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OpenML
OpenML
Supervised Classification on hip

Supervised Classification on hip

Task 3761 Supervised Classification hip 516 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 under100k under1m
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516 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7713, f_measure: 0.6624, kappa: 0.358, kb_relative_information_score: 13.9323, mean_absolute_error: 0.3782, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7362, predictive_accuracy: 0.6852, prior_entropy: 0.9991, recall: 0.6852, relative_absolute_error: 0.7574, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4768, root_relative_squared_error: 0.9542, scimark_benchmark: 1324.8395,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7995, f_measure: 0.7952, kappa: 0.5948, kb_relative_information_score: 31.9558, mean_absolute_error: 0.2037, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.8081, predictive_accuracy: 0.7963, prior_entropy: 0.9991, recall: 0.7963, relative_absolute_error: 0.4079, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4513, root_relative_squared_error: 0.9033, scimark_benchmark: 1313.9994, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5192, f_measure: 0.3941, kappa: 0.0398, kb_relative_information_score: 3.9042, mean_absolute_error: 0.463, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7554, predictive_accuracy: 0.537, prior_entropy: 0.9991, recall: 0.537, relative_absolute_error: 0.9272, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.6804, root_relative_squared_error: 1.3618, scimark_benchmark: 887.6719, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8132, f_measure: 0.8143, kappa: 0.6281, kb_relative_information_score: 33.9595, mean_absolute_error: 0.1852, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.816, predictive_accuracy: 0.8148, prior_entropy: 0.9991, recall: 0.8148, relative_absolute_error: 0.3709, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4303, root_relative_squared_error: 0.8613, scimark_benchmark: 1386.5717,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.875, f_measure: 0.8148, kappa: 0.6301, kb_relative_information_score: 24.4741, mean_absolute_error: 0.2924, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.8171, predictive_accuracy: 0.8148, prior_entropy: 0.9991, recall: 0.8148, relative_absolute_error: 0.5857, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3744, root_relative_squared_error: 0.7493, scimark_benchmark: 938.343, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7981, f_measure: 0.7961, kappa: 0.5937, kb_relative_information_score: 31.9558, mean_absolute_error: 0.2037, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.8008, predictive_accuracy: 0.7963, prior_entropy: 0.9991, recall: 0.7963, relative_absolute_error: 0.4079, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4513, root_relative_squared_error: 0.9033, scimark_benchmark: 942.9708, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9135, f_measure: 0.8519, kappa: 0.7033, kb_relative_information_score: 30.4801, mean_absolute_error: 0.235, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.8519, predictive_accuracy: 0.8519, prior_entropy: 0.9991, recall: 0.8519, relative_absolute_error: 0.4705, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.324, root_relative_squared_error: 0.6485, scimark_benchmark: 918.0213, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5398, f_measure: 0.4553, kappa: 0.0822, kb_relative_information_score: 5.9079, mean_absolute_error: 0.4444, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.6411, predictive_accuracy: 0.5556, prior_entropy: 0.9991, recall: 0.5556, relative_absolute_error: 0.8901, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.6667, root_relative_squared_error: 1.3342, scimark_benchmark: 1306.6379,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8489, f_measure: 0.7961, kappa: 0.5915, kb_relative_information_score: 27.5766, mean_absolute_error: 0.2548, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7964, predictive_accuracy: 0.7963, prior_entropy: 0.9991, recall: 0.7963, relative_absolute_error: 0.5102, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3938, root_relative_squared_error: 0.7882, scimark_benchmark: 918.6491,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8654, f_measure: 0.7952, kappa: 0.5903, kb_relative_information_score: 26.2242, mean_absolute_error: 0.2655, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7992, predictive_accuracy: 0.7963, prior_entropy: 0.9991, recall: 0.7963, relative_absolute_error: 0.5318, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3946, root_relative_squared_error: 0.7896, scimark_benchmark: 1368.9272,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8709, f_measure: 0.7952, kappa: 0.5903, kb_relative_information_score: 27.4803, mean_absolute_error: 0.2549, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7992, predictive_accuracy: 0.7963, prior_entropy: 0.9991, recall: 0.7963, relative_absolute_error: 0.5105, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3902, root_relative_squared_error: 0.7809, scimark_benchmark: 904.2311,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8098, f_measure: 0.759, kappa: 0.5172, kb_relative_information_score: 22.4958, mean_absolute_error: 