relative_information_score: 1249.7069, mean_absolute_error: 0.0534, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.8554, predictive_accuracy: 0.8655, prior_entropy: 2.2353, recall: 0.8655, relative_absolute_error: 0.2922, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.1656, root_relative_squared_error: 0.549, scimark_benchmark: 1321.527, usercpu_time_millis: 130, usercpu_time_millis_training: 130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9078, f_measure: 0.852, kappa: 0.8068, kb_relative_information_score: 1283.6365, mean_absolute_error: 0.0345, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.8489, predictive_accuracy: 0.8619, prior_entropy: 2.2353, recall: 0.8619, relative_absolute_error: 0.1889, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.1858, root_relative_squared_error: 0.616, scimark_benchmark: 1250.8301,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9662, f_measure: 0.8214, kappa: 0.7608, kb_relative_information_score: 1231.4184, mean_absolute_error: 0.0537, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.8184, predictive_accuracy: 0.8268, prior_entropy: 2.2353, recall: 0.8268, relative_absolute_error: 0.2938, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.1747, root_relative_squared_error: 0.5793, scimark_benchmark: 1073.494,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9435, f_measure: 0.8086, kappa: 0.7429, kb_relative_information_score: 1082.8747, mean_absolute_error: 0.0753, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.8038, predictive_accuracy: 0.8143, prior_entropy: 2.2353, recall: 0.8143, relative_absolute_error: 0.4118, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.1889, root_relative_squared_error: 0.6264, scimark_benchmark: 1309.3173, usercpu_time_millis: 100, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9635, f_measure: 0.8478, kappa: 0.7979, kb_relative_information_score: 1190.943, mean_absolute_error: 0.0624, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.8432, predictive_accuracy: 0.8542, prior_entropy: 2.2353, recall: 0.8542, relative_absolute_error: 0.3416, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.1725, root_relative_squared_error: 0.5719, scimark_benchmark: 1298.285, usercpu_time_millis: 80, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8636, f_measure: 0.7835, kappa: 0.7038, kb_relative_information_score: 1141.7208, mean_absolute_error: 0.0542, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.7844, predictive_accuracy: 0.7833, prior_entropy: 2.2353, recall: 0.7833, relative_absolute_error: 0.2963, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.2327, root_relative_squared_error: 0.7716, scimark_benchmark: 1315.0767,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9083, f_measure: 0.7861, kappa: 0.7191, kb_relative_information_score: 1061.5647, mean_absolute_error: 0.0707, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.7804, predictive_accuracy: 0.7994, prior_entropy: 2.2353, recall: 0.7994, relative_absolute_error: 0.3871, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.202, root_relative_squared_error: 0.6697, scimark_benchmark: 1335.4072,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9082, f_measure: 0.8016, kappa: 0.7348, kb_relative_information_score: 1107.5815, mean_absolute_error: 0.0631, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.7969, predictive_accuracy: 0.8083, prior_entropy: 2.2353, recall: 0.8083, relative_absolute_error: 0.3452, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.2027, root_relative_squared_error: 0.672, scimark_benchmark: 1321.6263, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8987, f_measure: 0.8355, kappa: 0.7807, kb_relative_information_score: 1250.5118, mean_absolute_error: 0.0396, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.831, predictive_accuracy: 0.8417, prior_entropy: 2.2353, recall: 0.8417, relative_absolute_error: 0.2166, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.199, root_relative_squared_error: 0.6596, scimark_benchmark: 1386.5717, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6948, f_measure: 0.5724, kappa: 0.4116, kb_relative_information_score: 713.0752, mean_absolute_error: 0.0957, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.6245, predictive_accuracy: 0.6173, prior_entropy: 2.2353, recall: 0.6173, relative_absolute_error: 0.5235, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.3093, root_relative_squared_error: 1.0256, scimark_benchmark: 1368.9272,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8907, f_measure: 0.792, kappa: 0.7156, kb_relative_information_score: 1135.7712, mean_absolute_error: 0.0601, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.7942, predictive_accuracy: 0.7929, prior_entropy: 2.2353, recall: 0.7929, relative_absolute_error: 0.3286, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.2113, root_relative_squared_error: 0.7007, scimark_benchmark: 1341.2341, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7567, f_measure: 0.5928, kappa: 0.4908, kb_relative_information_score: 