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

OpenML
Task
Supervised Classification on machine_cpu

Supervised Classification on machine_cpu

Task 3599 Supervised Classification machine_cpu 652 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
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9509, f_measure: 0.9271, kappa: 0.8117, kb_relative_information_score: 161.6415, mean_absolute_error: 0.0816, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9274, predictive_accuracy: 0.9282, prior_entropy: 0.8417, recall: 0.9282, relative_absolute_error: 0.2074, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2244, root_relative_squared_error: 0.5066, scimark_benchmark: 942.9518, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8976, f_measure: 0.9318, kappa: 0.8232, kb_relative_information_score: 169.2522, mean_absolute_error: 0.067, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9325, predictive_accuracy: 0.933, prior_entropy: 0.8417, recall: 0.933, relative_absolute_error: 0.1703, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2588, root_relative_squared_error: 0.5844, scimark_benchmark: 940.3347, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6188, kb_relative_information_score: 52.3583, mean_absolute_error: 0.2679, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.5359, predictive_accuracy: 0.7321, prior_entropy: 0.8417, recall: 0.7321, relative_absolute_error: 0.6812, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.5176, root_relative_squared_error: 1.1688, scimark_benchmark: 1315.395, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8628, f_measure: 0.9197, kappa: 0.7881, kb_relative_information_score: 163.6858, mean_absolute_error: 0.0766, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9279, predictive_accuracy: 0.9234, prior_entropy: 0.8417, recall: 0.9234, relative_absolute_error: 0.1946, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2767, root_relative_squared_error: 0.6247, scimark_benchmark: 1386.5717,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9809, f_measure: 0.9322, kappa: 0.8253, kb_relative_information_score: 160.2276, mean_absolute_error: 0.0923, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9323, predictive_accuracy: 0.933, prior_entropy: 0.8417, recall: 0.933, relative_absolute_error: 0.2347, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2149, root_relative_squared_error: 0.4853, scimark_benchmark: 1335.643, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8617, f_measure: 0.8819, kappa: 0.7035, kb_relative_information_score: 138.6371, mean_absolute_error: 0.1196, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.8846, predictive_accuracy: 0.8804, prior_entropy: 0.8417, recall: 0.8804, relative_absolute_error: 0.3041, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.3459, root_relative_squared_error: 0.7809, scimark_benchmark: 938.343, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9831, f_measure: 0.9419, kappa: 0.8503, kb_relative_information_score: 159.9245, mean_absolute_error: 0.0958, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9421, predictive_accuracy: 0.9426, prior_entropy: 0.8417, recall: 0.9426, relative_absolute_error: 0.2436, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2072, root_relative_squared_error: 0.4677, scimark_benchmark: 935.5075, usercpu_time_millis: 160, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 150,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.586, f_measure: 0.714, kappa: 0.2308, kb_relative_information_score: 77.407, mean_absolute_error: 0.2249, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.8056, predictive_accuracy: 0.7751, prior_entropy: 0.8417, recall: 0.7751, relative_absolute_error: 0.5718, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.4742, root_relative_squared_error: 1.0707, scimark_benchmark: 1363.434, usercpu_time_millis: 30, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.974, f_measure: 0.9376, kappa: 0.8405, kb_relative_information_score: 163.5159, mean_absolute_error: 0.0819, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9375, predictive_accuracy: 0.9378, prior_entropy: 0.8417, recall: 0.9378, relative_absolute_error: 0.2083, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2208, root_relative_squared_error: 0.4985, scimark_benchmark: 1363.434,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9573, f_measure: 0.9426, kappa: 0.8536, kb_relative_information_score: 160.5616, mean_absolute_error: 0.092, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9426, predictive_accuracy: 0.9426, prior_entropy: 0.8417, recall: 0.9426, relative_absolute_error: 0.2339, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2303, root_relative_squared_error: 0.52, scimark_benchmark: 1250.8301, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9723, f_measure: 0.9422, kappa: 0.852, kb_relative_information_score: 159.7147, mean_absolute_error: 0.0907, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9421, predictive_accuracy: 0.9426, prior_entropy: 0.8417, recall: 0.9426, relative_absolute_error: 0.2306, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2181, root_relative_squared_error: 0.4924, scimark_benchmark: 1315.0767, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9179, f_measure: 0.9376, kappa: 0.8405, kb_relative_information_score: 172.0354, mean_absolute_error: 0.0622, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9375, predictive_accuracy: 0.9378, prior_entropy: 0.8417, recall: 0.9378, relative_absolute_error: 0.1581, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2494, root_relative_squared_error: 0.5631, scimark_benchmark: 825.5282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9334, f_measure: 0.9288, kappa: 0.8201, kb_relative_information_score: 146.0903, mean_absolute_error: 0.1243, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9298, predictive_accuracy: 0.9282, prior_entropy: 0.8417, recall: 0.9282, relative_absolute_error: 