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File: /var/www/openml/openml_OS/core/MY_Database_Read_Model.php
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File: /var/www/openml/index.php
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Function: require_once

OpenML
OpenML
Supervised Classification on diabetes

Supervised Classification on diabetes

Task 37 Supervised Classification diabetes 131649 runs submitted
0 likes downloaded by 11 people , 15 total downloads 0 issues
Visibility: Public
  • 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: 0.7989, build_cpu_time: 0.2169, build_memory: 1220867331.5313, f_measure: 0.7424, kappa: 0.4252, kb_relative_information_score: 276.0025, mean_absolute_error: 0.2875, 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: 0.6327, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4333, root_relative_squared_error: 0.9092, scimark_benchmark: 933.4498,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.792, build_cpu_time: 0.2065, build_memory: 715146939.9896, f_measure: 0.7441, kappa: 0.428, kb_relative_information_score: 267.933, mean_absolute_error: 0.2927, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7435, predictive_accuracy: 0.75, prior_entropy: 0.9335, recall: 0.75, relative_absolute_error: 0.6441, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4359, root_relative_squared_error: 0.9146, scimark_benchmark: 920.7965,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7857, build_cpu_time: 0.166, build_memory: 233950448.4375, f_measure: 0.7383, kappa: 0.4192, kb_relative_information_score: 308.7158, mean_absolute_error: 0.2618, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7368, predictive_accuracy: 0.7409, prior_entropy: 0.9335, recall: 0.7409, relative_absolute_error: 0.5761, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.487, root_relative_squared_error: 1.0217, scimark_benchmark: 902.712,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7828, build_cpu_time: 0.3482, build_memory: 151353100.5208, f_measure: 0.7433, kappa: 0.4298, kb_relative_information_score: 318.0505, mean_absolute_error: 0.2564, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7418, predictive_accuracy: 0.7461, prior_entropy: 0.9335, recall: 0.7461, relative_absolute_error: 0.5642, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4934, root_relative_squared_error: 1.0352, scimark_benchmark: 934.6076,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.742, build_cpu_time: 0.5951, build_memory: 777053022.6042, f_measure: 0.7418, kappa: 0.4264, kb_relative_information_score: 320.5221, mean_absolute_error: 0.2544, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7403, predictive_accuracy: 0.7448, prior_entropy: 0.9335, recall: 0.7448, relative_absolute_error: 0.5597, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4977, root_relative_squared_error: 1.0442, scimark_benchmark: 936.1433,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7413, build_cpu_time: 1.0354, build_memory: 100097770.625, f_measure: 0.7412, kappa: 0.426, kb_relative_information_score: 315.3666, mean_absolute_error: 0.2575, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7398, predictive_accuracy: 0.7435, prior_entropy: 0.9335, recall: 0.7435, relative_absolute_error: 0.5665, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.504, root_relative_squared_error: 1.0574, scimark_benchmark: 925.481,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7332, build_cpu_time: 1.9146, build_memory: 370782532.8021, f_measure: 0.7427, kappa: 0.4278, kb_relative_information_score: 319.6347, mean_absolute_error: 0.255, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7412, predictive_accuracy: 0.7461, prior_entropy: 0.9335, recall: 0.7461, relative_absolute_error: 0.5611, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5015, root_relative_squared_error: 1.0522, scimark_benchmark: 937.6343,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6725, build_cpu_time: 0.0693, build_memory: 397077949.1667, f_measure: 0.7006, kappa: 0.3363, kb_relative_information_score: 244.9883, mean_absolute_error: 0.2975, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.6988, predictive_accuracy: 0.7031, prior_entropy: 0.9335, recall: 0.7031, relative_absolute_error: 0.6545, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5441, root_relative_squared_error: 1.1415, scimark_benchmark: 937.279,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6725, build_cpu_time: 0.0434, build_memory: 103219853.4583, f_measure: 0.7006, kappa: 0.3363, kb_relative_information_score: 244.9883, mean_absolute_error: 0.2975, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.6988, predictive_accuracy: 0.7031, prior_entropy: 0.9335, recall: 0.7031, relative_absolute_error: 0.6545, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5441, root_relative_squared_error: 1.1415, scimark_benchmark: 943.4024,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6725, build_cpu_time: 0.0638, build_memory: 144131009.2188, f_measure: 0.7006, kappa: 0.3363, kb_relative_information_score: 244.9883, mean_absolute_error: 0.2975, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.6988, predictive_accuracy: 0.7031, prior_entropy: 0.9335, recall: 0.7031, relative_absolute_error: 0.6545, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5441, root_relative_squared_error: 1.1415, scimark_benchmark: 