755.873, mean_absolute_error: 0.0884, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.5828, predictive_accuracy: 0.6464, prior_entropy: 2.2353, recall: 0.6464, relative_absolute_error: 0.4836, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.2973, root_relative_squared_error: 0.9857, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8566, f_measure: 0.7709, kappa: 0.6919, kb_relative_information_score: 1093.9706, mean_absolute_error: 0.0555, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.7694, predictive_accuracy: 0.778, prior_entropy: 2.2353, recall: 0.778, relative_absolute_error: 0.3037, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.2356, root_relative_squared_error: 0.7811, scimark_benchmark: 1028.5889, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4962, f_measure: 0.2541, kb_relative_information_score: 2.2336, mean_absolute_error: 0.1836, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.1811, predictive_accuracy: 0.4256, prior_entropy: 2.2353, recall: 0.4256, relative_absolute_error: 1.0045, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.3017, root_relative_squared_error: 1.0002, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8983, f_measure: 0.7999, kappa: 0.73, kb_relative_information_score: 1141.9747, mean_absolute_error: 0.0587, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.7969, predictive_accuracy: 0.8042, prior_entropy: 2.2353, recall: 0.8042, relative_absolute_error: 0.3212, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.2057, root_relative_squared_error: 0.6818, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9454, build_cpu_time: 0.5633, build_memory: 945381480.8, f_measure: 0.8482, kappa: 0.7961, kb_relative_information_score: 1114.748, mean_absolute_error: 0.0749, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.8465, predictive_accuracy: 0.8524, prior_entropy: 2.2353, recall: 0.8524, relative_absolute_error: 0.41, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.1794, root_relative_squared_error: 0.5949, scimark_benchmark: 932.2022,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9454, build_cpu_time: 0.5547, build_memory: 692917800, f_measure: 0.8482, kappa: 0.7961, kb_relative_information_score: 1114.748, mean_absolute_error: 0.0749, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.8465, predictive_accuracy: 0.8524, prior_entropy: 2.2353, recall: 0.8524, relative_absolute_error: 0.41, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.1794, root_relative_squared_error: 0.5949, scimark_benchmark: 926.9332,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9454, build_cpu_time: 0.5777, build_memory: 779013559.2, f_measure: 0.8482, kappa: 0.7961, kb_relative_information_score: 1114.748, mean_absolute_error: 0.0749, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.8465, predictive_accuracy: 0.8524, prior_entropy: 2.2353, recall: 0.8524, relative_absolute_error: 0.41, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.1794, root_relative_squared_error: 0.5949, scimark_benchmark: 938.8409,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9453, build_cpu_time: 0.5666, build_memory: 846546376, f_measure: 0.8482, kappa: 0.7961, kb_relative_information_score: 1113.0395, mean_absolute_error: 0.0752, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.8465, predictive_accuracy: 0.8524, prior_entropy: 2.2353, recall: 0.8524, relative_absolute_error: 0.4116, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.1795, root_relative_squared_error: 0.595, scimark_benchmark: 936.5273,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9427, build_cpu_time: 0.011, build_memory: 1124736948, f_measure: 0.8207, kappa: 0.7622, kb_relative_information_score: 1146.9295, mean_absolute_error: 0.0636, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.8166, predictive_accuracy: 0.8292, prior_entropy: 2.2353, recall: 0.8292, relative_absolute_error: 0.348, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.1845, root_relative_squared_error: 0.6118, scimark_benchmark: 918.7639,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9405, build_cpu_time: 0.0136, build_memory: 63174904.8, f_measure: 0.8167, kappa: 0.756, kb_relative_information_score: 1156.6339, mean_absolute_error: 0.0615, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.8125, predictive_accuracy: 0.8244, prior_entropy: 2.2353, recall: 0.8244, relative_absolute_error: 0.3364, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.1858, root_relative_squared_error: 0.616, scimark_benchmark: 926.638,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9475, build_cpu_time: 0.0968, build_memory: 2150599956, f_measure: 0.8206, kappa: 0.7582, kb_relative_information_score: 1234.6104, mean_absolute_error: 0.0443, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.8183, predictive_accuracy: 0.8244, prior_entropy: 2.2353, recall: 0.8244, relative_absolute_error: 0.2422, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.1975, root_relative_squared_error: 0.6547, scimark_benchmark: 