Task
Supervised Classification on tr31.wc

Supervised Classification on tr31.wc

Task 4225 Supervised Classification tr31.wc 34 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9964, f_measure: 0.9221, kappa: 0.9002, kb_relative_information_score: 5847.317, mean_absolute_error: 0.1104, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.9291, predictive_accuracy: 0.9266, prior_entropy: 2.2393, recall: 0.9266, relative_absolute_error: 0.5146, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.1877, root_relative_squared_error: 0.5735, scimark_benchmark: 1331.6907, usercpu_time_millis: 16870, usercpu_time_millis_testing: 360, usercpu_time_millis_training: 16510,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8014, f_measure: 0.6234, kappa: 0.5317, kb_relative_information_score: 995.036, mean_absolute_error: 0.2142, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.7099, predictive_accuracy: 0.6752, prior_entropy: 2.2393, recall: 0.6752, relative_absolute_error: 0.9986, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.3175, root_relative_squared_error: 0.97, scimark_benchmark: 915.6729, usercpu_time_millis: 24490, usercpu_time_millis_testing: 20000, usercpu_time_millis_training: 4490,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8309, f_measure: 0.4877, kappa: 0.4226, kb_relative_information_score: 172.4767, mean_absolute_error: 0.2294, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.4419, predictive_accuracy: 0.5944, prior_entropy: 2.2393, recall: 0.5944, relative_absolute_error: 1.0697, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.3331, root_relative_squared_error: 1.0179, scimark_benchmark: 1324.8395, usercpu_time_millis: 15810, usercpu_time_millis_training: 15810,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8309, f_measure: 0.4877, kappa: 0.4226, kb_relative_information_score: 172.4767, mean_absolute_error: 0.2294, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.4419, predictive_accuracy: 0.5944, prior_entropy: 2.2393, recall: 0.5944, relative_absolute_error: 1.0697, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.3331, root_relative_squared_error: 1.0179, scimark_benchmark: 1333.5799, usercpu_time_millis: 13940, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 13930,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8309, f_measure: 0.4877, kappa: 0.4226, kb_relative_information_score: 172.4767, mean_absolute_error: 0.2294, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.4419, predictive_accuracy: 0.5944, prior_entropy: 2.2393, recall: 0.5944, relative_absolute_error: 1.0697, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.3331, root_relative_squared_error: 1.0179, scimark_benchmark: 825.5282, usercpu_time_millis: 14310, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 14300,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8309, f_measure: 0.4877, kappa: 0.4226, kb_relative_information_score: 172.4767, mean_absolute_error: 0.2294, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.4419, predictive_accuracy: 0.5944, prior_entropy: 2.2393, recall: 0.5944, relative_absolute_error: 1.0697, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.3331, root_relative_squared_error: 1.0179, scimark_benchmark: 1363.454, usercpu_time_millis: 15420, usercpu_time_millis_training: 15420,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9618, f_measure: 0.9301, kappa: 0.9077, kb_relative_information_score: 8317.4298, mean_absolute_error: 0.0213, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.9295, predictive_accuracy: 0.9309, prior_entropy: 2.2393, recall: 0.9309, relative_absolute_error: 0.0994, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.1355, root_relative_squared_error: 0.4141, scimark_benchmark: 1380.2233, usercpu_time_millis: 30310, usercpu_time_millis_training: 30310,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7265, f_measure: 0.4877, kappa: 0.4226, kb_relative_information_score: 3702.0534, mean_absolute_error: 0.1159, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.4419, predictive_accuracy: 0.5944, prior_entropy: 2.2393, recall: 0.5944, relative_absolute_error: 0.5403, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.3404, root_relative_squared_error: 1.0401, scimark_benchmark: 1466.6185, usercpu_time_millis: 2470, usercpu_time_millis_training: 2470,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9605, f_measure: 0.9314, kappa: 0.9103, kb_relative_information_score: 8278.7428, mean_absolute_error: 0.0204, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.9307, predictive_accuracy: 