OpenML
Supervised Classification on diabetes

Supervised Classification on diabetes

Task 267 Supervised Classification diabetes 373 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8249, f_measure: 0.7364, kappa: 0.4256, kb_relative_information_score: 91.4903, mean_absolute_error: 0.296, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7351, predictive_accuracy: 0.7391, prior_entropy: 0.9335, recall: 0.7391, relative_absolute_error: 0.6449, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4079, root_relative_squared_error: 0.8476, scimark_benchmark: 1304.9611, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8136, f_measure: 0.7312, kappa: 0.4193, kb_relative_information_score: 84.8678, mean_absolute_error: 0.3071, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7312, predictive_accuracy: 0.7312, prior_entropy: 0.9335, recall: 0.7312, relative_absolute_error: 0.6692, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4163, root_relative_squared_error: 0.865, scimark_benchmark: 889.3151, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8054, f_measure: 0.7212, kappa: 0.3937, kb_relative_information_score: 82.9796, mean_absolute_error: 0.3105, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7199, predictive_accuracy: 0.7233, prior_entropy: 0.9335, recall: 0.7233, relative_absolute_error: 0.6766, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4195, root_relative_squared_error: 0.8718, scimark_benchmark: 915.9324, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7644, f_measure: 0.7177, kappa: 0.382, kb_relative_information_score: 80.1785, mean_absolute_error: 0.3108, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7167, predictive_accuracy: 0.7233, prior_entropy: 0.9335, recall: 0.7233, relative_absolute_error: 0.6773, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4386, root_relative_squared_error: 0.9113, scimark_benchmark: 930.5999, usercpu_time_millis: 110, usercpu_time_millis_testing: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7414, f_measure: 0.7035, kappa: 0.3529, kb_relative_information_score: 79.4257, mean_absolute_error: 0.3085, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7018, predictive_accuracy: 0.7075, prior_entropy: 0.9335, recall: 0.7075, relative_absolute_error: 0.6723, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4599, root_relative_squared_error: 0.9557, scimark_benchmark: 889.3151, usercpu_time_millis: 100, usercpu_time_millis_testing: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7539, f_measure: 0.7583, kappa: 0.4895, kb_relative_information_score: 114.5194, mean_absolute_error: 0.2451, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7677, predictive_accuracy: 0.7549, prior_entropy: 0.9335, recall: 0.7549, relative_absolute_error: 0.534, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.495, root_relative_squared_error: 1.0286, scimark_benchmark: 1313.9994, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4949, kb_relative_information_score: 45.8317, mean_absolute_error: 0.3636, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.405, predictive_accuracy: 0.6364, prior_entropy: 0.9335, recall: 0.6364, relative_absolute_error: 0.7924, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.603, root_relative_squared_error: 1.253, scimark_benchmark: 1304.9611, usercpu_time_millis: 590, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 540,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7329, f_measure: 0.7697, kappa: 0.4934, kb_relative_information_score: 128.2569, mean_absolute_error: 0.2213, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7768, predictive_accuracy: 0.7787, prior_entropy: 0.9335, recall: 0.7787, relative_absolute_error: 0.4823, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4705, root_relative_squared_error: 0.9776, scimark_benchmark: 1287.514, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8411, f_measure: 0.7653, kappa: 0.4855, kb_relative_information_score: 87.0961, mean_absolute_error: 0.311, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7665, predictive_accuracy: 0.7708, prior_entropy: 0.9335, recall: 0.7708, relative_absolute_error: 0.6777, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.3939, root_relative_squared_error: 0.8186, scimark_benchmark: 1321.527, usercpu_time_millis: 100, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4949, kb_relative_information_score: 45.8317, mean_absolute_error: 0.3636, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.405, predictive_accuracy: 0.6364, prior_entropy: 0.9335, recall: 0.6364, relative_absolute_error: 0.7924, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.603, root_relative_squared_error: 1.253, scimark_benchmark: 1386.5717, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8375, f_measure: 0.7567, kappa: 0.4704, kb_relative_information_score: 89.5775, mean_absolute_error: 0.3032, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7557, predictive_accuracy: 0.7589, prior_entropy: 0.9335, recall: 0.7589, relative_absolute_error: 0.6607, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.3977, root_relative_squared_error: 0.8264, scimark_benchmark: 1355.9413, usercpu_time_millis: 