892.0716,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9635, build_cpu_time: 0.0411, build_memory: 1870053420, f_measure: 0.8478, kappa: 0.7979, kb_relative_information_score: 1190.943, mean_absolute_error: 0.0624, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.8432, predictive_accuracy: 0.8542, prior_entropy: 2.2353, recall: 0.8542, relative_absolute_error: 0.3416, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.1725, root_relative_squared_error: 0.5719, scimark_benchmark: 928.1083,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7567, build_cpu_time: 0.0006, build_memory: 923353956, f_measure: 0.5928, kappa: 0.4908, kb_relative_information_score: 755.873, mean_absolute_error: 0.0884, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.5828, predictive_accuracy: 0.6464, prior_entropy: 2.2353, recall: 0.6464, relative_absolute_error: 0.4836, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.2973, root_relative_squared_error: 0.9857, scimark_benchmark: 947.5974,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8983, build_cpu_time: 0.0018, build_memory: 436749012.8, f_measure: 0.7999, kappa: 0.73, kb_relative_information_score: 1141.9747, mean_absolute_error: 0.0587, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.7969, predictive_accuracy: 0.8042, prior_entropy: 2.2353, recall: 0.8042, relative_absolute_error: 0.3212, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.2057, root_relative_squared_error: 0.6818, scimark_benchmark: 938.2445,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8983, build_cpu_time: 0.0019, build_memory: 550454672.8, f_measure: 0.7999, kappa: 0.73, kb_relative_information_score: 1141.9747, mean_absolute_error: 0.0587, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.7969, predictive_accuracy: 0.8042, prior_entropy: 2.2353, recall: 0.8042, relative_absolute_error: 0.3212, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.2057, root_relative_squared_error: 0.6818, scimark_benchmark: 946.9694,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8243, build_cpu_time: 0.0003, build_memory: 160722539.2, f_measure: 0.67, kappa: 0.6306, kb_relative_information_score: 951.2077, mean_absolute_error: 0.0649, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.7832, predictive_accuracy: 0.7405, prior_entropy: 2.2353, recall: 0.7405, relative_absolute_error: 0.355, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.2547, root_relative_squared_error: 0.8445, scimark_benchmark: 941.5087,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9614, build_cpu_time: 8.8279, build_memory: 17954559.2, f_measure: 0.815, kappa: 0.7496, kb_relative_information_score: 1192.3454, mean_absolute_error: 0.0597, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.812, predictive_accuracy: 0.8185, prior_entropy: 2.2353, recall: 0.8185, relative_absolute_error: 0.3264, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.1781, root_relative_squared_error: 0.5906, scimark_benchmark: 935.4884,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9589, build_cpu_time: 0.7628, build_memory: 929994732, f_measure: 0.7588, kappa: 0.7199, kb_relative_information_score: 210.8374, mean_absolute_error: 0.1899, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.791, predictive_accuracy: 0.8024, prior_entropy: 2.2353, recall: 0.8024, relative_absolute_error: 1.0389, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.2949, root_relative_squared_error: 0.9777, scimark_benchmark: 919.3675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9607, build_cpu_time: 1.4411, build_memory: 473992059.2, f_measure: 0.7755, kappa: 0.7329, kb_relative_information_score: 212.8684, mean_absolute_error: 0.1897, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.7984, predictive_accuracy: 0.8113, prior_entropy: 2.2353, recall: 0.8113, relative_absolute_error: 1.0378, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.2947, root_relative_squared_error: 0.9771, scimark_benchmark: 942.0094,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9611, build_cpu_time: 2.8533, build_memory: 910361952, f_measure: 0.7714, kappa: 0.7278, kb_relative_information_score: 214.9619, mean_absolute_error: 0.1895, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.7874, predictive_accuracy: 0.8077, prior_entropy: 2.2353, recall: 0.8077, relative_absolute_error: 1.0367, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.2945, root_relative_squared_error: 0.9765, scimark_benchmark: 945.8947,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9627, build_cpu_time: 5.2166, build_memory: 1419948460, f_measure: 0.7857, kappa: 0.7418, kb_relative_information_score: 214.137, mean_absolute_error: 0.1896, mean_prior_absolute_error: 0.1828, number_of_instances: 1680, precision: 0.8068, predictive_accuracy: 0.8173, prior_entropy: 2.2353, recall: 0.8173, relative_absolute_error: 1.0373, root_mean_prior_squared_error: 0.3016, root_mean_squared_error: 0.2946, root_relative_squared_error: 0.9767, scimark_benchmark: 945.7067,

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