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OpenML
Task
Supervised Classification on letter

Supervised Classification on letter

Task 3840 Supervised Classification letter 434 runs submitted
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Visibility: Public
  • mythbusting_1 study_1 study_107 study_15 study_20 study_41 study_7 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.998, f_measure: 0.9985, kappa: 0.9812, kb_relative_information_score: 18932.8058, mean_absolute_error: 0.0024, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9985, predictive_accuracy: 0.9986, prior_entropy: 0.2455, recall: 0.9986, relative_absolute_error: 0.0309, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.0347, root_relative_squared_error: 0.176, scimark_benchmark: 1324.8395, usercpu_time_millis: 44580, usercpu_time_millis_testing: 44580,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.9394, kb_relative_information_score: 4486.5698, mean_absolute_error: 0.0407, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9204, predictive_accuracy: 0.9594, prior_entropy: 0.2455, recall: 0.9594, relative_absolute_error: 0.5209, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.2016, root_relative_squared_error: 1.021, scimark_benchmark: 1442.7264, usercpu_time_millis: 1370, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 1350,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.9394, kb_relative_information_score: 4486.5698, mean_absolute_error: 0.0407, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9204, predictive_accuracy: 0.9594, prior_entropy: 0.2455, recall: 0.9594, relative_absolute_error: 0.5209, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.2016, root_relative_squared_error: 1.021, scimark_benchmark: 1336.3256, usercpu_time_millis: 85590, usercpu_time_millis_testing: 7680, usercpu_time_millis_training: 77910,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.653, f_measure: 0.9643, kappa: 0.4562, kb_relative_information_score: 9137.3867, mean_absolute_error: 0.0285, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9718, predictive_accuracy: 0.9716, prior_entropy: 0.2455, recall: 0.9716, relative_absolute_error: 0.3646, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.1687, root_relative_squared_error: 0.8541, scimark_benchmark: 1333.5799, usercpu_time_millis: 920, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 900,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9648, f_measure: 0.9735, kappa: 0.6209, kb_relative_information_score: 793.7549, mean_absolute_error: 0.0392, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9749, predictive_accuracy: 0.9767, prior_entropy: 0.2455, recall: 0.9767, relative_absolute_error: 0.5028, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.1368, root_relative_squared_error: 0.6929, scimark_benchmark: 887.6719, usercpu_time_millis: 9880, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 9850,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7558, f_measure: 0.9664, kappa: 0.5527, kb_relative_information_score: 7669.7109, mean_absolute_error: 0.0323, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9654, predictive_accuracy: 0.9677, prior_entropy: 0.2455, recall: 0.9677, relative_absolute_error: 0.4139, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.1797, root_relative_squared_error: 0.9101, scimark_benchmark: 940.3347, usercpu_time_millis: 2150, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 2130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9778, f_measure: 0.998, kappa: 0.9739, kb_relative_information_score: 19220.5103, mean_absolute_error: 0.002, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.998, predictive_accuracy: 0.998, prior_entropy: 0.2455, recall: 0.998, relative_absolute_error: 0.0256, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.0447, root_relative_squared_error: 0.2265, scimark_benchmark: 1368.9272, usercpu_time_millis: 51870, usercpu_time_millis_testing: 7120, usercpu_time_millis_training: 44750,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9774, f_measure: 0.9805, kappa: 0.7421, kb_relative_information_score: 9354.0148, mean_absolute_error: 0.0236, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9802, predictive_accuracy: 0.9812, prior_entropy: 0.2455, recall: 0.9812, relative_absolute_error: 0.3029, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.1265, root_relative_squared_error: 0.6407, scimark_benchmark: 934.0566, usercpu_time_millis: 240, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 180,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9966, f_measure: 0.9892, kappa: 0.8583, kb_relative_information_score: 12160.0445, mean_absolute_error: 0.017, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9892, predictive_accuracy: 0.9896, prior_entropy: 0.2455, recall: 0.9896, relative_absolute_error: 0.2176, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.0888, root_relative_squared_error: 0.4498, scimark_benchmark: 918.6491, usercpu_time_millis: 1010, usercpu_time_millis_testing: 780, usercpu_time_millis_training: 230,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9942, f_measure: 0.9853, kappa: 0.8052, kb_relative_information_score: 10896.2509, mean_absolute_error: 0.0196, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9852, predictive_accuracy: 0.9859, prior_entropy: 0.2455, recall: 0.9859, relative_absolute_error: 0.2515, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.0996, root_relative_squared_error: 0.5043, scimark_benchmark: 1350.9691, usercpu_time_millis: 190, usercpu_time_millis_testing: 90, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9998, f_measure: 0.9963, kappa: 0.952, kb_relative_information_score: 16318.8643, mean_absolute_error: 0.0096, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9964, predictive_accuracy: 0.9964, prior_entropy: 0.2455, recall: 0.9964, relative_absolute_error: 