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Backtrace:

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

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

OpenML
Task
Supervised Classification on breast-w

Supervised Classification on breast-w

Task 15 Supervised Classification breast-w 24605 runs submitted
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Visibility: Public
  • at2 basic mythbusting mythbusting_1 OpenML-CC18 OpenML100 study_1 study_107 study_123 study_14 study_15 study_20 study_41 study_50 study_70 study_98 study_99 under100k under1m
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24605 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9829, build_cpu_time: 0.175, build_memory: 456454827.9027, f_measure: 0.9544, kappa: 0.8995, kb_relative_information_score: 625.9321, mean_absolute_error: 0.0448, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9548, predictive_accuracy: 0.9542, prior_entropy: 0.9297, recall: 0.9542, relative_absolute_error: 0.0992, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2073, root_relative_squared_error: 0.4361, scimark_benchmark: 945.0532,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9876, build_cpu_time: 0.1195, build_memory: 402520394.3348, f_measure: 0.9601, kappa: 0.912, kb_relative_information_score: 633.6341, mean_absolute_error: 0.0403, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9605, predictive_accuracy: 0.9599, prior_entropy: 0.9297, recall: 0.9599, relative_absolute_error: 0.0891, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1909, root_relative_squared_error: 0.4017, scimark_benchmark: 935.6292,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9778, build_cpu_time: 0.0681, build_memory: 1504826324.0172, f_measure: 0.9657, kappa: 0.9242, kb_relative_information_score: 642.4995, mean_absolute_error: 0.0351, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9657, predictive_accuracy: 0.9657, prior_entropy: 0.9297, recall: 0.9657, relative_absolute_error: 0.0776, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1822, root_relative_squared_error: 0.3833, scimark_benchmark: 917.4547,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9705, build_cpu_time: 0.1462, build_memory: 74539586.1745, f_measure: 0.96, kappa: 0.9115, kb_relative_information_score: 636.1561, mean_absolute_error: 0.0386, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.96, predictive_accuracy: 0.9599, prior_entropy: 0.9297, recall: 0.9599, relative_absolute_error: 0.0853, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1937, root_relative_squared_error: 0.4076, scimark_benchmark: 934.6076,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9698, build_cpu_time: 0.2908, build_memory: 710427876.5322, f_measure: 0.9658, kappa: 0.9245, kb_relative_information_score: 643.206, mean_absolute_error: 0.0344, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.966, predictive_accuracy: 0.9657, prior_entropy: 0.9297, recall: 0.9657, relative_absolute_error: 0.0762, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1853, root_relative_squared_error: 0.3898, scimark_benchmark: 923.9118,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9669, build_cpu_time: 0.5664, build_memory: 851124456.0114, f_measure: 0.9643, kappa: 0.9212, kb_relative_information_score: 641.2158, mean_absolute_error: 0.0356, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9645, predictive_accuracy: 0.9642, prior_entropy: 0.9297, recall: 0.9642, relative_absolute_error: 0.0787, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1882, root_relative_squared_error: 0.396, scimark_benchmark: 908.2898,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.969, build_cpu_time: 1.0073, build_memory: 487568092.4063, f_measure: 0.9658, kappa: 0.9246, kb_relative_information_score: 643.9055, mean_absolute_error: 0.0338, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9662, predictive_accuracy: 0.9657, prior_entropy: 0.9297, recall: 0.9657, relative_absolute_error: 0.0749, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1829, root_relative_squared_error: 0.3848, scimark_benchmark: 916.1588,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9766, build_cpu_time: 0.1902, build_memory: 1105089454.0773, f_measure: 0.957, kappa: 0.9048, kb_relative_information_score: 632.2789, mean_absolute_error: 0.0416, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.957, predictive_accuracy: 0.9571, prior_entropy: 0.9297, recall: 0.9571, relative_absolute_error: 0.092, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.199, root_relative_squared_error: 0.4186, scimark_benchmark: 945.0532,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9906, build_cpu_time: 0.0949, build_memory: 647286827.9714, f_measure: 0.9557, kappa: 0.9019, kb_relative_information_score: 623.6732, mean_absolute_error: 