OpenML
Supervised Classification on diabetes

Supervised Classification on diabetes

Task 37 Supervised Classification diabetes 131682 runs submitted
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  • at2 basic mythbusting mythbusting_1 OpenML-CC18 OpenML100 study_1 study_107 study_123 study_14 study_15 study_20 study_29 study_30 study_41 study_7 study_70 study_73 study_98 study_99 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7062, build_cpu_time: 0.0106, build_memory: 940912847.6979, f_measure: 0.6963, kappa: 0.3158, kb_relative_information_score: 209.5081, mean_absolute_error: 0.3254, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7113, predictive_accuracy: 0.7201, prior_entropy: 0.9335, recall: 0.7201, relative_absolute_error: 0.7159, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4632, root_relative_squared_error: 0.9718, scimark_benchmark: 902.1764,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7062, build_cpu_time: 0.0102, build_memory: 1040280440.6771, f_measure: 0.6963, kappa: 0.3158, kb_relative_information_score: 209.5081, mean_absolute_error: 0.3254, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7113, predictive_accuracy: 0.7201, prior_entropy: 0.9335, recall: 0.7201, relative_absolute_error: 0.7159, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4632, root_relative_squared_error: 0.9718, scimark_benchmark: 942.3187,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7236, build_cpu_time: 0.0388, build_memory: 534084307.1771, f_measure: 0.6834, kappa: 0.2867, kb_relative_information_score: 206.3976, mean_absolute_error: 0.329, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.6943, predictive_accuracy: 0.707, prior_entropy: 0.9335, recall: 0.707, relative_absolute_error: 0.7239, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4552, root_relative_squared_error: 0.955, scimark_benchmark: 938.3567,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7236, build_cpu_time: 0.0375, build_memory: 600171387.6771, f_measure: 0.6834, kappa: 0.2867, kb_relative_information_score: 206.3976, mean_absolute_error: 0.329, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.6943, predictive_accuracy: 0.707, prior_entropy: 0.9335, recall: 0.707, relative_absolute_error: 0.7239, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4552, root_relative_squared_error: 0.955, scimark_benchmark: 941.6532,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7236, build_cpu_time: 0.0379, build_memory: 344096331.1563, f_measure: 0.6834, kappa: 0.2867, kb_relative_information_score: 206.3976, mean_absolute_error: 0.329, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.6943, predictive_accuracy: 0.707, prior_entropy: 0.9335, recall: 0.707, relative_absolute_error: 0.7239, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4552, root_relative_squared_error: 0.955, scimark_benchmark: 937.52,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8357, build_cpu_time: 2.0723, build_memory: 736224468.6979, f_measure: 0.7662, kappa: 0.4797, kb_relative_information_score: 258.0272, mean_absolute_error: 0.3069, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7652, predictive_accuracy: 0.7695, prior_entropy: 0.9335, recall: 0.7695, relative_absolute_error: 0.6754, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.394, root_relative_squared_error: 0.8265, scimark_benchmark: 926.9727,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8357, build_cpu_time: 2.1005, build_memory: 1655005770.2292, f_measure: 0.7662, kappa: 0.4797, kb_relative_information_score: 258.0272, mean_absolute_error: 0.3069, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7652, predictive_accuracy: 0.7695, prior_entropy: 0.9335, recall: 0.7695, relative_absolute_error: 0.6754, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.394, root_relative_squared_error: 0.8265, scimark_benchmark: 902.1764,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8366, build_cpu_time: 7.4405, build_memory: 718850841.4063, f_measure: 0.7662, kappa: 0.4797, kb_relative_information_score: 254.4924, mean_absolute_error: 0.3093, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7652, predictive_accuracy: 0.7695, prior_entropy: 0.9335, recall: 0.7695, relative_absolute_error: 0.6805, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3939, root_relative_squared_error: 0.8263, scimark_benchmark: 929.8269,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8366, build_cpu_time: 7.6946, build_memory: 1347111632.3542, f_measure: 0.7662, kappa: 0.4797, kb_relative_information_score: 254.4924, mean_absolute_error: 0.3093, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7652, predictive_accuracy: 0.7695, prior_entropy: 0.9335, recall: 0.7695, relative_absolute_error: 0.6805, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3939, root_relative_squared_error: 0.8263, scimark_benchmark: 922.9897,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8366, build_cpu_time: 8.1598, build_memory: 697280183.375, f_measure: 0.7662, kappa: 0.4797, kb_relative_information_score: 254.4924, mean_absolute_error: 0.3093, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7652, predictive_accuracy: 0.7695, prior_entropy: 0.9335, recall: 0.7695, relative_absolute_error: 0.6805, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3939, root_relative_squared_error: 0.8263, scimark_benchmark: 940.5606,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8369, build_cpu_time: 0.9481, build_memory: 