0.3007, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7593, predictive_accuracy: 0.7593, prior_entropy: 0.9991, recall: 0.7593, relative_absolute_error: 0.6022, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4414, root_relative_squared_error: 0.8835, scimark_benchmark: 932.7645, usercpu_time_millis: 140, usercpu_time_millis_training: 140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8681, f_measure: 0.8143, kappa: 0.6281, kb_relative_information_score: 25.2577, mean_absolute_error: 0.2807, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.816, predictive_accuracy: 0.8148, prior_entropy: 0.9991, recall: 0.8148, relative_absolute_error: 0.5622, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.374, root_relative_squared_error: 0.7485, scimark_benchmark: 1315.0767, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7102, f_measure: 0.7208, kappa: 0.4414, kb_relative_information_score: 20.9108, mean_absolute_error: 0.3099, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7239, predictive_accuracy: 0.7222, prior_entropy: 0.9991, recall: 0.7222, relative_absolute_error: 0.6207, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5158, root_relative_squared_error: 1.0322, scimark_benchmark: 1325.942,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7328, f_measure: 0.6836, kappa: 0.3669, kb_relative_information_score: 16.0516, mean_absolute_error: 0.3596, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.6862, predictive_accuracy: 0.6852, prior_entropy: 0.9991, recall: 0.6852, relative_absolute_error: 0.7201, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4852, root_relative_squared_error: 0.971, scimark_benchmark: 1073.494, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7926, f_measure: 0.7219, kappa: 0.4429, kb_relative_information_score: 20.7188, mean_absolute_error: 0.3114, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7221, predictive_accuracy: 0.7222, prior_entropy: 0.9991, recall: 0.7222, relative_absolute_error: 0.6236, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4691, root_relative_squared_error: 0.9388, scimark_benchmark: 1354.2491,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7569, f_measure: 0.758, kappa: 0.5159, kb_relative_information_score: 27.9484, mean_absolute_error: 0.2407, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7615, predictive_accuracy: 0.7593, prior_entropy: 0.9991, recall: 0.7593, relative_absolute_error: 0.4821, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4907, root_relative_squared_error: 0.982, scimark_benchmark: 1372.2145,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5879, f_measure: 0.5076, kappa: 0.1709, kb_relative_information_score: 7.9116, mean_absolute_error: 0.4259, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7006, predictive_accuracy: 0.5741, prior_entropy: 0.9991, recall: 0.5741, relative_absolute_error: 0.853, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.6526, root_relative_squared_error: 1.3062, scimark_benchmark: 1337.7959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.728, f_measure: 0.7386, kappa: 0.4779, kb_relative_information_score: 19.0457, mean_absolute_error: 0.3358, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7447, predictive_accuracy: 0.7407, prior_entropy: 0.9991, recall: 0.7407, relative_absolute_error: 0.6725, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4641, root_relative_squared_error: 0.9289, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6291, f_measure: 0.6296, kappa: 0.2582, kb_relative_information_score: 13.9226, mean_absolute_error: 0.3704, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.6296, predictive_accuracy: 0.6296, prior_entropy: 0.9991, recall: 0.6296, relative_absolute_error: 0.7417, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.6086, root_relative_squared_error: 1.218, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6854, f_measure: 0.6853, kappa: 0.3704, kb_relative_information_score: 19.9337, mean_absolute_error: 0.3148, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.6859, predictive_accuracy: 0.6852, prior_entropy: 0.9991, recall: 0.6852, relative_absolute_error: 0.6305, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5611, root_relative_squared_error: 1.1229, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4231, f_measure: 0.3541, kb_relative_information_score: -0.1594, mean_absolute_error: 0.5004, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.2689, predictive_accuracy: 0.5185, prior_entropy: 0.9991, recall: 0.5185, relative_absolute_error: 1.0021, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5007, root_relative_squared_error: 1.0022, scimark_benchmark: 1380.2233,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7734, f_measure: 0.7386, kappa: 0.4779, kb_relative_information_score: 18.9382, mean_absolute_error: 0.3329, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7447, predictive_accuracy: 0.7407, prior_entropy: 0.9991, recall: 0.7407, relative_absolute_error: 0.6667, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4501, root_relative_squared_error: 0.9009, scimark_benchmark: 1501.4698,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8496, f_measure: 0.7778, kappa: 0.5562, kb_relative_information_score: 30.7293, mean_absolute_error: 