0.0477, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9557, predictive_accuracy: 0.9557, prior_entropy: 0.9297, recall: 0.9557, relative_absolute_error: 0.1055, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.188, root_relative_squared_error: 0.3955, scimark_benchmark: 945.0554,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9911, build_cpu_time: 0.2528, build_memory: 68364909.3677, f_measure: 0.9557, kappa: 0.9019, kb_relative_information_score: 626.9383, mean_absolute_error: 0.0454, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9557, predictive_accuracy: 0.9557, prior_entropy: 0.9297, recall: 0.9557, relative_absolute_error: 0.1004, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1888, root_relative_squared_error: 0.3972, scimark_benchmark: 939.0159,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9658, build_cpu_time: 2.1445, build_memory: 431604059.4678, f_measure: 0.9643, kappa: 0.9211, kb_relative_information_score: 641.1122, mean_absolute_error: 0.0357, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9644, predictive_accuracy: 0.9642, prior_entropy: 0.9297, recall: 0.9642, relative_absolute_error: 0.0789, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1885, root_relative_squared_error: 0.3967, scimark_benchmark: 923.019,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9727, build_cpu_time: 1.0348, build_memory: 1009981913.1216, f_measure: 0.9657, kappa: 0.9242, kb_relative_information_score: 642.7937, mean_absolute_error: 0.0347, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9657, predictive_accuracy: 0.9657, prior_entropy: 0.9297, recall: 0.9657, relative_absolute_error: 0.0768, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1844, root_relative_squared_error: 0.388, scimark_benchmark: 926.786,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9722, build_cpu_time: 0.6298, build_memory: 192029064.1373, f_measure: 0.9614, kappa: 0.9144, kb_relative_information_score: 637.7377, mean_absolute_error: 0.0379, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9613, predictive_accuracy: 0.9614, prior_entropy: 0.9297, recall: 0.9614, relative_absolute_error: 0.0838, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1909, root_relative_squared_error: 0.4016, scimark_benchmark: 908.1651,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9809, build_cpu_time: 0.3632, build_memory: 717749172.4063, f_measure: 0.9614, kappa: 0.9148, kb_relative_information_score: 635.1061, mean_absolute_error: 0.0397, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9615, predictive_accuracy: 0.9614, prior_entropy: 0.9297, recall: 0.9614, relative_absolute_error: 0.0878, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1938, root_relative_squared_error: 0.4078, scimark_benchmark: 913.4921,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9859, build_cpu_time: 0.3246, build_memory: 321277625.5222, f_measure: 0.9643, kappa: 0.9211, kb_relative_information_score: 640.3206, mean_absolute_error: 0.0362, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9644, predictive_accuracy: 0.9642, prior_entropy: 0.9297, recall: 0.9642, relative_absolute_error: 0.0802, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1855, root_relative_squared_error: 0.3903, scimark_benchmark: 945.7844,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9882, build_cpu_time: 0.006, build_memory: 887761024.5951, f_measure: 0.9715, kappa: 0.937, kb_relative_information_score: 642.0291, mean_absolute_error: 0.037, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9717, predictive_accuracy: 0.9714, prior_entropy: 0.9297, recall: 0.9714, relative_absolute_error: 0.0818, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1596, root_relative_squared_error: 0.3359, scimark_benchmark: 942.4411,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9917, build_cpu_time: 0.1285, build_memory: 880789539.9485, f_measure: 0.97, kappa: 0.9338, kb_relative_information_score: 611.8371, mean_absolute_error: 0.061, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9702, predictive_accuracy: 0.97, prior_entropy: 0.9297, recall: 0.97, relative_absolute_error: 0.1349, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1652, root_relative_squared_error: 0.3476, scimark_benchmark: 946.9374,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9661, build_cpu_time: 0.0365, build_memory: 219840548.2461, f_measure: 0.9516, kappa: 0.8936, kb_relative_information_score: 605.1372, mean_absolute_error: 0.0623, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9525, predictive_accuracy: 0.9514, prior_entropy: 0.9297, recall: 0.9514, relative_absolute_error: 0.1378, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2058, root_relative_squared_error: 0.4331, scimark_benchmark: 943.1817,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9766, build_cpu_time: 0.0002, build_memory: 398583731.0443, f_measure: 0.957, kappa: 