0.1231, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.0525, root_relative_squared_error: 0.2657, scimark_benchmark: 1291.6995, usercpu_time_millis: 4690, usercpu_time_millis_testing: 480, usercpu_time_millis_training: 4210,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9483, f_measure: 0.9924, kappa: 0.902, kb_relative_information_score: 17085.7091, mean_absolute_error: 0.0076, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9924, predictive_accuracy: 0.9924, prior_entropy: 0.2455, recall: 0.9924, relative_absolute_error: 0.0974, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.0872, root_relative_squared_error: 0.4415, scimark_benchmark: 1321.527, usercpu_time_millis: 100, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9814, f_measure: 0.9915, kappa: 0.8892, kb_relative_information_score: 14700.611, mean_absolute_error: 0.0127, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9914, predictive_accuracy: 0.9916, prior_entropy: 0.2455, recall: 0.9916, relative_absolute_error: 0.1634, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.0858, root_relative_squared_error: 0.4344, scimark_benchmark: 1073.494, usercpu_time_millis: 250, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 240,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9765, f_measure: 0.9932, kappa: 0.9123, kb_relative_information_score: 16666.5593, mean_absolute_error: 0.0095, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9932, predictive_accuracy: 0.9933, prior_entropy: 0.2455, recall: 0.9933, relative_absolute_error: 0.1214, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.0807, root_relative_squared_error: 0.4086, scimark_benchmark: 1309.3173, usercpu_time_millis: 2750, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 2730,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9198, f_measure: 0.9917, kappa: 0.8905, kb_relative_information_score: 16914.1625, mean_absolute_error: 0.0081, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9918, predictive_accuracy: 0.992, prior_entropy: 0.2455, recall: 0.992, relative_absolute_error: 0.1032, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.0897, root_relative_squared_error: 0.4543, scimark_benchmark: 1372.2145, usercpu_time_millis: 28640, usercpu_time_millis_testing: 11660, usercpu_time_millis_training: 16980,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7852, f_measure: 0.7455, kappa: 0.1099, kb_relative_information_score: -117311.463, mean_absolute_error: 0.3602, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9596, predictive_accuracy: 0.6399, prior_entropy: 0.2455, recall: 0.6399, relative_absolute_error: 4.6151, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.6001, root_relative_squared_error: 3.0389, scimark_benchmark: 1363.454, usercpu_time_millis: 97070, usercpu_time_millis_testing: 10240, usercpu_time_millis_training: 86830,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9738, f_measure: 0.9942, kappa: 0.9262, kb_relative_information_score: 17684.5453, mean_absolute_error: 0.0063, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9942, predictive_accuracy: 0.9943, prior_entropy: 0.2455, recall: 0.9943, relative_absolute_error: 0.0811, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.0728, root_relative_squared_error: 0.3685, scimark_benchmark: 1392.1129, usercpu_time_millis: 700, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 680,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5123, f_measure: 0.9419, kappa: 0.0462, kb_relative_information_score: 4867.7843, mean_absolute_error: 0.0397, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9619, predictive_accuracy: 0.9604, prior_entropy: 0.2455, recall: 0.9604, relative_absolute_error: 0.5081, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.1991, root_relative_squared_error: 1.0083, scimark_benchmark: 1465.2979, usercpu_time_millis: 90, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9499, f_measure: 0.992, kappa: 0.8971, kb_relative_information_score: 16914.1625, mean_absolute_error: 0.0081, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.992, predictive_accuracy: 0.992, prior_entropy: 0.2455, recall: 0.992, relative_absolute_error: 0.1032, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.0897, root_relative_squared_error: 0.4543, scimark_benchmark: 1353.5686, usercpu_time_millis: 880, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 870,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4987, f_measure: 0.9394, kb_relative_information_score: -39.8507, mean_absolute_error: 0.078, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9204, predictive_accuracy: 0.9594, prior_entropy: 0.2455, recall: 0.9594, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.1975, root_relative_squared_error: 1, scimark_benchmark: 1503.3362, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9856, f_measure: 0.9952, kappa: 0.9377, kb_relative_information_score: 17788.4535, mean_absolute_error: 0.0063, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9952, predictive_accuracy: 0.9952, prior_entropy: 0.2455, recall: 0.9952, relative_absolute_error: 0.0802, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.0677, root_relative_squared_error: 0.3429, scimark_benchmark: 1501.4698, usercpu_time_millis: 370, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 360,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9494, f_measure: 0.9728, kappa: 0.6421, kb_relative_information_score: 9931.5795, mean_absolute_error: 0.0265, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9723, predictive_accuracy: 0.9735, prior_entropy: 0.2455, recall: 0.9735, relative_absolute_error: 0.3395, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.1615, root_relative_squared_error: 0.8177, scimark_benchmark: 931.2336, usercpu_time_millis: 4130, usercpu_time_millis_testing: 1270, usercpu_time_millis_training: 2860,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9636, f_measure: 