375433246.7813, f_measure: 0.7656, kappa: 0.4741, kb_relative_information_score: 226.2597, mean_absolute_error: 0.3308, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7684, predictive_accuracy: 0.7734, prior_entropy: 0.9335, recall: 0.7734, relative_absolute_error: 0.7278, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3957, root_relative_squared_error: 0.8302, scimark_benchmark: 939.4327,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8033, build_cpu_time: 299.6014, build_memory: 45495017.0104, f_measure: 0.7448, kappa: 0.4358, kb_relative_information_score: 315.4436, mean_absolute_error: 0.2583, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7439, predictive_accuracy: 0.7461, prior_entropy: 0.9335, recall: 0.7461, relative_absolute_error: 0.5684, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.465, root_relative_squared_error: 0.9756, scimark_benchmark: 937.9119,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8114, build_cpu_time: 155.9664, build_memory: 26769276.0313, f_measure: 0.7593, kappa: 0.4659, kb_relative_information_score: 315.9691, mean_absolute_error: 0.2605, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7581, predictive_accuracy: 0.7617, prior_entropy: 0.9335, recall: 0.7617, relative_absolute_error: 0.5732, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4409, root_relative_squared_error: 0.925, scimark_benchmark: 937.9406,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8082, build_cpu_time: 78.9084, build_memory: 822357330.8542, f_measure: 0.7368, kappa: 0.414, kb_relative_information_score: 293.703, mean_absolute_error: 0.2749, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7353, predictive_accuracy: 0.7409, prior_entropy: 0.9335, recall: 0.7409, relative_absolute_error: 0.6048, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4311, root_relative_squared_error: 0.9044, scimark_benchmark: 923.9118,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8025, build_cpu_time: 37.1578, build_memory: 746963288.6771, f_measure: 0.7459, kappa: 0.4357, kb_relative_information_score: 276.5949, mean_absolute_error: 0.2888, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7445, predictive_accuracy: 0.7487, prior_entropy: 0.9335, recall: 0.7487, relative_absolute_error: 0.6355, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4249, root_relative_squared_error: 0.8915, scimark_benchmark: 893.4088,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8031, build_cpu_time: 0.0597, build_memory: 1304017885.5313, f_measure: 0.761, kappa: 0.4666, kb_relative_information_score: 270.7828, mean_absolute_error: 0.2969, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7604, predictive_accuracy: 0.7656, prior_entropy: 0.9335, recall: 0.7656, relative_absolute_error: 0.6532, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4162, root_relative_squared_error: 0.8732, scimark_benchmark: 943.5504,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7996, build_cpu_time: 0.6777, build_memory: 245754999.2188, f_measure: 0.7529, kappa: 0.4518, kb_relative_information_score: 292.5271, mean_absolute_error: 0.2776, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7516, predictive_accuracy: 0.7552, prior_entropy: 0.9335, recall: 0.7552, relative_absolute_error: 0.6108, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4344, root_relative_squared_error: 0.9115, scimark_benchmark: 945.0532,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7719, build_cpu_time: 3.0511, build_memory: 398975008.5417, f_measure: 0.7239, kappa: 0.3876, kb_relative_information_score: 285.8052, mean_absolute_error: 0.2739, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7223, predictive_accuracy: 0.7266, prior_entropy: 0.9335, recall: 0.7266, relative_absolute_error: 0.6027, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4951, root_relative_squared_error: 1.0387, scimark_benchmark: 914.1182,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7873, build_cpu_time: 6.875, build_memory: 899054570.3125, f_measure: 0.7394, kappa: 0.4216, kb_relative_information_score: 318.1926, mean_absolute_error: 0.2554, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.738, predictive_accuracy: 0.7422, prior_entropy: 0.9335, recall: 0.7422, relative_absolute_error: 0.5619, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4919, root_relative_squared_error: 1.0319, scimark_benchmark: 930.5854,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7618, build_cpu_time: 14.3112, build_memory: 127582452.2188, f_measure: 0.7467, kappa: 0.4412, kb_relative_information_score: 322.6993, mean_absolute_error: 0.2532, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7461, predictive_accuracy: 0.7474, prior_entropy: 0.9335, recall: 0.7474, relative_absolute_error: 0.5572, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4957, root_relative_squared_error: 1.0399, scimark_benchmark: 938.1146,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7375, build_cpu_time: 55.8366, build_memory: 101243428.2813, f_measure: 0.7517, kappa: 0.4517, kb_relative_information_score: 332.8895, mean_absolute_error: 0.2473, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.751, predictive_accuracy: 0.7526, prior_entropy: 0.9335, recall: 0.7526, relative_absolute_error: 0.5441, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4958, root_relative_squared_error: 1.0401, scimark_benchmark: 931.6517,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8005, build_cpu_time: 