4470, usercpu_time_millis_testing: 80, usercpu_time_millis_training: 4390,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8093, f_measure: 0.7507, kappa: 0.4607, kb_relative_information_score: 87.3794, mean_absolute_error: 0.3057, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7504, predictive_accuracy: 0.751, prior_entropy: 0.9335, recall: 0.751, relative_absolute_error: 0.6661, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4156, root_relative_squared_error: 0.8635, scimark_benchmark: 1309.3173, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8142, f_measure: 0.7592, kappa: 0.4802, kb_relative_information_score: 82.5776, mean_absolute_error: 0.3131, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7595, predictive_accuracy: 0.7589, prior_entropy: 0.9335, recall: 0.7589, relative_absolute_error: 0.6822, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4114, root_relative_squared_error: 0.8548, scimark_benchmark: 1304.6687, usercpu_time_millis: 260, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 230,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6452, f_measure: 0.6665, kappa: 0.2857, kb_relative_information_score: 61.8588, mean_absolute_error: 0.336, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.6699, predictive_accuracy: 0.664, prior_entropy: 0.9335, recall: 0.664, relative_absolute_error: 0.7321, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.5796, root_relative_squared_error: 1.2044, scimark_benchmark: 825.5282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7846, f_measure: 0.7347, kappa: 0.4201, kb_relative_information_score: 81.6748, mean_absolute_error: 0.3168, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7338, predictive_accuracy: 0.7391, prior_entropy: 0.9335, recall: 0.7391, relative_absolute_error: 0.6904, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4289, root_relative_squared_error: 0.8912, scimark_benchmark: 1325.942, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6859, f_measure: 0.7319, kappa: 0.4117, kb_relative_information_score: 68.9627, mean_absolute_error: 0.3451, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7328, predictive_accuracy: 0.7391, prior_entropy: 0.9335, recall: 0.7391, relative_absolute_error: 0.752, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4463, root_relative_squared_error: 0.9274, scimark_benchmark: 1354.2491, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7089, f_measure: 0.7364, kappa: 0.4256, kb_relative_information_score: 105.361, mean_absolute_error: 0.2609, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7351, predictive_accuracy: 0.7391, prior_entropy: 0.9335, recall: 0.7391, relative_absolute_error: 0.5685, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.5108, root_relative_squared_error: 1.0613, scimark_benchmark: 825.5282, usercpu_time_millis: 140, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5877, f_measure: 0.6321, kappa: 0.2023, kb_relative_information_score: 71.0172, mean_absolute_error: 0.3202, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.6739, predictive_accuracy: 0.6798, prior_entropy: 0.9335, recall: 0.6798, relative_absolute_error: 0.6976, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.5658, root_relative_squared_error: 1.1757, scimark_benchmark: 1368.9272, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7752, f_measure: 0.7202, kappa: 0.4151, kb_relative_information_score: 77.6263, mean_absolute_error: 0.3185, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7356, predictive_accuracy: 0.7154, prior_entropy: 0.9335, recall: 0.7154, relative_absolute_error: 0.694, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4395, root_relative_squared_error: 0.9132, scimark_benchmark: 1384.4418, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6669, f_measure: 0.7052, kappa: 0.3519, kb_relative_information_score: 91.6235, mean_absolute_error: 0.2846, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7067, predictive_accuracy: 0.7154, prior_entropy: 0.9335, recall: 0.7154, relative_absolute_error: 0.6201, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.5335, root_relative_squared_error: 1.1085, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6778, f_measure: 0.7242, kappa: 0.3941, kb_relative_information_score: 109.9402, mean_absolute_error: 0.253, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7539, predictive_accuracy: 0.747, prior_entropy: 0.9335, recall: 0.747, relative_absolute_error: 0.5512, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.503, root_relative_squared_error: 1.0451, scimark_benchmark: 977.6382, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4949, kb_relative_information_score: 1.1396, mean_absolute_error: 0.457, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.405, predictive_accuracy: 0.6364, prior_entropy: 0.9335, recall: 0.6364, relative_absolute_error: 0.9958, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4815, root_relative_squared_error: 1.0005, scimark_benchmark: 1054.3694,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6658, f_measure: 0.7132, kappa: 0.3764, kb_relative_information_score: 59.0182, mean_absolute_error: 