0.2136, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7799, predictive_accuracy: 0.7778, prior_entropy: 0.9991, recall: 0.7778, relative_absolute_error: 0.4278, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4454, root_relative_squared_error: 0.8915, scimark_benchmark: 927.0753,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8462, f_measure: 0.8148, kappa: 0.6301, kb_relative_information_score: 31.0634, mean_absolute_error: 0.216, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.8171, predictive_accuracy: 0.8148, prior_entropy: 0.9991, recall: 0.8148, relative_absolute_error: 0.4325, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4082, root_relative_squared_error: 0.8169, scimark_benchmark: 941.7954,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8386, f_measure: 0.7772, kappa: 0.5574, kb_relative_information_score: 28.008, mean_absolute_error: 0.2431, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7852, predictive_accuracy: 0.7778, prior_entropy: 0.9991, recall: 0.7778, relative_absolute_error: 0.4868, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4275, root_relative_squared_error: 0.8555, scimark_benchmark: 923.7642,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8386, f_measure: 0.7772, kappa: 0.5574, kb_relative_information_score: 28.008, mean_absolute_error: 0.2431, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7852, predictive_accuracy: 0.7778, prior_entropy: 0.9991, recall: 0.7778, relative_absolute_error: 0.4868, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4275, root_relative_squared_error: 0.8555, scimark_benchmark: 894.7455,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9011, f_measure: 0.8148, kappa: 0.6291, kb_relative_information_score: 35.2942, mean_absolute_error: 0.1719, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.8148, predictive_accuracy: 0.8148, prior_entropy: 0.9991, recall: 0.8148, relative_absolute_error: 0.3443, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4037, root_relative_squared_error: 0.808, scimark_benchmark: 936.6206, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8736, f_measure: 0.759, kappa: 0.5198, kb_relative_information_score: 29.7096, mean_absolute_error: 0.2234, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7635, predictive_accuracy: 0.7593, prior_entropy: 0.9991, recall: 0.7593, relative_absolute_error: 0.4474, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4391, root_relative_squared_error: 0.8787, scimark_benchmark: 938.2848, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8736, f_measure: 0.759, kappa: 0.5198, kb_relative_information_score: 29.7306, mean_absolute_error: 0.2216, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7635, predictive_accuracy: 0.7593, prior_entropy: 0.9991, recall: 0.7593, relative_absolute_error: 0.4437, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4405, root_relative_squared_error: 0.8816, scimark_benchmark: 938.2848,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.842, f_measure: 0.7772, kappa: 0.5574, kb_relative_information_score: 29.4297, mean_absolute_error: 0.2291, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7852, predictive_accuracy: 0.7778, prior_entropy: 0.9991, recall: 0.7778, relative_absolute_error: 0.4589, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4462, root_relative_squared_error: 0.8929, scimark_benchmark: 934.5243, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8352, f_measure: 0.7772, kappa: 0.5574, kb_relative_information_score: 29.73, mean_absolute_error: 0.2274, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7852, predictive_accuracy: 0.7778, prior_entropy: 0.9991, recall: 0.7778, relative_absolute_error: 0.4554, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4123, root_relative_squared_error: 0.8252, scimark_benchmark: 938.9865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9032, f_measure: 0.8148, kappa: 0.6291, kb_relative_information_score: 34.2214, mean_absolute_error: 0.1815, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.8148, predictive_accuracy: 0.8148, prior_entropy: 0.9991, recall: 0.8148, relative_absolute_error: 0.3634, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4096, root_relative_squared_error: 0.8198, scimark_benchmark: 938.4285, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9135, f_measure: 0.8514, kappa: 0.7025, kb_relative_information_score: 37.7107, mean_absolute_error: 0.1521, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.8534, predictive_accuracy: 0.8519, prior_entropy: 0.9991, recall: 0.8519, relative_absolute_error: 0.3045, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3554, root_relative_squared_error: 0.7112, scimark_benchmark: 924.6116, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.919, f_measure: 0.8886, kappa: 0.7769, kb_relative_information_score: 38.0376, mean_absolute_error: 0.152, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.8907, predictive_accuracy: 0.8889, prior_entropy: 0.9991, recall: 0.8889, relative_absolute_error: 0.3043, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3256, root_relative_squared_error: 0.6516, scimark_benchmark: 924.6116, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8427, build_cpu_time: 0.0035, build_memory: 1304558262.2222, f_measure: 0.7772, kappa: 0.5574, kb_relative_information_score: 28.2791, mean_absolute_error: 