0.9329, prior_entropy: 2.2393, recall: 0.9329, relative_absolute_error: 0.0951, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.1373, root_relative_squared_error: 0.4194, scimark_benchmark: 1418.5826, usercpu_time_millis: 63330, usercpu_time_millis_training: 63330,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9623, f_measure: 0.9082, kappa: 0.8793, kb_relative_information_score: 1842.4353, mean_absolute_error: 0.2063, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.9079, predictive_accuracy: 0.91, prior_entropy: 2.2393, recall: 0.91, relative_absolute_error: 0.9618, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.3047, root_relative_squared_error: 0.931, scimark_benchmark: 1301.9956, usercpu_time_millis: 2910, usercpu_time_millis_testing: 470, usercpu_time_millis_training: 2440,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9884, f_measure: 0.9809, kappa: 0.9761, kb_relative_information_score: 8934.698, mean_absolute_error: 0.0051, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.9799, predictive_accuracy: 0.9821, prior_entropy: 2.2393, recall: 0.9821, relative_absolute_error: 0.0239, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.0715, root_relative_squared_error: 0.2185, scimark_benchmark: 1337.7959, usercpu_time_millis: 240, usercpu_time_millis_training: 240,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9336, f_measure: 0.9077, kappa: 0.8782, kb_relative_information_score: 7966.4199, mean_absolute_error: 0.0256, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.9154, predictive_accuracy: 0.9104, prior_entropy: 2.2393, recall: 0.9104, relative_absolute_error: 0.1194, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.16, root_relative_squared_error: 0.489, scimark_benchmark: 1330.7266, usercpu_time_millis: 189260, usercpu_time_millis_testing: 96430, usercpu_time_millis_training: 92830,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9961, f_measure: 0.982, kappa: 0.9772, kb_relative_information_score: 8959.8657, mean_absolute_error: 0.0052, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.9814, predictive_accuracy: 0.983, prior_entropy: 2.2393, recall: 0.983, relative_absolute_error: 0.0244, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.064, root_relative_squared_error: 0.1955, scimark_benchmark: 1315.395, usercpu_time_millis: 308120, usercpu_time_millis_testing: 2450, usercpu_time_millis_training: 305670,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9682, f_measure: 0.9122, kappa: 0.885, kb_relative_information_score: 7878.8115, mean_absolute_error: 0.0346, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.9113, predictive_accuracy: 0.9142, prior_entropy: 2.2393, recall: 0.9142, relative_absolute_error: 0.1611, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.1439, root_relative_squared_error: 0.4396, scimark_benchmark: 1315.3881, usercpu_time_millis: 18710, usercpu_time_millis_training: 18710,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9636, f_measure: 0.9324, kappa: 0.911, kb_relative_information_score: 8248.0521, mean_absolute_error: 0.0246, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.9319, predictive_accuracy: 0.9335, prior_entropy: 2.2393, recall: 0.9335, relative_absolute_error: 0.1148, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.1296, root_relative_squared_error: 0.396, scimark_benchmark: 1355.9413, usercpu_time_millis: 149980, usercpu_time_millis_training: 149980,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7649, f_measure: 0.6388, kappa: 0.5188, kb_relative_information_score: 4905.0519, mean_absolute_error: 0.1031, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.6388, predictive_accuracy: 0.6391, prior_entropy: 2.2393, recall: 0.6391, relative_absolute_error: 0.4809, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.3211, root_relative_squared_error: 0.9812, scimark_benchmark: 1301.9956, usercpu_time_millis: 250, usercpu_time_millis_training: 250,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9958, build_cpu_time: 587.7431, build_memory: 747715863.9085, f_measure: 0.9526, kappa: 0.9382, kb_relative_information_score: 8464.5595, mean_absolute_error: 0.0232, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.952, predictive_accuracy: 0.9538, prior_entropy: 2.2393, recall: 0.9538, relative_absolute_error: 0.1083, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.0995, root_relative_squared_error: 0.3041, scimark_benchmark: 892.8519,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9678, f_measure: 