0.9048, kb_relative_information_score: 632.2789, mean_absolute_error: 0.0416, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.957, predictive_accuracy: 0.9571, prior_entropy: 0.9297, recall: 0.9571, relative_absolute_error: 0.092, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.199, root_relative_squared_error: 0.4186, scimark_benchmark: 943.1817,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9527, build_cpu_time: 0.0912, build_memory: 1332704364.269, f_measure: 0.9598, kappa: 0.9108, kb_relative_information_score: 634.0831, mean_absolute_error: 0.0401, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9599, predictive_accuracy: 0.9599, prior_entropy: 0.9297, recall: 0.9599, relative_absolute_error: 0.0886, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2001, root_relative_squared_error: 0.4211, scimark_benchmark: 915.7861,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9897, build_cpu_time: 0.0442, build_memory: 607807619.1931, f_measure: 0.9545, kappa: 0.8999, kb_relative_information_score: 546.8982, mean_absolute_error: 0.1113, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9553, predictive_accuracy: 0.9542, prior_entropy: 0.9297, recall: 0.9542, relative_absolute_error: 0.2462, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1964, root_relative_squared_error: 0.4133, scimark_benchmark: 1225.9989,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9915, build_cpu_time: 2.0958, build_memory: 1352485367.0615, f_measure: 0.96, kappa: 0.9115, kb_relative_information_score: 615.9436, mean_absolute_error: 0.0557, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.96, predictive_accuracy: 0.9599, prior_entropy: 0.9297, recall: 0.9599, relative_absolute_error: 0.1233, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1715, root_relative_squared_error: 0.3608, scimark_benchmark: 942.3742,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9923, build_cpu_time: 5.9489, build_memory: 724751120.9957, f_measure: 0.96, kappa: 0.9117, kb_relative_information_score: 615.4065, mean_absolute_error: 0.0561, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9602, predictive_accuracy: 0.9599, prior_entropy: 0.9297, recall: 0.9599, relative_absolute_error: 0.1241, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1691, root_relative_squared_error: 0.3559, scimark_benchmark: 824.2652,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9925, build_cpu_time: 9.169, build_memory: 91512437.4478, f_measure: 0.9614, kappa: 0.9146, kb_relative_information_score: 617.466, mean_absolute_error: 0.0554, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9614, predictive_accuracy: 0.9614, prior_entropy: 0.9297, recall: 0.9614, relative_absolute_error: 0.1225, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1659, root_relative_squared_error: 0.3491, scimark_benchmark: 938.4414,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9904, f_measure: 0.9686, kappa: 0.9307, kb_relative_information_score: 0.8877, mean_absolute_error: 0.0546, mean_prior_absolute_error: 0.4519, number_of_instances: 699, precision: 0.9689, predictive_accuracy: 0.9685, prior_entropy: 0.9293, recall: 0.9685, relative_absolute_error: 0.1208, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1603, root_relative_squared_error: 0.3372,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9904, f_measure: 0.9686, kappa: 0.9307, kb_relative_information_score: 0.8877, mean_absolute_error: 0.0546, mean_prior_absolute_error: 0.4519, number_of_instances: 699, precision: 0.9689, predictive_accuracy: 0.9685, prior_entropy: 0.9293, recall: 0.9685, relative_absolute_error: 0.1208, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1603, root_relative_squared_error: 0.3372,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9927, build_cpu_time: 17.5123, build_memory: 838794932.99, f_measure: 0.96, kappa: 0.9115, kb_relative_information_score: 618.6498, mean_absolute_error: 0.0547, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.96, predictive_accuracy: 0.9599, prior_entropy: 0.9297, recall: 0.9599, relative_absolute_error: 0.121, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1637, root_relative_squared_error: 0.3443, scimark_benchmark: 935.2997,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9798, build_cpu_time: 0.0006, build_memory: 475403160.1373, f_measure: 0.9616, kappa: 0.9158, kb_relative_information_score: 636.2096, mean_absolute_error: 0.0388, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9628, predictive_accuracy: 0.9614, prior_entropy: 0.9297, recall: 0.9614, relative_absolute_error: 0.0858, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1951, root_relative_squared_error: 0.4104, scimark_benchmark: 1469.6837,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9926, build_cpu_time: 33.2735, build_memory: 2243620398.5579, f_measure: 0.9628, kappa: 