Task
Supervised Classification on spambase

Supervised Classification on spambase

Task 1807 Supervised Classification spambase 367 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9389, build_cpu_time: 5.8395, build_memory: 463076800.5202, f_measure: 0.9168, kappa: 0.8249, kb_relative_information_score: 18838.0662, mean_absolute_error: 0.0856, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9175, predictive_accuracy: 0.9173, prior_entropy: 0.9674, recall: 0.9173, relative_absolute_error: 0.1792, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2668, root_relative_squared_error: 0.546, scimark_benchmark: 939.7809,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.924, build_cpu_time: 2.0813, build_memory: 265341045.812, f_measure: 0.9025, kappa: 0.7943, kb_relative_information_score: 18209.0358, mean_absolute_error: 0.0982, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9043, predictive_accuracy: 0.9035, prior_entropy: 0.9674, recall: 0.9035, relative_absolute_error: 0.2057, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2902, root_relative_squared_error: 0.594, scimark_benchmark: 931.4894,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.924, build_cpu_time: 1.5283, build_memory: 780868523.9084, f_measure: 0.9025, kappa: 0.7943, kb_relative_information_score: 18209.0358, mean_absolute_error: 0.0982, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9043, predictive_accuracy: 0.9035, prior_entropy: 0.9674, recall: 0.9035, relative_absolute_error: 0.2057, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2902, root_relative_squared_error: 0.594, scimark_benchmark: 935.7354,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.924, build_cpu_time: 1.2171, build_memory: 388543210.1328, f_measure: 0.9025, kappa: 0.7943, kb_relative_information_score: 18209.0358, mean_absolute_error: 0.0982, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9043, predictive_accuracy: 0.9035, prior_entropy: 0.9674, recall: 0.9035, relative_absolute_error: 0.2057, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2902, root_relative_squared_error: 0.594, scimark_benchmark: 926.0021,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9294, build_cpu_time: 2.7371, build_memory: 673962356.1699, f_measure: 0.903, kappa: 0.7956, kb_relative_information_score: 18236.2725, mean_absolute_error: 0.0979, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9049, predictive_accuracy: 0.904, prior_entropy: 0.9674, recall: 0.904, relative_absolute_error: 0.205, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2879, root_relative_squared_error: 0.5892, scimark_benchmark: 919.3675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.933, build_cpu_time: 5.1805, build_memory: 676734744.884, f_measure: 0.9049, kappa: 0.7995, kb_relative_information_score: 18244.9172, mean_absolute_error: 0.0977, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9065, predictive_accuracy: 0.9058, prior_entropy: 0.9674, recall: 0.9058, relative_absolute_error: 0.2045, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2871, root_relative_squared_error: 0.5876, scimark_benchmark: 935.2304,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9373, build_cpu_time: 9.9839, build_memory: 3269098229.8582, f_measure: 0.9046, kappa: 0.7989, kb_relative_information_score: 18235.1824, mean_absolute_error: 0.0979, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9062, predictive_accuracy: 0.9055, prior_entropy: 0.9674, recall: 0.9055, relative_absolute_error: 0.205, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2871, root_relative_squared_error: 0.5876, scimark_benchmark: 949.2096,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9405, build_cpu_time: 19.5049, build_memory: 2656398647.5601, f_measure: 0.9047, kappa: 0.7991, kb_relative_information_score: 18232.1864, mean_absolute_error: 0.0979, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9063, predictive_accuracy: 0.9056, prior_entropy: 0.9674, recall: 0.9056, relative_absolute_error: 0.2051, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.287, root_relative_squared_error: 0.5873, scimark_benchmark: 949.2096,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9765, build_cpu_time: 9.6686, build_memory: 78070348.9683, f_measure: 0.9326, kappa: 0.8585, kb_relative_information_score: 17546.001, mean_absolute_error: 0.1246, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9329, predictive_accuracy: 0.9329, prior_entropy: 0.9674, recall: 0.9329, relative_absolute_error: 0.261, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2285, root_relative_squared_error: 0.4676, scimark_benchmark: 943.2048,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.976, build_cpu_time: 5.754, build_memory: 1379914597.1836, f_measure: 0.9323, kappa: 0.8577, kb_relative_information_score: 17539.6109, mean_absolute_error: 