923.8078,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8231, build_cpu_time: 0.1178, build_memory: 370561853.7188, f_measure: 0.7479, kappa: 0.4364, kb_relative_information_score: 269.5882, mean_absolute_error: 0.2956, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7476, predictive_accuracy: 0.7539, prior_entropy: 0.9335, recall: 0.7539, relative_absolute_error: 0.6504, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4072, root_relative_squared_error: 0.8543, scimark_benchmark: 937.279,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8238, build_cpu_time: 0.2414, build_memory: 550081863.3021, f_measure: 0.7486, kappa: 0.4385, kb_relative_information_score: 277.0021, mean_absolute_error: 0.2907, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7479, predictive_accuracy: 0.7539, prior_entropy: 0.9335, recall: 0.7539, relative_absolute_error: 0.6395, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4068, root_relative_squared_error: 0.8535, scimark_benchmark: 873.8637,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7694, build_cpu_time: 2.2185, build_memory: 2996244116.8021, f_measure: 0.7266, kappa: 0.3915, kb_relative_information_score: 296.0914, mean_absolute_error: 0.2679, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7248, predictive_accuracy: 0.7305, prior_entropy: 0.9335, recall: 0.7305, relative_absolute_error: 0.5894, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.507, root_relative_squared_error: 1.0636, scimark_benchmark: 909.8271,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7693, build_cpu_time: 1.1811, build_memory: 1154207047.3333, f_measure: 0.7151, kappa: 0.3668, kb_relative_information_score: 284.5913, mean_absolute_error: 0.2747, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7132, predictive_accuracy: 0.7188, prior_entropy: 0.9335, recall: 0.7188, relative_absolute_error: 0.6044, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.505, root_relative_squared_error: 1.0594, scimark_benchmark: 874.7324,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7729, build_cpu_time: 0.6062, build_memory: 222703515.9271, f_measure: 0.7087, kappa: 0.3571, kb_relative_information_score: 264.1062, mean_absolute_error: 0.286, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7079, predictive_accuracy: 0.7096, prior_entropy: 0.9335, recall: 0.7096, relative_absolute_error: 0.6292, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4925, root_relative_squared_error: 1.0332, scimark_benchmark: 937.4026,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4764, build_cpu_time: 0.0461, build_memory: 397940946.9063, f_measure: 0.2263, kappa: -0.034, kb_relative_information_score: -381.6627, mean_absolute_error: 0.6536, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.4297, predictive_accuracy: 0.3464, prior_entropy: 0.9335, recall: 0.3464, relative_absolute_error: 1.4382, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.8085, root_relative_squared_error: 1.6962, scimark_benchmark: 945.384,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8016, build_cpu_time: 0.3022, build_memory: 509761821.1146, f_measure: 0.7442, kappa: 0.4313, kb_relative_information_score: 281.2266, mean_absolute_error: 0.2845, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7427, predictive_accuracy: 0.7474, prior_entropy: 0.9335, recall: 0.7474, relative_absolute_error: 0.626, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4294, root_relative_squared_error: 0.9008, scimark_benchmark: 935.37,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8149, build_cpu_time: 0.004, build_memory: 478727384, f_measure: 0.7614, kappa: 0.4698, kb_relative_information_score: 264.6413, mean_absolute_error: 0.2986, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7603, predictive_accuracy: 0.7643, prior_entropy: 0.9335, recall: 0.7643, relative_absolute_error: 0.6571, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.41, root_relative_squared_error: 0.8602, scimark_benchmark: 945.7844,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.83, build_cpu_time: 0.2168, build_memory: 526709167.8021, f_measure: 0.7638, kappa: 0.4748, kb_relative_information_score: 257.3874, mean_absolute_error: 0.3063, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7627, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.6739, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3976, root_relative_squared_error: 0.8343, scimark_benchmark: 936.8995,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7269, build_cpu_time: 0.0326, build_memory: 814412582.5, f_measure: 0.7465, kappa: 0.4345, kb_relative_information_score: 201.2167, mean_absolute_error: 0.3459, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7455, predictive_accuracy: 0.7513, prior_entropy: 0.9335, recall: 0.7513, relative_absolute_error: 0.7612, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.43, root_relative_squared_error: 0.9022, scimark_benchmark: 931.9838,
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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,
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,
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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: 0.8195, f_measure: 0.7585, kappa: 0.463, kb_relative_information_score: 0.3205, mean_absolute_error: 0.3121, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7573, predictive_accuracy: 0.7617, prior_entropy: 0.9331, recall: 0.7617, relative_absolute_error: 0.6868, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4035, root_relative_squared_error: 0.8466,