0.9775, kappa: 0.7094, kb_relative_information_score: 11190.3336, mean_absolute_error: 0.022, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9773, predictive_accuracy: 0.9776, prior_entropy: 0.2455, recall: 0.9776, relative_absolute_error: 0.2817, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.1398, root_relative_squared_error: 0.7077, scimark_benchmark: 876.8277, usercpu_time_millis: 18890, usercpu_time_millis_testing: 5190, usercpu_time_millis_training: 13700,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9838, f_measure: 0.9794, kappa: 0.7339, kb_relative_information_score: 8000.0084, mean_absolute_error: 0.0268, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9793, predictive_accuracy: 0.9796, prior_entropy: 0.2455, recall: 0.9796, relative_absolute_error: 0.3439, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.1277, root_relative_squared_error: 0.6469, scimark_benchmark: 923.7642, usercpu_time_millis: 11120, usercpu_time_millis_testing: 2910, usercpu_time_millis_training: 8210,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9845, f_measure: 0.9791, kappa: 0.7303, kb_relative_information_score: 7699.0548, mean_absolute_error: 0.0275, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.979, predictive_accuracy: 0.9793, prior_entropy: 0.2455, recall: 0.9793, relative_absolute_error: 0.3518, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.128, root_relative_squared_error: 0.6481, scimark_benchmark: 894.7455, usercpu_time_millis: 10820, usercpu_time_millis_testing: 2940, usercpu_time_millis_training: 7880,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.982, f_measure: 0.9533, kappa: 0.2596, kb_relative_information_score: 10409.0668, mean_absolute_error: 0.0314, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9662, predictive_accuracy: 0.9656, prior_entropy: 0.2455, recall: 0.9656, relative_absolute_error: 0.4027, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.1627, root_relative_squared_error: 0.8237, scimark_benchmark: 936.7115, usercpu_time_millis: 16200, usercpu_time_millis_testing: 140, usercpu_time_millis_training: 16060,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9654, f_measure: 0.9394, kb_relative_information_score: 6918.9853, mean_absolute_error: 0.0383, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9204, predictive_accuracy: 0.9594, prior_entropy: 0.2455, recall: 0.9594, relative_absolute_error: 0.4906, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.1874, root_relative_squared_error: 0.9489, scimark_benchmark: 936.6206, usercpu_time_millis: 9210, usercpu_time_millis_testing: 80, usercpu_time_millis_training: 9130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9461, f_measure: 0.9394, kb_relative_information_score: 4498.0027, mean_absolute_error: 0.0406, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9204, predictive_accuracy: 0.9594, prior_entropy: 0.2455, recall: 0.9594, relative_absolute_error: 0.5197, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.2007, root_relative_squared_error: 1.0165, scimark_benchmark: 942.1229, usercpu_time_millis: 3130, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 3090,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9261, f_measure: 0.9394, kb_relative_information_score: 4453.103, mean_absolute_error: 0.0409, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9204, predictive_accuracy: 0.9594, prior_entropy: 0.2455, recall: 0.9594, relative_absolute_error: 0.5245, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.1991, root_relative_squared_error: 1.008, scimark_benchmark: 934.5243, usercpu_time_millis: 1620, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 1580,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8697, f_measure: 0.9394, kb_relative_information_score: 4464.1717, mean_absolute_error: 0.0408, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9204, predictive_accuracy: 0.9594, prior_entropy: 0.2455, recall: 0.9594, relative_absolute_error: 0.5233, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.2014, root_relative_squared_error: 1.0199, scimark_benchmark: 938.4278, usercpu_time_millis: 990, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 970,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9983, build_cpu_time: 15.6646, build_memory: 2133075426.4, f_measure: 0.996, kappa: 0.9483, kb_relative_information_score: 16325.8277, mean_absolute_error: 0.0089, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9961, predictive_accuracy: 0.9961, prior_entropy: 0.2455, recall: 0.9961, relative_absolute_error: 0.114, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.0551, root_relative_squared_error: 0.2789, scimark_benchmark: 943.4051,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9983, build_cpu_time: 13.5109, build_memory: 2032060532, f_measure: 0.996, kappa: 0.9483, kb_relative_information_score: 16325.8277, mean_absolute_error: 0.0089, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.9961, predictive_accuracy: 0.9961, prior_entropy: 0.2455, recall: 0.9961, relative_absolute_error: 0.114, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.0551, root_relative_squared_error: 0.2789, scimark_benchmark: 942.3637,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9977, build_cpu_time: 7.2521, build_memory: 127590971.2, f_measure: 0.9959, kappa: 0.947, kb_relative_information_score: 16130.856, mean_absolute_error: 0.0088, mean_prior_absolute_error: 0.078, number_of_instances: 20000, precision: 0.996, predictive_accuracy: 0.996, prior_entropy: 0.2455, recall: 0.996, relative_absolute_error: 0.1128, root_mean_prior_squared_error: 0.1975, root_mean_squared_error: 0.0565, root_relative_squared_error: 0.2863, scimark_benchmark: 920.3151,

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

OpenML bootcamp

From your own software

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

OpenML APIs