0.3161, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2589, root_relative_squared_error: 0.5846, scimark_benchmark: 1316.0472,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9271, f_measure: 0.9318, kappa: 0.8232, kb_relative_information_score: 159.8657, mean_absolute_error: 0.0909, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9325, predictive_accuracy: 0.933, prior_entropy: 0.8417, recall: 0.933, relative_absolute_error: 0.2311, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2449, root_relative_squared_error: 0.5529, scimark_benchmark: 1290.1085,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9066, f_measure: 0.9368, kappa: 0.8368, kb_relative_information_score: 172.0354, mean_absolute_error: 0.0622, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9373, predictive_accuracy: 0.9378, prior_entropy: 0.8417, recall: 0.9378, relative_absolute_error: 0.1581, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2494, root_relative_squared_error: 0.5631, scimark_benchmark: 1339.3974,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8295, f_measure: 0.8941, kappa: 0.7201, kb_relative_information_score: 149.7699, mean_absolute_error: 0.1005, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.902, predictive_accuracy: 0.8995, prior_entropy: 0.8417, recall: 0.8995, relative_absolute_error: 0.2555, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.317, root_relative_squared_error: 0.7157, scimark_benchmark: 1319.6463,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9552, f_measure: 0.9318, kappa: 0.8232, kb_relative_information_score: 165.4248, mean_absolute_error: 0.0784, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9325, predictive_accuracy: 0.933, prior_entropy: 0.8417, recall: 0.933, relative_absolute_error: 0.1993, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2383, root_relative_squared_error: 0.5381, scimark_benchmark: 1358.4523,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8528, f_measure: 0.8769, kappa: 0.6899, kb_relative_information_score: 135.8539, mean_absolute_error: 0.1244, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.879, predictive_accuracy: 0.8756, prior_entropy: 0.8417, recall: 0.8756, relative_absolute_error: 0.3163, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.3527, root_relative_squared_error: 0.7964, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8732, f_measure: 0.9123, kappa: 0.7727, kb_relative_information_score: 158.1194, mean_absolute_error: 0.0861, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9126, predictive_accuracy: 0.9139, prior_entropy: 0.8417, recall: 0.9139, relative_absolute_error: 0.219, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2935, root_relative_squared_error: 0.6626, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4718, f_measure: 0.6188, kb_relative_information_score: -0.6521, mean_absolute_error: 0.3935, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.5359, predictive_accuracy: 0.7321, prior_entropy: 0.8417, recall: 0.7321, relative_absolute_error: 1.0005, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.443, root_relative_squared_error: 1.0003, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9063, f_measure: 0.9469, kappa: 0.8635, kb_relative_information_score: 167.4791, mean_absolute_error: 0.0799, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9469, predictive_accuracy: 0.9474, prior_entropy: 0.8417, recall: 0.9474, relative_absolute_error: 0.203, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2231, root_relative_squared_error: 0.5038, scimark_benchmark: 1605.6303,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.936, f_measure: 0.9432, kappa: 0.8569, kb_relative_information_score: 171.2826, mean_absolute_error: 0.0662, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9446, predictive_accuracy: 0.9426, prior_entropy: 0.8417, recall: 0.9426, relative_absolute_error: 0.1684, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2408, root_relative_squared_error: 0.5437, 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: 0.9216, f_measure: 0.9429, kappa: 0.8553, kb_relative_information_score: 169.3336, mean_absolute_error: 0.0725, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9434, predictive_accuracy: 0.9426, prior_entropy: 0.8417, recall: 0.9426, relative_absolute_error: 0.1844, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2342, root_relative_squared_error: 0.5288, scimark_benchmark: 932.3943,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9306, f_measure: 0.9429, kappa: 0.8553, kb_relative_information_score: 169.3524, mean_absolute_error: 0.0724, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9434, predictive_accuracy: 0.9426, prior_entropy: 0.8417, recall: 0.9426, relative_absolute_error: 0.1841, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2271, root_relative_squared_error: 0.5128, scimark_benchmark: 941.7954, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9306, f_measure: 0.9429, kappa: 0.8553, kb_relative_information_score: 169.3524, mean_absolute_error: 0.0724, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9434, predictive_accuracy: 0.9426, prior_entropy: 0.8417, recall: 0.9426, relative_absolute_error: 0.1841, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2271, root_relative_squared_error: 0.5128, scimark_benchmark: 923.7642, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9306, f_measure: 0.9429, kappa: 0.8553, kb_relative_information_score: 169.3524, mean_absolute_error: 0.0724, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9434, predictive_accuracy: 0.9426, prior_entropy: 0.8417, recall: 0.9426, relative_absolute_error: 0.1841, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2271, root_relative_squared_error: 0.5128, scimark_benchmark: 894.7455,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9719, f_measure: 0.9239, kappa: 0.807, kb_relative_information_score: 165.7508, mean_absolute_error: 0.0719, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9245, predictive_accuracy: 