0.344, build_memory: 1160790297.3542, f_measure: 0.7424, kappa: 0.4252, kb_relative_information_score: 278.703, mean_absolute_error: 0.2861, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7413, predictive_accuracy: 0.7474, prior_entropy: 0.9335, recall: 0.7474, relative_absolute_error: 0.6294, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4325, root_relative_squared_error: 0.9073, scimark_benchmark: 913.3372,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7921, build_cpu_time: 7.7391, build_memory: 378523793.2188, f_measure: 0.741, kappa: 0.4276, kb_relative_information_score: 307.6835, mean_absolute_error: 0.2622, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7401, predictive_accuracy: 0.7422, prior_entropy: 0.9335, recall: 0.7422, relative_absolute_error: 0.5768, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4858, root_relative_squared_error: 1.0192, scimark_benchmark: 937.9603,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7974, build_cpu_time: 3.9176, build_memory: 647475209.6563, f_measure: 0.7356, kappa: 0.4178, kb_relative_information_score: 301.1117, mean_absolute_error: 0.2667, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7355, predictive_accuracy: 0.7357, prior_entropy: 0.9335, recall: 0.7357, relative_absolute_error: 0.5868, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4735, root_relative_squared_error: 0.9933, scimark_benchmark: 937.9603,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.801, build_cpu_time: 2.0857, build_memory: 147118118.3646, f_measure: 0.7479, kappa: 0.4436, kb_relative_information_score: 301.5677, mean_absolute_error: 0.2673, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7472, predictive_accuracy: 0.7487, prior_entropy: 0.9335, recall: 0.7487, relative_absolute_error: 0.5882, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4589, root_relative_squared_error: 0.9627, scimark_benchmark: 913.3372,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.802, build_cpu_time: 19.3926, build_memory: 262985274.5208, f_measure: 0.7514, kappa: 0.4484, kb_relative_information_score: 259.5484, mean_absolute_error: 0.3022, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7501, predictive_accuracy: 0.7539, prior_entropy: 0.9335, recall: 0.7539, relative_absolute_error: 0.6648, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4222, root_relative_squared_error: 0.8858, scimark_benchmark: 892.8005,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8028, build_cpu_time: 1.0436, build_memory: 838343196.0208, f_measure: 0.7455, kappa: 0.4388, kb_relative_information_score: 292.4217, mean_absolute_error: 0.2742, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.745, predictive_accuracy: 0.7461, prior_entropy: 0.9335, recall: 0.7461, relative_absolute_error: 0.6033, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4454, root_relative_squared_error: 0.9345, scimark_benchmark: 923.3659,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7683, build_cpu_time: 0.0862, build_memory: 231434483.5938, f_measure: 0.7495, kappa: 0.4415, kb_relative_information_score: 332.3188, mean_absolute_error: 0.2479, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7484, predictive_accuracy: 0.7539, prior_entropy: 0.9335, recall: 0.7539, relative_absolute_error: 0.5455, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4828, root_relative_squared_error: 1.013, scimark_benchmark: 899.6089,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7683, build_cpu_time: 0.0833, build_memory: 819386950.9063, f_measure: 0.7495, kappa: 0.4415, kb_relative_information_score: 332.3188, mean_absolute_error: 0.2479, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7484, predictive_accuracy: 0.7539, prior_entropy: 0.9335, recall: 0.7539, relative_absolute_error: 0.5455, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4828, root_relative_squared_error: 1.013, scimark_benchmark: 927.7693,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7683, build_cpu_time: 0.0824, build_memory: 155172186.7604, f_measure: 0.7495, kappa: 0.4415, kb_relative_information_score: 332.3188, mean_absolute_error: 0.2479, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7484, predictive_accuracy: 0.7539, prior_entropy: 0.9335, recall: 0.7539, relative_absolute_error: 0.5455, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4828, root_relative_squared_error: 1.013, scimark_benchmark: 932.5791,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.824, build_cpu_time: 0.13, build_memory: 118350897.3125, f_measure: 0.7546, kappa: 0.4504, kb_relative_information_score: 226.8989, mean_absolute_error: 0.3284, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7556, predictive_accuracy: 0.7617, prior_entropy: 0.9335, recall: 0.7617, relative_absolute_error: 0.7227, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3999, root_relative_squared_error: 0.8389, scimark_benchmark: 937.52,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7819, build_cpu_time: 0.0175, build_memory: 2037577180.1563, f_measure: 0.7192, kappa: 0.3673, kb_relative_information_score: 166.4072, mean_absolute_error: 0.3649, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7278, predictive_accuracy: 0.7357, prior_entropy: 0.9335, recall: 0.7357, relative_absolute_error: 0.8028, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4218, root_relative_squared_error: 0.8849, scimark_benchmark: 