0.1246, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9324, predictive_accuracy: 0.9325, prior_entropy: 0.9674, recall: 0.9325, relative_absolute_error: 0.2609, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2294, root_relative_squared_error: 0.4695, scimark_benchmark: 943.4766,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9753, build_cpu_time: 2.7431, build_memory: 2360920868.0123, f_measure: 0.9328, kappa: 0.859, kb_relative_information_score: 17541.4154, mean_absolute_error: 0.1243, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.933, predictive_accuracy: 0.9331, prior_entropy: 0.9674, recall: 0.9331, relative_absolute_error: 0.2604, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2304, root_relative_squared_error: 0.4715, scimark_benchmark: 949.2096,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9745, build_cpu_time: 1.3871, build_memory: 1077939365.1411, f_measure: 0.9316, kappa: 0.8563, kb_relative_information_score: 17559.4007, mean_absolute_error: 0.1236, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9318, predictive_accuracy: 0.9318, prior_entropy: 0.9674, recall: 0.9318, relative_absolute_error: 0.2587, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2316, root_relative_squared_error: 0.474, scimark_benchmark: 947.4258,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9764, build_cpu_time: 0.1768, build_memory: 388912677.2458, f_measure: 0.9363, kappa: 0.866, kb_relative_information_score: 17674.2764, mean_absolute_error: 0.1202, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9368, predictive_accuracy: 0.9366, prior_entropy: 0.9674, recall: 0.9366, relative_absolute_error: 0.2517, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2286, root_relative_squared_error: 0.4678, scimark_benchmark: 941.5201,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9827, build_cpu_time: 0.6986, build_memory: 141120708.1807, f_measure: 0.9461, kappa: 0.8868, kb_relative_information_score: 17919.6013, mean_absolute_error: 0.1174, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9463, predictive_accuracy: 0.9463, prior_entropy: 0.9674, recall: 0.9463, relative_absolute_error: 0.2459, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2131, root_relative_squared_error: 0.4361, scimark_benchmark: 946.5543,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9837, build_cpu_time: 1.4302, build_memory: 2703010850.6746, f_measure: 0.9472, kappa: 0.8892, kb_relative_information_score: 17941.3496, mean_absolute_error: 0.1174, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9474, predictive_accuracy: 0.9474, prior_entropy: 0.9674, recall: 0.9474, relative_absolute_error: 0.2458, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.211, root_relative_squared_error: 0.4318, scimark_benchmark: 941.3608,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9837, build_cpu_time: 1.3377, build_memory: 2515302522.9075, f_measure: 0.9472, kappa: 0.8892, kb_relative_information_score: 17941.3496, mean_absolute_error: 0.1174, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9474, predictive_accuracy: 0.9474, prior_entropy: 0.9674, recall: 0.9474, relative_absolute_error: 0.2458, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.211, root_relative_squared_error: 0.4318, scimark_benchmark: 874.7213,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9842, build_cpu_time: 2.3705, build_memory: 642183439.4679, f_measure: 0.9479, kappa: 0.8905, kb_relative_information_score: 17949.3914, mean_absolute_error: 0.1174, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.948, predictive_accuracy: 0.948, prior_entropy: 0.9674, recall: 0.948, relative_absolute_error: 0.2459, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2098, root_relative_squared_error: 0.4294, scimark_benchmark: 941.1794,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.984, build_cpu_time: 170.0219, build_memory: 2156770214.3631, f_measure: 0.946, kappa: 0.8865, kb_relative_information_score: 17620.6056, mean_absolute_error: 0.1257, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9462, predictive_accuracy: 0.9461, prior_entropy: 0.9674, recall: 0.9461, relative_absolute_error: 0.2633, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2135, root_relative_squared_error: 0.4369, scimark_benchmark: 941.6768,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.984, build_cpu_time: 38.7628, build_memory: 1188765757.0507, f_measure: 0.9463, kappa: 0.8871, kb_relative_information_score: 17620.8433, mean_absolute_error: 0.1257, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9465, predictive_accuracy: 0.9464, prior_entropy: 0.9674, recall: 0.9464, relative_absolute_error: 0.2633, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2135, root_relative_squared_error: 0.437, scimark_benchmark: 