0.3603, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7119, predictive_accuracy: 0.7154, prior_entropy: 0.9335, recall: 0.7154, relative_absolute_error: 0.7852, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4672, root_relative_squared_error: 0.9708, scimark_benchmark: 1054.3694, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8151, build_cpu_time: 0.146, build_memory: 222972232, f_measure: 0.7753, kappa: 0.5061, kb_relative_information_score: 97.8702, mean_absolute_error: 0.291, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7801, predictive_accuracy: 0.7826, prior_entropy: 0.9335, recall: 0.7826, relative_absolute_error: 0.6342, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4087, root_relative_squared_error: 0.8493, scimark_benchmark: 943.0278,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8151, build_cpu_time: 0.119, build_memory: 1805031320, f_measure: 0.7753, kappa: 0.5061, kb_relative_information_score: 97.8702, mean_absolute_error: 0.291, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7801, predictive_accuracy: 0.7826, prior_entropy: 0.9335, recall: 0.7826, relative_absolute_error: 0.6342, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4087, root_relative_squared_error: 0.8493, scimark_benchmark: 938.8409,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8151, build_cpu_time: 0.16, build_memory: 907928648, f_measure: 0.7753, kappa: 0.5061, kb_relative_information_score: 97.8702, mean_absolute_error: 0.291, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7801, predictive_accuracy: 0.7826, prior_entropy: 0.9335, recall: 0.7826, relative_absolute_error: 0.6342, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4087, root_relative_squared_error: 0.8493, scimark_benchmark: 940.5101,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8151, build_cpu_time: 0.118, build_memory: 1062438472, f_measure: 0.7753, kappa: 0.5061, kb_relative_information_score: 97.8702, mean_absolute_error: 0.291, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7801, predictive_accuracy: 0.7826, prior_entropy: 0.9335, recall: 0.7826, relative_absolute_error: 0.6342, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4087, root_relative_squared_error: 0.8493, scimark_benchmark: 874.2668,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8151, build_cpu_time: 0.099, build_memory: 236363296, f_measure: 0.7753, kappa: 0.5061, kb_relative_information_score: 96.8151, mean_absolute_error: 0.293, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7801, predictive_accuracy: 0.7826, prior_entropy: 0.9335, recall: 0.7826, relative_absolute_error: 0.6385, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4087, root_relative_squared_error: 0.8492, scimark_benchmark: 941.7846,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7642, build_cpu_time: 0.041, build_memory: 1042475840, f_measure: 0.69, kappa: 0.3361, kb_relative_information_score: 81.0246, mean_absolute_error: 0.3031, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.6933, predictive_accuracy: 0.6877, prior_entropy: 0.9335, recall: 0.6877, relative_absolute_error: 0.6604, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4793, root_relative_squared_error: 0.996, scimark_benchmark: 936.5273,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7549, build_cpu_time: 0.083, build_memory: 186771528, f_measure: 0.6937, kappa: 0.3346, kb_relative_information_score: 84.0237, mean_absolute_error: 0.2992, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.6924, predictive_accuracy: 0.6957, prior_entropy: 0.9335, recall: 0.6957, relative_absolute_error: 0.652, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4886, root_relative_squared_error: 1.0152, scimark_benchmark: 935.1201,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7831, build_cpu_time: 0.178, build_memory: 408809736, f_measure: 0.7111, kappa: 0.3751, kb_relative_information_score: 89.7014, mean_absolute_error: 0.2878, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7108, predictive_accuracy: 0.7115, prior_entropy: 0.9335, recall: 0.7115, relative_absolute_error: 0.6272, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.5024, root_relative_squared_error: 1.0439, scimark_benchmark: 942.573,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7933, build_cpu_time: 0.359, build_memory: 623785696, f_measure: 0.7263, kappa: 0.4066, kb_relative_information_score: 95.0625, mean_absolute_error: 0.2794, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7255, predictive_accuracy: 0.7273, prior_entropy: 0.9335, recall: 0.7273, relative_absolute_error: 0.6089, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.5015, root_relative_squared_error: 1.042, scimark_benchmark: 895.3841,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7933, build_cpu_time: 0.318, build_memory: 86307200, f_measure: 0.7263, kappa: 0.4066, kb_relative_information_score: 95.0625, mean_absolute_error: 0.2794, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7255, predictive_accuracy: 0.7273, prior_entropy: 0.9335, recall: 0.7273, relative_absolute_error: 0.6089, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.5015, root_relative_squared_error: 1.042, scimark_benchmark: 