0.9502, kappa: 0.9351, kb_relative_information_score: 8527.6417, mean_absolute_error: 0.0138, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.9496, predictive_accuracy: 0.9516, prior_entropy: 2.2393, recall: 0.9516, relative_absolute_error: 0.0645, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.1176, root_relative_squared_error: 0.3594, scimark_benchmark: 1334.8495, usercpu_time_millis: 44730, usercpu_time_millis_testing: 780, usercpu_time_millis_training: 43950,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9915, kappa: 0.9901, kb_relative_information_score: 9065.8744, mean_absolute_error: 0.0032, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.9906, predictive_accuracy: 0.9926, prior_entropy: 2.2393, recall: 0.9926, relative_absolute_error: 0.015, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.0407, root_relative_squared_error: 0.1243, scimark_benchmark: 1276.5165, usercpu_time_millis: 1189600, usercpu_time_millis_training: 1189600,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9632, f_measure: 0.9393, kappa: 0.9206, kb_relative_information_score: 8384.8138, mean_absolute_error: 0.0201, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.9387, predictive_accuracy: 0.9408, prior_entropy: 2.2393, recall: 0.9408, relative_absolute_error: 0.0938, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.1274, root_relative_squared_error: 0.3894, scimark_benchmark: 1386.5717, usercpu_time_millis: 20480, usercpu_time_millis_testing: 630, usercpu_time_millis_training: 19850,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4924, f_measure: 0.209, kb_relative_information_score: 3.7825, mean_absolute_error: 0.2145, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.1442, predictive_accuracy: 0.3797, prior_entropy: 2.2393, recall: 0.3797, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.3273, root_relative_squared_error: 1, scimark_benchmark: 1380.2233,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9495, f_measure: 0.9237, kappa: 0.8995, kb_relative_information_score: 8239.2639, mean_absolute_error: 0.0214, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.9233, predictive_accuracy: 0.925, prior_entropy: 2.2393, recall: 0.925, relative_absolute_error: 0.0999, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.1464, root_relative_squared_error: 0.4472, scimark_benchmark: 1605.6303, usercpu_time_millis: 225980, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 225970,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8309, f_measure: 0.4877, kappa: 0.4226, kb_relative_information_score: 172.4767, mean_absolute_error: 0.2294, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.4419, predictive_accuracy: 0.5944, prior_entropy: 2.2393, recall: 0.5944, relative_absolute_error: 1.0697, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.3331, root_relative_squared_error: 1.0179, scimark_benchmark: 1404.1865, usercpu_time_millis: 14200, usercpu_time_millis_training: 14200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9717, f_measure: 0.9427, kappa: 0.9246, kb_relative_information_score: 8409.6678, mean_absolute_error: 0.0201, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.9422, predictive_accuracy: 0.9436, prior_entropy: 2.2393, recall: 0.9436, relative_absolute_error: 0.0938, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.1213, root_relative_squared_error: 0.3705, scimark_benchmark: 1310.3951, usercpu_time_millis: 139490, usercpu_time_millis_training: 139490,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8392, f_measure: 0.6081, kappa: 0.4923, kb_relative_information_score: 4109.8252, mean_absolute_error: 0.1415, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.6604, predictive_accuracy: 0.6214, prior_entropy: 2.2393, recall: 0.6214, relative_absolute_error: 0.6597, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.2754, root_relative_squared_error: 0.8414, scimark_benchmark: 1363.454, usercpu_time_millis: 8520, usercpu_time_millis_testing: 8520,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8313, f_measure: 0.6338, kappa: 0.5235, kb_relative_information_score: 4462.2763, mean_absolute_error: 0.1288, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.6506, predictive_accuracy: 0.6498, prior_entropy: 2.2393, recall: 0.6498, relative_absolute_error: 0.6005, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.2774, root_relative_squared_error: 0.8476, scimark_benchmark: 934.4732, usercpu_time_millis: 9550, usercpu_time_millis_testing: 