0.2406, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7852, predictive_accuracy: 0.7778, prior_entropy: 0.9991, recall: 0.7778, relative_absolute_error: 0.4818, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4244, root_relative_squared_error: 0.8495, scimark_benchmark: 929.5397,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8269, build_cpu_time: 0.0995, build_memory: 36386462.8148, f_measure: 0.7772, kappa: 0.5537, kb_relative_information_score: 30.3125, mean_absolute_error: 0.2226, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.7787, predictive_accuracy: 0.7778, prior_entropy: 0.9991, recall: 0.7778, relative_absolute_error: 0.4458, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4168, root_relative_squared_error: 0.8342, scimark_benchmark: 929.5397,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9162, build_cpu_time: 0.697, build_memory: 1798418682.3704, f_measure: 0.8889, kappa: 0.7775, kb_relative_information_score: 42.6635, mean_absolute_error: 0.1043, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.8889, predictive_accuracy: 0.8889, prior_entropy: 0.9991, recall: 0.8889, relative_absolute_error: 0.2089, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3151, root_relative_squared_error: 0.6306, scimark_benchmark: 916.8903,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9183, build_cpu_time: 0.3796, build_memory: 889203558.3704, f_measure: 0.8702, kappa: 0.74, kb_relative_information_score: 40.0193, mean_absolute_error: 0.129, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.8707, predictive_accuracy: 0.8704, prior_entropy: 0.9991, recall: 0.8704, relative_absolute_error: 0.2584, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.358, root_relative_squared_error: 0.7166, scimark_benchmark: 942.3919,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9464, build_cpu_time: 0.1724, build_memory: 133983650.6667, f_measure: 0.8889, kappa: 0.7775, kb_relative_information_score: 41.9041, mean_absolute_error: 0.112, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.8889, predictive_accuracy: 0.8889, prior_entropy: 0.9991, recall: 0.8889, relative_absolute_error: 0.2243, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3222, root_relative_squared_error: 0.6449, scimark_benchmark: 942.5053,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9025, build_cpu_time: 0.0245, build_memory: 1359392193.7778, f_measure: 0.8148, kappa: 0.6291, kb_relative_information_score: 34.011, mean_absolute_error: 0.1857, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.8148, predictive_accuracy: 0.8148, prior_entropy: 0.9991, recall: 0.8148, relative_absolute_error: 0.3718, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4145, root_relative_squared_error: 0.8295, scimark_benchmark: 923.3659,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9011, build_cpu_time: 0.0454, build_memory: 754405984.4444, f_measure: 0.8514, kappa: 0.7025, kb_relative_information_score: 38.664, mean_absolute_error: 0.1405, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.8534, predictive_accuracy: 0.8519, prior_entropy: 0.9991, recall: 0.8519, relative_absolute_error: 0.2814, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3645, root_relative_squared_error: 0.7295, scimark_benchmark: 874.7324,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8523, build_cpu_time: 0.0914, build_memory: 847793506.3704, f_measure: 0.8332, kappa: 0.6658, kb_relative_information_score: 36.0285, mean_absolute_error: 0.1659, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.8336, predictive_accuracy: 0.8333, prior_entropy: 0.9991, recall: 0.8333, relative_absolute_error: 0.3321, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4061, root_relative_squared_error: 0.8128, scimark_benchmark: 924.6733,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8462, build_cpu_time: 0.1932, build_memory: 945517975.1111, f_measure: 0.8519, kappa: 0.7033, kb_relative_information_score: 37.4273, mean_absolute_error: 0.1543, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.8519, predictive_accuracy: 0.8519, prior_entropy: 0.9991, recall: 0.8519, relative_absolute_error: 0.3091, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3865, root_relative_squared_error: 0.7736, scimark_benchmark: 890.3066,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8462, build_cpu_time: 0.3799, build_memory: 275820992.5926, f_measure: 0.8334, kappa: 0.6667, kb_relative_information_score: 36.0825, mean_absolute_error: 0.1654, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.834, predictive_accuracy: 0.8333, prior_entropy: 0.9991, recall: 0.8333, relative_absolute_error: 0.3313, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.3997, root_relative_squared_error: 0.8, scimark_benchmark: 893.4088,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9052, build_cpu_time: 0.0206, build_memory: 831597926.0741, f_measure: 0.8148, kappa: 0.6291, kb_relative_information_score: 33.3924, mean_absolute_error: 0.1919, mean_prior_absolute_error: 0.4993, number_of_instances: 54, precision: 0.8148, predictive_accuracy: 0.8148, prior_entropy: 0.9991, recall: 0.8148, relative_absolute_error: 0.3844, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.417, root_relative_squared_error: 0.8346, scimark_benchmark: 945.5885,

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