0.9178, kb_relative_information_score: 619.6358, mean_absolute_error: 0.0542, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9629, predictive_accuracy: 0.9628, prior_entropy: 0.9297, recall: 0.9628, relative_absolute_error: 0.12, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1632, root_relative_squared_error: 0.3433, scimark_benchmark: 939.7104,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9657, build_cpu_time: 1.58, build_memory: 802885616.5379, f_measure: 0.9643, kappa: 0.9212, kb_relative_information_score: 640.6293, mean_absolute_error: 0.0361, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9645, predictive_accuracy: 0.9642, prior_entropy: 0.9297, recall: 0.9642, relative_absolute_error: 0.0798, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1893, root_relative_squared_error: 0.3982, scimark_benchmark: 945.8914,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9734, build_cpu_time: 0.8996, build_memory: 78390658.9185, f_measure: 0.9643, kappa: 0.9212, kb_relative_information_score: 640.6087, mean_absolute_error: 0.0361, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9645, predictive_accuracy: 0.9642, prior_entropy: 0.9297, recall: 0.9642, relative_absolute_error: 0.0798, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1893, root_relative_squared_error: 0.3983, scimark_benchmark: 947.8147,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9734, build_cpu_time: 0.8937, build_memory: 1441675368.618, f_measure: 0.9643, kappa: 0.9212, kb_relative_information_score: 640.6087, mean_absolute_error: 0.0361, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9645, predictive_accuracy: 0.9642, prior_entropy: 0.9297, recall: 0.9642, relative_absolute_error: 0.0798, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1893, root_relative_squared_error: 0.3983, scimark_benchmark: 942.9632,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9734, build_cpu_time: 0.8233, build_memory: 43346258.804, f_measure: 0.9643, kappa: 0.9212, kb_relative_information_score: 640.6087, mean_absolute_error: 0.0361, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9645, predictive_accuracy: 0.9642, prior_entropy: 0.9297, recall: 0.9642, relative_absolute_error: 0.0798, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1893, root_relative_squared_error: 0.3983, scimark_benchmark: 935.2997,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9734, build_cpu_time: 0.8174, build_memory: 40448461.2074, f_measure: 0.9643, kappa: 0.9212, kb_relative_information_score: 640.6087, mean_absolute_error: 0.0361, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9645, predictive_accuracy: 0.9642, prior_entropy: 0.9297, recall: 0.9642, relative_absolute_error: 0.0798, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1893, root_relative_squared_error: 0.3983, scimark_benchmark: 939.6491,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9763, build_cpu_time: 0.5388, build_memory: 62449115.0443, f_measure: 0.9628, kappa: 0.9178, kb_relative_information_score: 638.1637, mean_absolute_error: 0.0376, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9629, predictive_accuracy: 0.9628, prior_entropy: 0.9297, recall: 0.9628, relative_absolute_error: 0.0832, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1901, root_relative_squared_error: 0.4, scimark_benchmark: 942.9632,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9922, build_cpu_time: 1.1046, build_memory: 1104856763.3763, f_measure: 0.9686, kappa: 0.9309, kb_relative_information_score: 614.5345, mean_absolute_error: 0.0589, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.969, predictive_accuracy: 0.9685, prior_entropy: 0.9297, recall: 0.9685, relative_absolute_error: 0.1303, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1657, root_relative_squared_error: 0.3487, scimark_benchmark: 936.4194,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9925, build_cpu_time: 2.3497, build_memory: 3321981462.6266, f_measure: 0.9701, kappa: 0.934, kb_relative_information_score: 615.9719, mean_absolute_error: 0.058, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9704, predictive_accuracy: 0.97, prior_entropy: 0.9297, recall: 0.97, relative_absolute_error: 0.1283, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1635, root_relative_squared_error: 0.3439, scimark_benchmark: 937.0592,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9908, build_cpu_time: 0.48, build_memory: 1185482006.5007, f_measure: 0.9671, kappa: 0.9274, kb_relative_information_score: 607.3839, mean_absolute_error: 0.0639, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9672, predictive_accuracy: 0.9671, prior_entropy: 0.9297, recall: 0.9671, relative_absolute_error: 0.1414, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.171, root_relative_squared_error: 0.3597, scimark_benchmark: 934.3351,

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