882.4531,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6537, build_cpu_time: 0.006, build_memory: 580428672, f_measure: 0.6822, kappa: 0.3103, kb_relative_information_score: 73.3068, mean_absolute_error: 0.3162, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.681, predictive_accuracy: 0.6838, prior_entropy: 0.9335, recall: 0.6838, relative_absolute_error: 0.689, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.5623, root_relative_squared_error: 1.1684, scimark_benchmark: 926.507,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6537, build_cpu_time: 0.007, build_memory: 2108903920, f_measure: 0.6822, kappa: 0.3103, kb_relative_information_score: 73.3068, mean_absolute_error: 0.3162, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.681, predictive_accuracy: 0.6838, prior_entropy: 0.9335, recall: 0.6838, relative_absolute_error: 0.689, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.5623, root_relative_squared_error: 1.1684, scimark_benchmark: 934.6076,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6537, build_cpu_time: 0.005, build_memory: 2837435344, f_measure: 0.6822, kappa: 0.3103, kb_relative_information_score: 73.3068, mean_absolute_error: 0.3162, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.681, predictive_accuracy: 0.6838, prior_entropy: 0.9335, recall: 0.6838, relative_absolute_error: 0.689, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.5623, root_relative_squared_error: 1.1684, scimark_benchmark: 946.9091,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6537, build_cpu_time: 0.006, build_memory: 1044743392, f_measure: 0.6822, kappa: 0.3103, kb_relative_information_score: 73.3068, mean_absolute_error: 0.3162, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.681, predictive_accuracy: 0.6838, prior_entropy: 0.9335, recall: 0.6838, relative_absolute_error: 0.689, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.5623, root_relative_squared_error: 1.1684, scimark_benchmark: 946.9091,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7857, build_cpu_time: 0.556, build_memory: 1476837664, f_measure: 0.7439, kappa: 0.4487, kb_relative_information_score: 99.9287, mean_absolute_error: 0.2721, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.745, predictive_accuracy: 0.7431, prior_entropy: 0.9335, recall: 0.7431, relative_absolute_error: 0.5929, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4879, root_relative_squared_error: 1.0139, scimark_benchmark: 943.521,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5008, build_cpu_time: 0.037, build_memory: 1825778712, f_measure: 0.209, kappa: 0.0011, kb_relative_information_score: -109.8603, mean_absolute_error: 0.6324, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.5566, predictive_accuracy: 0.3676, prior_entropy: 0.9335, recall: 0.3676, relative_absolute_error: 1.3781, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.7952, root_relative_squared_error: 1.6524, scimark_benchmark: 933.9469,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8019, build_cpu_time: 0.003, build_memory: 1859069488, f_measure: 0.714, kappa: 0.3793, kb_relative_information_score: 83.332, mean_absolute_error: 0.308, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7129, predictive_accuracy: 0.7154, prior_entropy: 0.9335, recall: 0.7154, relative_absolute_error: 0.6712, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4242, root_relative_squared_error: 0.8815, scimark_benchmark: 918.4301,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8019, build_cpu_time: 0.003, build_memory: 417367968, f_measure: 0.714, kappa: 0.3793, kb_relative_information_score: 83.9976, mean_absolute_error: 0.3062, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7129, predictive_accuracy: 0.7154, prior_entropy: 0.9335, recall: 0.7154, relative_absolute_error: 0.6673, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4276, root_relative_squared_error: 0.8884, scimark_benchmark: 942.4411,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8142, build_cpu_time: 0.249, build_memory: 358771632, f_measure: 0.7592, kappa: 0.4802, kb_relative_information_score: 82.5776, mean_absolute_error: 0.3131, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7595, predictive_accuracy: 0.7589, prior_entropy: 0.9335, recall: 0.7589, relative_absolute_error: 0.6822, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4114, root_relative_squared_error: 0.8548, scimark_benchmark: 875.7999,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6879, build_cpu_time: 0.01, build_memory: 85017024, f_measure: 0.7057, kappa: 0.3697, kb_relative_information_score: 53.9618, mean_absolute_error: 0.3675, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7089, predictive_accuracy: 0.7036, prior_entropy: 0.9335, recall: 0.7036, relative_absolute_error: 0.8009, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4627, root_relative_squared_error: 0.9615, scimark_benchmark: 937.1859,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6421, build_memory: 210300048, f_measure: 0.6774, kappa: 0.2937, kb_relative_information_score: 73.0285, mean_absolute_error: 0.3169, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.6752, predictive_accuracy: 0.6838, prior_entropy: 