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Function: require_once

OpenML
Task
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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131649 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7564, f_measure: 0.717, kappa: 0.3642, kb_relative_information_score: 140.2899, mean_absolute_error: 0.3802, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7183, predictive_accuracy: 0.7279, prior_entropy: 0.9335, recall: 0.7279, relative_absolute_error: 0.8365, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4292, root_relative_squared_error: 0.9005, scimark_benchmark: 945.3703,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7235, f_measure: 0.748, kappa: 0.438, kb_relative_information_score: 333.5949, mean_absolute_error: 0.2468, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7469, predictive_accuracy: 0.7526, prior_entropy: 0.9335, recall: 0.7526, relative_absolute_error: 0.543, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4959, root_relative_squared_error: 1.0404, scimark_benchmark: 937.1066,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.678, f_measure: 0.7072, kappa: 0.3558, kb_relative_information_score: 252.5531, mean_absolute_error: 0.293, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7073, predictive_accuracy: 0.707, prior_entropy: 0.9335, recall: 0.707, relative_absolute_error: 0.6446, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5413, root_relative_squared_error: 1.1356, scimark_benchmark: 943.8141,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.825, f_measure: 0.7613, kappa: 0.4663, kb_relative_information_score: 253.8842, mean_absolute_error: 0.3134, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7614, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.6896, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3998, root_relative_squared_error: 0.8388, scimark_benchmark: 911.0804,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7832, f_measure: 0.7538, kappa: 0.4532, kb_relative_information_score: 276.1166, mean_absolute_error: 0.2928, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7525, predictive_accuracy: 0.7565, prior_entropy: 0.9335, recall: 0.7565, relative_absolute_error: 0.6442, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4294, root_relative_squared_error: 0.9008, scimark_benchmark: 940.0645,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8098, f_measure: 0.7479, kappa: 0.4364, kb_relative_information_score: 329.8899, mean_absolute_error: 0.2497, 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: 0.5493, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4674, root_relative_squared_error: 0.9806, scimark_benchmark: 942.7017,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7623, f_measure: 0.5134, kb_relative_information_score: 155.6139, mean_absolute_error: 0.3478, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.4239, predictive_accuracy: 0.651, prior_entropy: 0.9335, recall: 0.651, relative_absolute_error: 0.7653, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5688, root_relative_squared_error: 1.1934, scimark_benchmark: 947.571,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7694, 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: 946.0198,
0 likes - 0 downloads - 0 reach - No evaluations yet (or not applicable). Evaluation Engine Exception: Required output files not present (e.g., arff predictions).
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7896, f_measure: 0.7577, kappa: 0.455, kb_relative_information_score: 254.7996, mean_absolute_error: 0.3129, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7636, predictive_accuracy: 0.7682, prior_entropy: 0.9335, recall: 0.7682, relative_absolute_error: 0.6885, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4167, root_relative_squared_error: 0.8743,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.796, f_measure: 0.7513, kappa: 0.4423, kb_relative_information_score: 252.6725, mean_absolute_error: 0.3033, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7527, predictive_accuracy: 0.7591, prior_entropy: 0.9335, recall: 0.7591, relative_absolute_error: 0.6672, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4207, root_relative_squared_error: 0.8827, scimark_benchmark: 944.2848,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7533, f_measure: 0.7088, kappa: 0.3448, kb_relative_information_score: 132.6477, mean_absolute_error: 0.3838, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7121, predictive_accuracy: 0.7227, prior_entropy: 0.9335, recall: 0.7227, relative_absolute_error: 0.8445, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4317, root_relative_squared_error: 0.9056, scimark_benchmark: 941.3955,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8318, f_measure: 0.7526, kappa: 0.4508, kb_relative_information_score: 271.5913, mean_absolute_error: 0.2957, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7513, predictive_accuracy: 0.7552, prior_entropy: 0.9335, recall: 0.7552, relative_absolute_error: 0.6507, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3987, root_relative_squared_error: 0.8365, scimark_benchmark: 942.5279,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7093, f_measure: 0.6605, kappa: 0.2463, kb_relative_information_score: 170.6991, mean_absolute_error: 0.3421, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.658, predictive_accuracy: 0.6641, prior_entropy: 0.9335, recall: 0.6641, relative_absolute_error: 0.7526, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5074, root_relative_squared_error: 1.0645, scimark_benchmark: 928.504,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7937, f_measure: 0.7421, kappa: 0.4204, kb_relative_information_score: 230.3237, mean_absolute_error: 0.3203, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7458, predictive_accuracy: 0.7526, prior_entropy: 0.9335, recall: 0.7526, relative_absolute_error: 