941.0301,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7828, build_cpu_time: 0.0369, build_memory: 125493141.5208, f_measure: 0.7203, kappa: 0.3699, kb_relative_information_score: 165.9679, mean_absolute_error: 0.3653, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7295, predictive_accuracy: 0.737, prior_entropy: 0.9335, recall: 0.737, relative_absolute_error: 0.8037, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4214, root_relative_squared_error: 0.884, scimark_benchmark: 915.7224,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.832, build_cpu_time: 9.7602, build_memory: 158182166.6979, f_measure: 0.7514, kappa: 0.4484, kb_relative_information_score: 271.6557, mean_absolute_error: 0.2957, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7501, predictive_accuracy: 0.7539, prior_entropy: 0.9335, recall: 0.7539, relative_absolute_error: 0.6506, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3986, root_relative_squared_error: 0.8362, scimark_benchmark: 1212.2248,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8259, build_cpu_time: 2.7929, build_memory: 52819380.6875, f_measure: 0.7569, kappa: 0.461, kb_relative_information_score: 274.3843, mean_absolute_error: 0.2934, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7557, predictive_accuracy: 0.7591, prior_entropy: 0.9335, recall: 0.7591, relative_absolute_error: 0.6456, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4036, root_relative_squared_error: 0.8468, scimark_benchmark: 942.6348,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7815, build_cpu_time: 0.0027, build_memory: 1260670809.2917, f_measure: 0.7229, kappa: 0.3759, kb_relative_information_score: 166.7234, mean_absolute_error: 0.3644, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7306, predictive_accuracy: 0.7383, prior_entropy: 0.9335, recall: 0.7383, relative_absolute_error: 0.8017, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4208, root_relative_squared_error: 0.8829, scimark_benchmark: 938.259,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7878, build_cpu_time: 0.7192, build_memory: 30170798.2292, f_measure: 0.7606, kappa: 0.4643, kb_relative_information_score: 337.075, mean_absolute_error: 0.2488, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7612, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.5474, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.453, root_relative_squared_error: 0.9505, scimark_benchmark: 942.728,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7819, build_cpu_time: 0.0051, build_memory: 117448478.3333, f_measure: 0.7127, kappa: 0.3526, kb_relative_information_score: 167.0349, mean_absolute_error: 0.3645, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7265, predictive_accuracy: 0.7331, prior_entropy: 0.9335, recall: 0.7331, relative_absolute_error: 0.802, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4208, root_relative_squared_error: 0.8829, scimark_benchmark: 939.0518,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7835, build_cpu_time: 0.0119, build_memory: 689640459.8958, f_measure: 0.7213, kappa: 0.3722, kb_relative_information_score: 165.1981, mean_absolute_error: 0.3653, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7291, predictive_accuracy: 0.737, prior_entropy: 0.9335, recall: 0.737, relative_absolute_error: 0.8038, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4215, root_relative_squared_error: 0.8843, scimark_benchmark: 906.33,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8338, build_cpu_time: 151.7227, build_memory: 800784081.9792, f_measure: 0.7701, kappa: 0.4901, kb_relative_information_score: 288.706, mean_absolute_error: 0.2847, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.769, predictive_accuracy: 0.7721, prior_entropy: 0.9335, recall: 0.7721, relative_absolute_error: 0.6264, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3999, root_relative_squared_error: 0.8389, scimark_benchmark: 949.7836,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8324, build_cpu_time: 63.4879, build_memory: 3267570963.2604, f_measure: 0.7629, kappa: 0.4732, kb_relative_information_score: 290.2424, mean_absolute_error: 0.2835, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7617, predictive_accuracy: 0.7656, prior_entropy: 0.9335, recall: 0.7656, relative_absolute_error: 0.6237, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.401, root_relative_squared_error: 0.8412, scimark_benchmark: 944.3501,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8136, build_cpu_time: 0.0105, build_memory: 179468616.9583, f_measure: 0.7556, kappa: 0.4562, kb_relative_information_score: 278.2263, mean_absolute_error: 0.2882, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7544, predictive_accuracy: 0.7591, prior_entropy: 0.9335, recall: 0.7591, relative_absolute_error: 0.6341, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4208, root_relative_squared_error: 0.8828, scimark_benchmark: 929.8459,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8146, build_cpu_time: 0.16, build_memory: 715778552.1667, f_measure: 0.7518, kappa: 0.4479, kb_relative_information_score: 275.6253, mean_absolute_error: 0.2898, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7505, predictive_accuracy: 0.7552, prior_entropy: 0.9335, recall: 0.7552, relative_absolute_error: 0.6377, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4192, root_relative_squared_error: 0.8795, scimark_benchmark: 927.7693,

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