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: 0.7828, 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: 0.7819, 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: 0.7835, 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: 0.7878, 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,
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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: 0.832, 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: 0.8351, build_cpu_time: 11.7798, build_memory: 88531679.3542, f_measure: 0.7638, kappa: 0.4748, kb_relative_information_score: 270.6885, mean_absolute_error: 0.2971, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7627, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.6538, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3964, root_relative_squared_error: 0.8317, scimark_benchmark: 938.259,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8195, f_measure: 0.7585, kappa: 0.463, kb_relative_information_score: 0.3205, mean_absolute_error: 0.3121, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7573, predictive_accuracy: 0.7617, prior_entropy: 0.9331, recall: 0.7617, relative_absolute_error: 0.6868, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4035, root_relative_squared_error: 0.8466,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8331, build_cpu_time: 21.4846, build_memory: 3408018626.7917, f_measure: 0.76, kappa: 0.4664, kb_relative_information_score: 268.1478, mean_absolute_error: 0.2987, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7588, predictive_accuracy: 0.763, prior_entropy: 0.9335, recall: 0.763, relative_absolute_error: 0.6573, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3969, root_relative_squared_error: 0.8327, scimark_benchmark: 945.8425,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8321, build_cpu_time: 44.3541, build_memory: 503882429.6563, f_measure: 0.7658, kappa: 0.48, kb_relative_information_score: 267.0432, mean_absolute_error: 0.2995, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7646, predictive_accuracy: 0.7682, prior_entropy: 0.9335, recall: 0.7682, relative_absolute_error: 0.6591, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3972, root_relative_squared_error: 0.8333, scimark_benchmark: 941.2105,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7924, build_cpu_time: 4.6814, build_memory: 595546328.6979, f_measure: 0.7579, kappa: 0.4648, kb_relative_information_score: 340.3045, mean_absolute_error: 0.2437, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.757, predictive_accuracy: 0.7591, prior_entropy: 0.9335, recall: 0.7591, relative_absolute_error: 0.5361, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4781, root_relative_squared_error: 1.003, scimark_benchmark: 897.921,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8166, build_cpu_time: 2.0639, build_memory: 272949030.5833, f_measure: 0.7615, kappa: 0.472, kb_relative_information_score: 345.9181, mean_absolute_error: 0.2403, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7605, predictive_accuracy: 0.763, prior_entropy: 0.9335, recall: 0.763, relative_absolute_error: 0.5287, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.47, root_relative_squared_error: 0.9861, scimark_benchmark: 938.0657,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8213, build_cpu_time: 1.096, build_memory: 53171710.4167, f_measure: 0.7522, kappa: 0.4513, kb_relative_information_score: 337.6225, mean_absolute_error: 0.2445, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7511, predictive_accuracy: 0.7539, prior_entropy: 0.9335, recall: 0.7539, relative_absolute_error: 0.5379, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.469, root_relative_squared_error: 0.9839, scimark_benchmark: 947.8147,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8213, build_cpu_time: 1.0875, build_memory: 35414184.3438, f_measure: 0.7522, kappa: 0.4513, kb_relative_information_score: 337.6225, mean_absolute_error: 0.2445, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7511, predictive_accuracy: 0.7539, prior_entropy: 0.9335, recall: 0.7539, relative_absolute_error: 0.5379, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.469, root_relative_squared_error: 0.9839, scimark_benchmark: 935.2997,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.825, build_cpu_time: 0.681, build_memory: 1476105315.5833, f_measure: 0.7534, kappa: 0.4537, kb_relative_information_score: 345.3729, mean_absolute_error: 0.2397, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7522, predictive_accuracy: 0.7552, prior_entropy: 0.9335, recall: 0.7552, relative_absolute_error: 0.5273, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4656, root_relative_squared_error: 0.9768, scimark_benchmark: 941.5665,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8268, build_cpu_time: 4.5053, build_memory: 80881482.0938, f_measure: 0.7634, kappa: 0.4686, kb_relative_information_score: 245.7116, mean_absolute_error: 0.3178, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7672, predictive_accuracy: 0.7721, prior_entropy: 0.9335, recall: 0.7721, relative_absolute_error: 0.6993, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3983, root_relative_squared_error: 0.8356, scimark_benchmark: 921.0032,

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