9550,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7756, f_measure: 0.4877, kappa: 0.4226, kb_relative_information_score: 3310.4959, mean_absolute_error: 0.1469, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.4419, predictive_accuracy: 0.5944, prior_entropy: 2.2393, recall: 0.5944, relative_absolute_error: 0.6851, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.2711, root_relative_squared_error: 0.8284, scimark_benchmark: 1324.3755, usercpu_time_millis: 4900, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 4890,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9933, f_measure: 0.9425, kappa: 0.925, kb_relative_information_score: 8115.7223, mean_absolute_error: 0.0342, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.9429, predictive_accuracy: 0.9442, prior_entropy: 2.2393, recall: 0.9442, relative_absolute_error: 0.1594, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.1145, root_relative_squared_error: 0.3497, scimark_benchmark: 1318.3541, usercpu_time_millis: 557640, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 557620,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9933, f_measure: 0.945, kappa: 0.9279, kb_relative_information_score: 8309.9388, mean_absolute_error: 0.0263, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.9446, predictive_accuracy: 0.9463, prior_entropy: 2.2393, recall: 0.9463, relative_absolute_error: 0.1224, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.1045, root_relative_squared_error: 0.3192, scimark_benchmark: 1341.468, usercpu_time_millis: 181940, usercpu_time_millis_training: 181940,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8852, f_measure: 0.8178, kappa: 0.7384, kb_relative_information_score: 6854.4136, mean_absolute_error: 0.0575, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.8582, predictive_accuracy: 0.7987, prior_entropy: 2.2393, recall: 0.7987, relative_absolute_error: 0.268, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.2394, root_relative_squared_error: 0.7313, scimark_benchmark: 1358.4523, usercpu_time_millis: 31310, usercpu_time_millis_testing: 26690, usercpu_time_millis_training: 4620,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8771, f_measure: 0.8067, kappa: 0.7192, kb_relative_information_score: 6690.6943, mean_absolute_error: 0.062, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.8543, predictive_accuracy: 0.783, prior_entropy: 2.2393, recall: 0.783, relative_absolute_error: 0.2891, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.2485, root_relative_squared_error: 0.7592, scimark_benchmark: 1341.994, usercpu_time_millis: 41480, usercpu_time_millis_testing: 31190, usercpu_time_millis_training: 10290,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7278, f_measure: 0.7847, kappa: 0.7074, kb_relative_information_score: -200.599, mean_absolute_error: 0.2446, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.863, predictive_accuracy: 0.7949, prior_entropy: 2.2393, recall: 0.7949, relative_absolute_error: 1.1403, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.3494, root_relative_squared_error: 1.0677, scimark_benchmark: 932.0242, usercpu_time_millis: 5160, usercpu_time_millis_testing: 4510, usercpu_time_millis_training: 650,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7905, f_measure: 0.4849, kappa: 0.4153, kb_relative_information_score: 3298.937, mean_absolute_error: 0.1468, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.4443, predictive_accuracy: 0.5884, prior_entropy: 2.2393, recall: 0.5884, relative_absolute_error: 0.6845, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.2718, root_relative_squared_error: 0.8305, scimark_benchmark: 940.0008, usercpu_time_millis: 12010, usercpu_time_millis_training: 12010,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.999, f_measure: 0.9915, kappa: 0.9901, kb_relative_information_score: 9065.8744, mean_absolute_error: 0.0032, mean_prior_absolute_error: 0.2145, number_of_instances: 9270, precision: 0.9906, predictive_accuracy: 0.9926, prior_entropy: 2.2393, recall: 0.9926, relative_absolute_error: 0.015, root_mean_prior_squared_error: 0.3273, root_mean_squared_error: 0.0407, root_relative_squared_error: 0.1243, scimark_benchmark: 1333.5799, usercpu_time_millis: 1202040, usercpu_time_millis_training: 1202040,

    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

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    From your own software

    Use one of our APIs to download data from OpenML and upload your results

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