0.9335, recall: 0.6838, relative_absolute_error: 0.6906, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.5612, root_relative_squared_error: 1.1662, scimark_benchmark: 943.1817,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7329, build_cpu_time: 0.012, build_memory: 1297211616, f_measure: 0.7697, kappa: 0.4934, kb_relative_information_score: 128.2569, mean_absolute_error: 0.2213, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7768, predictive_accuracy: 0.7787, prior_entropy: 0.9335, recall: 0.7787, relative_absolute_error: 0.4823, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4705, root_relative_squared_error: 0.9776, scimark_benchmark: 940.4464,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7391, build_cpu_time: 0.042, build_memory: 22970648, f_measure: 0.7697, kappa: 0.4956, kb_relative_information_score: 125.9673, mean_absolute_error: 0.2253, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7707, predictive_accuracy: 0.7747, prior_entropy: 0.9335, recall: 0.7747, relative_absolute_error: 0.4909, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4747, root_relative_squared_error: 0.9863, scimark_benchmark: 926.8365,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8409, build_cpu_time: 0.018, build_memory: 36603576, f_measure: 0.7689, kappa: 0.4931, kb_relative_information_score: 87.4031, mean_absolute_error: 0.3104, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7708, predictive_accuracy: 0.7747, prior_entropy: 0.9335, recall: 0.7747, relative_absolute_error: 0.6763, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.3939, root_relative_squared_error: 0.8185, scimark_benchmark: 947.9978,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8137, build_cpu_time: 0.001, build_memory: 501659448, f_measure: 0.7617, kappa: 0.4828, kb_relative_information_score: 97.6378, mean_absolute_error: 0.2858, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7609, predictive_accuracy: 0.7628, prior_entropy: 0.9335, recall: 0.7628, relative_absolute_error: 0.6228, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4198, root_relative_squared_error: 0.8723, scimark_benchmark: 940.7816,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8054, build_cpu_time: 0.018, build_memory: 246688520, f_measure: 0.7212, kappa: 0.3937, kb_relative_information_score: 82.9796, mean_absolute_error: 0.3105, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7199, predictive_accuracy: 0.7233, prior_entropy: 0.9335, recall: 0.7233, relative_absolute_error: 0.6766, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4195, root_relative_squared_error: 0.8718, scimark_benchmark: 930.1524,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6669, build_cpu_time: 0.001, build_memory: 446649128, f_measure: 0.7052, kappa: 0.3519, kb_relative_information_score: 91.6235, mean_absolute_error: 0.2846, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7067, predictive_accuracy: 0.7154, prior_entropy: 0.9335, recall: 0.7154, relative_absolute_error: 0.6201, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.5335, root_relative_squared_error: 1.1085, scimark_benchmark: 929.8725,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6669, build_cpu_time: 0.002, build_memory: 330349616, f_measure: 0.7052, kappa: 0.3519, kb_relative_information_score: 91.6235, mean_absolute_error: 0.2846, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7067, predictive_accuracy: 0.7154, prior_entropy: 0.9335, recall: 0.7154, relative_absolute_error: 0.6201, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.5335, root_relative_squared_error: 1.1085, scimark_benchmark: 946.3269,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6658, build_cpu_time: 0.007, build_memory: 584219656, f_measure: 0.7132, kappa: 0.3764, kb_relative_information_score: 59.0182, mean_absolute_error: 0.3603, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7119, predictive_accuracy: 0.7154, prior_entropy: 0.9335, recall: 0.7154, relative_absolute_error: 0.7852, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4672, root_relative_squared_error: 0.9708, scimark_benchmark: 946.9694,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6658, build_cpu_time: 0.007, build_memory: 639596288, f_measure: 0.7132, kappa: 0.3764, kb_relative_information_score: 59.0182, mean_absolute_error: 0.3603, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.7119, predictive_accuracy: 0.7154, prior_entropy: 0.9335, recall: 0.7154, relative_absolute_error: 0.7852, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.4672, root_relative_squared_error: 0.9708, scimark_benchmark: 922.5645,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5411, build_cpu_time: 0.001, build_memory: 130118136, f_measure: 0.5741, kappa: 0.0819, kb_relative_information_score: 9.1983, mean_absolute_error: 0.4269, mean_prior_absolute_error: 0.4589, number_of_instances: 253, precision: 0.5751, predictive_accuracy: 0.5731, prior_entropy: 0.9335, recall: 0.5731, relative_absolute_error: 0.9302, root_mean_prior_squared_error: 0.4813, root_mean_squared_error: 0.6534, root_relative_squared_error: 1.3576, scimark_benchmark: 941.5087,

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