922.9897,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9839, build_cpu_time: 19.1424, build_memory: 2226473825.9857, f_measure: 0.9465, kappa: 0.8877, kb_relative_information_score: 17615.2177, mean_absolute_error: 0.1258, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9467, predictive_accuracy: 0.9467, prior_entropy: 0.9674, recall: 0.9467, relative_absolute_error: 0.2635, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2137, root_relative_squared_error: 0.4373, scimark_benchmark: 939.4327,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9838, build_cpu_time: 10.1711, build_memory: 620499862.6062, f_measure: 0.9458, kappa: 0.8862, kb_relative_information_score: 17612.3149, mean_absolute_error: 0.1258, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9461, predictive_accuracy: 0.946, prior_entropy: 0.9674, recall: 0.946, relative_absolute_error: 0.2635, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.214, root_relative_squared_error: 0.438, scimark_benchmark: 926.9727,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8299, build_cpu_time: 0.1778, build_memory: 1471699228.1619, f_measure: 0.7799, kappa: 0.5356, kb_relative_information_score: 11636.2868, mean_absolute_error: 0.2357, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.7804, predictive_accuracy: 0.7825, prior_entropy: 0.9674, recall: 0.7825, relative_absolute_error: 0.4935, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.4141, root_relative_squared_error: 0.8474, scimark_benchmark: 942.3187,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9834, build_cpu_time: 57.634, build_memory: 752280421.7987, f_measure: 0.9478, kappa: 0.8904, kb_relative_information_score: 18491.6037, mean_absolute_error: 0.1043, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9479, predictive_accuracy: 0.9479, prior_entropy: 0.9674, recall: 0.9479, relative_absolute_error: 0.2184, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2037, root_relative_squared_error: 0.4169, scimark_benchmark: 938.3567,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8383, build_cpu_time: 0.3879, build_memory: 335559886.0679, f_measure: 0.7854, kappa: 0.5478, kb_relative_information_score: 11663.5876, mean_absolute_error: 0.2357, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.7853, predictive_accuracy: 0.7872, prior_entropy: 0.9674, recall: 0.7872, relative_absolute_error: 0.4936, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.4104, root_relative_squared_error: 0.84, scimark_benchmark: 943.2191,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8383, build_cpu_time: 0.3875, build_memory: 543183227.8694, f_measure: 0.7854, kappa: 0.5478, kb_relative_information_score: 11663.5876, mean_absolute_error: 0.2357, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.7853, predictive_accuracy: 0.7872, prior_entropy: 0.9674, recall: 0.7872, relative_absolute_error: 0.4936, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.4104, root_relative_squared_error: 0.84, scimark_benchmark: 938.3567,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8383, build_cpu_time: 0.3982, build_memory: 272561488.0838, f_measure: 0.7854, kappa: 0.5478, kb_relative_information_score: 11663.5876, mean_absolute_error: 0.2357, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.7853, predictive_accuracy: 0.7872, prior_entropy: 0.9674, recall: 0.7872, relative_absolute_error: 0.4936, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.4104, root_relative_squared_error: 0.84, scimark_benchmark: 926.9727,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8383, build_cpu_time: 0.3929, build_memory: 402776437.7779, f_measure: 0.7854, kappa: 0.5478, kb_relative_information_score: 11663.5876, mean_absolute_error: 0.2357, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.7853, predictive_accuracy: 0.7872, prior_entropy: 0.9674, recall: 0.7872, relative_absolute_error: 0.4936, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.4104, root_relative_squared_error: 0.84, scimark_benchmark: 941.6532,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8465, build_cpu_time: 0.6747, build_memory: 752719819.2442, f_measure: 0.7876, kappa: 0.5532, kb_relative_information_score: 11696.1009, mean_absolute_error: 0.2356, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.7873, predictive_accuracy: 0.7889, prior_entropy: 0.9674, recall: 0.7889, relative_absolute_error: 0.4934, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.4065, root_relative_squared_error: 0.8319, scimark_benchmark: 937.52,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8472, build_cpu_time: 1.5026, build_memory: 70200279.3351, f_measure: 0.7886, kappa: 0.5552, kb_relative_information_score: 11661.9652, mean_absolute_error: 0.2363, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.7883, predictive_accuracy: 0.79, prior_entropy: 