0.7048, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4184, root_relative_squared_error: 0.8778, scimark_benchmark: 943.6958,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.786, f_measure: 0.7583, kappa: 0.4621, kb_relative_information_score: 256.9091, mean_absolute_error: 0.3074, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7571, predictive_accuracy: 0.7617, prior_entropy: 0.9335, recall: 0.7617, relative_absolute_error: 0.6764, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4174, root_relative_squared_error: 0.8758, scimark_benchmark: 947.8835,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8143, f_measure: 0.7551, kappa: 0.4543, kb_relative_information_score: 270.0796, mean_absolute_error: 0.2943, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.754, predictive_accuracy: 0.7591, prior_entropy: 0.9335, recall: 0.7591, relative_absolute_error: 0.6475, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.414, root_relative_squared_error: 0.8687, scimark_benchmark: 929.4236,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8232, f_measure: 0.7339, kappa: 0.4008, kb_relative_information_score: 198.9195, mean_absolute_error: 0.3469, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7428, predictive_accuracy: 0.7487, prior_entropy: 0.9335, recall: 0.7487, relative_absolute_error: 0.7633, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4042, root_relative_squared_error: 0.8479, scimark_benchmark: 947.6248,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5134, kb_relative_information_score: 154.1008, mean_absolute_error: 0.349, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.4239, predictive_accuracy: 0.651, prior_entropy: 0.9335, recall: 0.651, relative_absolute_error: 0.7678, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5907, root_relative_squared_error: 1.2394, scimark_benchmark: 944.1551,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8196, f_measure: 0.7453, kappa: 0.4305, kb_relative_information_score: 263.3355, mean_absolute_error: 0.3, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7448, predictive_accuracy: 0.7513, prior_entropy: 0.9335, recall: 0.7513, relative_absolute_error: 0.6601, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4081, root_relative_squared_error: 0.8562, scimark_benchmark: 948.7198,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7889, f_measure: 0.7412, kappa: 0.4227, kb_relative_information_score: 240.7979, mean_absolute_error: 0.3158, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.74, predictive_accuracy: 0.7461, prior_entropy: 0.9335, recall: 0.7461, relative_absolute_error: 0.6949, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4193, root_relative_squared_error: 0.8796,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7428, f_measure: 0.7201, kappa: 0.3794, kb_relative_information_score: 234.2833, mean_absolute_error: 0.309, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7185, predictive_accuracy: 0.7227, prior_entropy: 0.9335, recall: 0.7227, relative_absolute_error: 0.6799, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4618, root_relative_squared_error: 0.9688, scimark_benchmark: 948.5222,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7471, f_measure: 0.7395, kappa: 0.4199, kb_relative_information_score: 259.1108, mean_absolute_error: 0.3016, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.738, predictive_accuracy: 0.7435, prior_entropy: 0.9335, recall: 0.7435, relative_absolute_error: 0.6637, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.444, root_relative_squared_error: 0.9316, scimark_benchmark: 949.5932,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5104, f_measure: 0.5395, kappa: 0.0263, kb_relative_information_score: 154.1008, mean_absolute_error: 0.349, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.6015, predictive_accuracy: 0.651, prior_entropy: 0.9335, recall: 0.651, relative_absolute_error: 0.7678, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5907, root_relative_squared_error: 1.2394, scimark_benchmark: 946.6089,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5134, kb_relative_information_score: 154.1008, mean_absolute_error: 0.349, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.4239, predictive_accuracy: 0.651, prior_entropy: 0.9335, recall: 0.651, relative_absolute_error: 0.7678, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5907, root_relative_squared_error: 1.2394, scimark_benchmark: 945.2628,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7388, f_measure: 0.7395, kappa: 0.4199, kb_relative_information_score: 243.669, mean_absolute_error: 0.3127, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.738, predictive_accuracy: 0.7435, prior_entropy: 0.9335, recall: 0.7435, relative_absolute_error: 0.6881, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4485, root_relative_squared_error: 0.9409, scimark_benchmark: 946.418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7575, f_measure: 0.7421, kappa: 0.4258, kb_relative_information_score: 235.818, mean_absolute_error: 0.3193, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7407, predictive_accuracy: 0.7461, prior_entropy: 0.9335, recall: 0.7461, relative_absolute_error: 0.7025, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4365, root_relative_squared_error: 0.9158, scimark_benchmark: 947.9122,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.827, f_measure: 0.7648, kappa: 0.4751, kb_relative_information_score: 257.9267, mean_absolute_error: 0.3072, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7644, predictive_accuracy: 0.7695, prior_entropy: 0.9335, recall: 0.7695, relative_absolute_error: 0.6759, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3982, root_relative_squared_error: 0.8354, scimark_benchmark: 946.2552,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7364, f_measure: 0.6888, kappa: 0.3, kb_relative_information_score: 248.5867, mean_absolute_error: 