0.9234, prior_entropy: 0.8417, recall: 0.9234, relative_absolute_error: 0.1827, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.255, root_relative_squared_error: 0.5758, scimark_benchmark: 936.7115, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9706, f_measure: 0.9372, kappa: 0.8387, kb_relative_information_score: 170.7404, mean_absolute_error: 0.0653, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9372, predictive_accuracy: 0.9378, prior_entropy: 0.8417, recall: 0.9378, relative_absolute_error: 0.166, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2393, root_relative_squared_error: 0.5404, scimark_benchmark: 936.6206, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9684, f_measure: 0.9288, kappa: 0.8201, kb_relative_information_score: 166.0787, mean_absolute_error: 0.0726, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9298, predictive_accuracy: 0.9282, prior_entropy: 0.8417, recall: 0.9282, relative_absolute_error: 0.1845, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.253, root_relative_squared_error: 0.5713, scimark_benchmark: 942.1229, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9751, f_measure: 0.933, kappa: 0.8292, kb_relative_information_score: 168.2302, mean_absolute_error: 0.0702, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.933, predictive_accuracy: 0.933, prior_entropy: 0.8417, recall: 0.933, relative_absolute_error: 0.1786, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2433, root_relative_squared_error: 0.5493, scimark_benchmark: 922.9039, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9664, f_measure: 0.9292, kappa: 0.8221, kb_relative_information_score: 164.052, mean_absolute_error: 0.0774, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9313, predictive_accuracy: 0.9282, prior_entropy: 0.8417, recall: 0.9282, relative_absolute_error: 0.1969, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2577, root_relative_squared_error: 0.5818, scimark_benchmark: 938.9865, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9702, f_measure: 0.9234, kappa: 0.8049, kb_relative_information_score: 162.3229, mean_absolute_error: 0.0787, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9234, predictive_accuracy: 0.9234, prior_entropy: 0.8417, recall: 0.9234, relative_absolute_error: 0.2001, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2581, root_relative_squared_error: 0.5827, scimark_benchmark: 936.6206, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9664, f_measure: 0.9239, kappa: 0.807, kb_relative_information_score: 165.2937, mean_absolute_error: 0.0743, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9245, predictive_accuracy: 0.9234, prior_entropy: 0.8417, recall: 0.9234, relative_absolute_error: 0.1889, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2425, root_relative_squared_error: 0.5475, scimark_benchmark: 924.6116, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9603, build_cpu_time: 0.5145, build_memory: 1325316140.6316, f_measure: 0.9472, kappa: 0.8651, kb_relative_information_score: 177.8643, mean_absolute_error: 0.0525, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9471, predictive_accuracy: 0.9474, prior_entropy: 0.8417, recall: 0.9474, relative_absolute_error: 0.1334, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2223, root_relative_squared_error: 0.5018, scimark_benchmark: 874.7324,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9551, build_cpu_time: 0.147, build_memory: 1165238874.3349, f_measure: 0.9426, kappa: 0.8536, kb_relative_information_score: 174.0782, mean_absolute_error: 0.0586, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9426, predictive_accuracy: 0.9426, prior_entropy: 0.8417, recall: 0.9426, relative_absolute_error: 0.1491, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2291, root_relative_squared_error: 0.5173, scimark_benchmark: 924.2473,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9558, build_cpu_time: 0.1677, build_memory: 197265580.7847, f_measure: 0.9426, kappa: 0.8536, kb_relative_information_score: 175.8993, mean_absolute_error: 0.0556, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9426, predictive_accuracy: 0.9426, prior_entropy: 0.8417, recall: 0.9426, relative_absolute_error: 0.1415, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2249, root_relative_squared_error: 0.5079, scimark_benchmark: 942.5053,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9562, build_cpu_time: 0.4336, build_memory: 637137257.1866, f_measure: 0.9426, kappa: 0.8536, kb_relative_information_score: 175.1502, mean_absolute_error: 0.0569, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9426, predictive_accuracy: 0.9426, prior_entropy: 0.8417, recall: 0.9426, relative_absolute_error: 0.1447, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.228, root_relative_squared_error: 0.5147, scimark_benchmark: 893.4088,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9586, build_cpu_time: 0.0249, build_memory: 1372724944.1148, f_measure: 0.9475, kappa: 0.8666, kb_relative_information_score: 176.6948, mean_absolute_error: 0.055, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9477, predictive_accuracy: 0.9474, prior_entropy: 0.8417, recall: 0.9474, relative_absolute_error: 0.1397, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2272, root_relative_squared_error: 0.513, scimark_benchmark: 933.4498,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9586, build_cpu_time: 0.036, build_memory: 1290309385.6842, f_measure: 0.9475, kappa: 0.8666, kb_relative_information_score: 176.6948, mean_absolute_error: 0.055, mean_prior_absolute_error: 0.3933, number_of_instances: 209, precision: 0.9477, predictive_accuracy: 0.9474, prior_entropy: 0.8417, recall: 0.9474, relative_absolute_error: 0.1397, root_mean_prior_squared_error: 0.4429, root_mean_squared_error: 0.2272, root_relative_squared_error: 0.513, scimark_benchmark: 917.4547,

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