0.9674, recall: 0.79, relative_absolute_error: 0.4949, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.4073, root_relative_squared_error: 0.8336, scimark_benchmark: 938.3567,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8472, build_cpu_time: 1.3567, build_memory: 277100990.3642, f_measure: 0.7886, kappa: 0.5552, kb_relative_information_score: 11661.9652, mean_absolute_error: 0.2363, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.7883, predictive_accuracy: 0.79, prior_entropy: 0.9674, recall: 0.79, relative_absolute_error: 0.4949, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.4073, root_relative_squared_error: 0.8336, scimark_benchmark: 910.9043,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8472, build_cpu_time: 1.296, build_memory: 1004793741.4597, f_measure: 0.7886, kappa: 0.5552, kb_relative_information_score: 11661.9652, mean_absolute_error: 0.2363, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.7883, predictive_accuracy: 0.79, prior_entropy: 0.9674, recall: 0.79, relative_absolute_error: 0.4949, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.4073, root_relative_squared_error: 0.8336, scimark_benchmark: 943.443,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9799, build_cpu_time: 3.7767, build_memory: 201177818.6158, f_measure: 0.9458, kappa: 0.8863, kb_relative_information_score: 18433.9784, mean_absolute_error: 0.1042, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9459, predictive_accuracy: 0.9459, prior_entropy: 0.9674, recall: 0.9459, relative_absolute_error: 0.2181, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2124, root_relative_squared_error: 0.4346, scimark_benchmark: 926.9727,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8773, build_cpu_time: 3.099, build_memory: 1041780233.8038, f_measure: 0.804, kappa: 0.6134, kb_relative_information_score: 13145.3237, mean_absolute_error: 0.2013, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.847, predictive_accuracy: 0.8023, prior_entropy: 0.9674, recall: 0.8023, relative_absolute_error: 0.4215, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.428, root_relative_squared_error: 0.8759, scimark_benchmark: 927.7693,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9672, build_cpu_time: 1.7144, build_memory: 82543372.0148, f_measure: 0.9182, kappa: 0.8282, kb_relative_information_score: 17437.1069, mean_absolute_error: 0.1221, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9183, predictive_accuracy: 0.9185, prior_entropy: 0.9674, recall: 0.9185, relative_absolute_error: 0.2556, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2518, root_relative_squared_error: 0.5153, scimark_benchmark: 926.5157,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8671, build_cpu_time: 0.4316, build_memory: 289663867.2577, f_measure: 0.7977, kappa: 0.5921, kb_relative_information_score: 12104.3384, mean_absolute_error: 0.2241, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.8207, predictive_accuracy: 0.7953, prior_entropy: 0.9674, recall: 0.7953, relative_absolute_error: 0.4694, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.4417, root_relative_squared_error: 0.904, scimark_benchmark: 939.2194,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9719, build_cpu_time: 3884.658, build_memory: 385447599.0207, f_measure: 0.9281, kappa: 0.849, kb_relative_information_score: 17732.6219, mean_absolute_error: 0.1181, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9282, predictive_accuracy: 0.9283, prior_entropy: 0.9674, recall: 0.9283, relative_absolute_error: 0.2472, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2389, root_relative_squared_error: 0.4889, scimark_benchmark: 941.326,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9726, build_cpu_time: 11772.598, build_memory: 823302273.5593, f_measure: 0.9279, kappa: 0.8486, kb_relative_information_score: 17836.2217, mean_absolute_error: 0.1155, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.9279, predictive_accuracy: 0.9281, prior_entropy: 0.9674, recall: 0.9281, relative_absolute_error: 0.2419, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.2377, root_relative_squared_error: 0.4865, scimark_benchmark: 906.33,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8739, build_cpu_time: 0.1075, build_memory: 1003568528.0358, f_measure: 0.7938, kappa: 0.5646, kb_relative_information_score: 8578.3415, mean_absolute_error: 0.3191, mean_prior_absolute_error: 0.4776, number_of_instances: 23005, precision: 0.795, predictive_accuracy: 0.7966, prior_entropy: 0.9674, recall: 0.7966, relative_absolute_error: 0.6682, root_mean_prior_squared_error: 0.4886, root_mean_squared_error: 0.376, root_relative_squared_error: 0.7695, scimark_benchmark: 941.0301,
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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