0.2946, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7105, predictive_accuracy: 0.7174, prior_entropy: 0.9335, recall: 0.7174, relative_absolute_error: 0.6481, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4661, root_relative_squared_error: 0.9779, scimark_benchmark: 933.3666,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8304, f_measure: 0.7656, kappa: 0.4741, kb_relative_information_score: 226.3965, mean_absolute_error: 0.3269, 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: 0.7192, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3981, root_relative_squared_error: 0.8353, scimark_benchmark: 912.2097,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7935, f_measure: 0.7175, kappa: 0.3674, kb_relative_information_score: 218.8265, mean_absolute_error: 0.3252, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7166, predictive_accuracy: 0.7253, prior_entropy: 0.9335, recall: 0.7253, relative_absolute_error: 0.7156, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4158, root_relative_squared_error: 0.8724, scimark_benchmark: 944.0326,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7471, f_measure: 0.7395, kappa: 0.4199, kb_relative_information_score: 259.1108, mean_absolute_error: 0.3016, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.738, predictive_accuracy: 0.7435, prior_entropy: 0.9335, recall: 0.7435, relative_absolute_error: 0.6637, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.444, root_relative_squared_error: 0.9316, scimark_benchmark: 946.738,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7302, f_measure: 0.7642, kappa: 0.4744, kb_relative_information_score: 360.1638, mean_absolute_error: 0.2318, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7634, predictive_accuracy: 0.7682, prior_entropy: 0.9335, recall: 0.7682, relative_absolute_error: 0.51, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4814, root_relative_squared_error: 1.01, scimark_benchmark: 948.2261,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5668, f_measure: 0.6129, kappa: 0.1655, kb_relative_information_score: 229.6572, mean_absolute_error: 0.306, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7473, predictive_accuracy: 0.694, prior_entropy: 0.9335, recall: 0.694, relative_absolute_error: 0.6733, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5532, root_relative_squared_error: 1.1605, scimark_benchmark: 923.0729,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7079, f_measure: 0.756, kappa: 0.4504, kb_relative_information_score: 362.4533, mean_absolute_error: 0.2305, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7672, predictive_accuracy: 0.7695, prior_entropy: 0.9335, recall: 0.7695, relative_absolute_error: 0.5071, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4801, root_relative_squared_error: 1.0072, scimark_benchmark: 944.0009,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7838, f_measure: 0.7355, kappa: 0.4057, kb_relative_information_score: 243.7706, mean_absolute_error: 0.3149, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7385, predictive_accuracy: 0.7461, prior_entropy: 0.9335, recall: 0.7461, relative_absolute_error: 0.6929, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4209, root_relative_squared_error: 0.883, scimark_benchmark: 947.4496,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7714, f_measure: 0.7188, kappa: 0.3663, kb_relative_information_score: 221.7708, mean_absolute_error: 0.3219, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7302, predictive_accuracy: 0.737, prior_entropy: 0.9335, recall: 0.737, relative_absolute_error: 0.7083, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4287, root_relative_squared_error: 0.8993, scimark_benchmark: 947.5929,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8345, f_measure: 0.7627, kappa: 0.4697, kb_relative_information_score: 255.1433, mean_absolute_error: 0.3088, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7628, predictive_accuracy: 0.7682, prior_entropy: 0.9335, recall: 0.7682, relative_absolute_error: 0.6795, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.395, root_relative_squared_error: 0.8287, scimark_benchmark: 946.8908,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5134, kb_relative_information_score: 154.1008, mean_absolute_error: 0.349, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.4239, predictive_accuracy: 0.651, prior_entropy: 0.9335, recall: 0.651, relative_absolute_error: 0.7678, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5907, root_relative_squared_error: 1.2394, scimark_benchmark: 947.1255,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7157, f_measure: 0.755, kappa: 0.4514, kb_relative_information_score: 348.7158, mean_absolute_error: 0.2383, 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: 0.5243, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4881, root_relative_squared_error: 1.0241, scimark_benchmark: 943.9592,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8325, f_measure: 0.7616, kappa: 0.4672, kb_relative_information_score: 253.558, mean_absolute_error: 0.3097, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7615, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.6814, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3964, root_relative_squared_error: 0.8316, scimark_benchmark: 945.2707,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.835, f_measure: 0.7559, kappa: 0.4543, kb_relative_information_score: 254.1207, mean_absolute_error: 0.3095, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7558, predictive_accuracy: 0.7617, prior_entropy: 0.9335, recall: 0.7617, relative_absolute_error: 0.681, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3949, root_relative_squared_error: 0.8286, scimark_benchmark: 910.938,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8085, f_measure: 0.7495, kappa: 0.4415, kb_relative_information_score: 272.6761, mean_absolute_error: 0.2921, 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: 0.6427, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4184, root_relative_squared_error: 0.8778, scimark_benchmark: 947.9329,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.721, f_measure: 0.7625, kappa: 0.467, kb_relative_information_score: 364.7429, mean_absolute_error: 0.2292, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7656, predictive_accuracy: 0.7708, prior_entropy: 0.9335, recall: 0.7708, relative_absolute_error: 0.5042, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4787, root_relative_squared_error: 1.0043, scimark_benchmark: 946.0148,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7079, f_measure: 0.7518, kappa: 0.4423, kb_relative_information_score: 348.7158, mean_absolute_error: 0.2383, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7559, predictive_accuracy: 0.7617, prior_entropy: 0.9335, recall: 0.7617, relative_absolute_error: 0.5243, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4881, root_relative_squared_error: 1.0241, scimark_benchmark: 943.9237,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8261, f_measure: 0.7572, kappa: 0.4545, kb_relative_information_score: 241.6435, mean_absolute_error: 0.319, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7617, predictive_accuracy: 0.7669, prior_entropy: 0.9335, recall: 0.7669, relative_absolute_error: 0.7019, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.3987, root_relative_squared_error: 0.8365, scimark_benchmark: 909.4595,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7258, f_measure: 0.7509, kappa: 0.4413, kb_relative_information_score: 191.9897, mean_absolute_error: 0.3535, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7527, predictive_accuracy: 0.7591, prior_entropy: 0.9335, recall: 0.7591, relative_absolute_error: 0.7778, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4269, root_relative_squared_error: 0.8956, scimark_benchmark: 947.1597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7992, f_measure: 0.7448, kappa: 0.4383, kb_relative_information_score: 248.9873, mean_absolute_error: 0.3091, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7448, predictive_accuracy: 0.7448, prior_entropy: 0.9335, recall: 0.7448, relative_absolute_error: 0.6801, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4201, root_relative_squared_error: 0.8814, scimark_benchmark: 933.9099,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7797, f_measure: 0.717, kappa: 0.3683, kb_relative_information_score: 166.0834, mean_absolute_error: 0.363, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7152, predictive_accuracy: 0.7227, prior_entropy: 0.9335, recall: 0.7227, relative_absolute_error: 0.7987, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4363, root_relative_squared_error: 0.9153, scimark_benchmark: 921.1036,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5134, kb_relative_information_score: 154.1008, mean_absolute_error: 0.349, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.4239, predictive_accuracy: 0.651, prior_entropy: 0.9335, recall: 0.651, relative_absolute_error: 0.7678, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.5907, root_relative_squared_error: 1.2394, scimark_benchmark: 947.9844,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7408, f_measure: 0.7395, kappa: 0.4199, kb_relative_information_score: 243.0813, mean_absolute_error: 0.3132, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.738, predictive_accuracy: 0.7435, prior_entropy: 0.9335, recall: 0.7435, relative_absolute_error: 0.689, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.448, root_relative_squared_error: 0.9399, scimark_benchmark: 931.5599,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6079, f_measure: 0.664, kappa: 0.2558, kb_relative_information_score: 266.2907, mean_absolute_error: 0.2852, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7326, predictive_accuracy: 0.7148, prior_entropy: 0.9335, recall: 0.7148, relative_absolute_error: 0.6274, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.534, root_relative_squared_error: 1.1203, scimark_benchmark: 947.9269,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7922, f_measure: 0.7515, kappa: 0.4469, kb_relative_information_score: 249.2143, mean_absolute_error: 0.3108, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7503, predictive_accuracy: 0.7552, prior_entropy: 0.9335, recall: 0.7552, relative_absolute_error: 0.6839, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4181, root_relative_squared_error: 0.8772, scimark_benchmark: 940.3598,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7224, f_measure: 0.7662, kappa: 0.4743, kb_relative_information_score: 373.9013, mean_absolute_error: 0.224, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7721, predictive_accuracy: 0.776, prior_entropy: 0.9335, recall: 0.776, relative_absolute_error: 0.4928, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4732, root_relative_squared_error: 0.9929, scimark_benchmark: 929.6074,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.801, f_measure: 0.7473, kappa: 0.4344, kb_relative_information_score: 220.2396, mean_absolute_error: 0.3259, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7473, predictive_accuracy: 0.7539, prior_entropy: 0.9335, recall: 0.7539, relative_absolute_error: 0.717, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4132, root_relative_squared_error: 0.867, scimark_benchmark: 948.4079,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8303, f_measure: 0.7717, kappa: 0.4944, kb_relative_information_score: 259.8977, mean_absolute_error: 0.3041, mean_prior_absolute_error: 0.4545, number_of_instances: 768, precision: 0.7707, predictive_accuracy: 0.7734, prior_entropy: 0.9335, recall: 0.7734, relative_absolute_error: 0.6691, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.398, root_relative_squared_error: 0.835,

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