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OpenML
OpenML
Supervised Classification on arrhythmia

Supervised Classification on arrhythmia

Task 5 Supervised Classification arrhythmia 3391 runs submitted
0 likes downloaded by 1 people , 1 total downloads 0 issues
Visibility: Public
  • basic study_1 study_41 study_73 under100k under1m
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3391 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.787, f_measure: 0.6554, kappa: 0.5129, kb_relative_information_score: 200.349, mean_absolute_error: 0.0517, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.6317, predictive_accuracy: 0.6881, prior_entropy: 2.5222, recall: 0.6881, relative_absolute_error: 0.6045, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.1755, root_relative_squared_error: 0.854, scimark_benchmark: 947.4382,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7208, f_measure: 0.6123, kappa: 0.433, kb_relative_information_score: 180.4987, mean_absolute_error: 0.0498, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.5981, predictive_accuracy: 0.6283, prior_entropy: 2.5222, recall: 0.6283, relative_absolute_error: 0.5822, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2052, root_relative_squared_error: 0.9987, scimark_benchmark: 947.3149,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7242, f_measure: 0.6167, kappa: 0.4403, kb_relative_information_score: 181.7737, mean_absolute_error: 0.0494, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.6006, predictive_accuracy: 0.635, prior_entropy: 2.5222, recall: 0.635, relative_absolute_error: 0.5775, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2036, root_relative_squared_error: 0.9905, scimark_benchmark: 912.9115,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4964, f_measure: 0.3811, kb_relative_information_score: -25.3168, mean_absolute_error: 0.1108, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.2938, predictive_accuracy: 0.542, prior_entropy: 2.5222, recall: 0.542, relative_absolute_error: 1.2954, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2323, root_relative_squared_error: 1.1302, scimark_benchmark: 949.8329,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7703, f_measure: 0.6034, kappa: 0.4011, kb_relative_information_score: 171.2896, mean_absolute_error: 0.051, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.6273, predictive_accuracy: 0.5885, prior_entropy: 2.5222, recall: 0.5885, relative_absolute_error: 0.5957, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2195, root_relative_squared_error: 1.068, scimark_benchmark: 946.8369,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4973, f_measure: 0.3811, kb_relative_information_score: -25.1912, mean_absolute_error: 0.1108, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.2938, predictive_accuracy: 0.542, prior_entropy: 2.5222, recall: 0.542, relative_absolute_error: 1.2953, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2323, root_relative_squared_error: 1.1302, scimark_benchmark: 946.6093,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7027, f_measure: 0.562, kappa: 0.3317, kb_relative_information_score: -7.5276, mean_absolute_error: 0.11, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.6084, predictive_accuracy: 0.6527, prior_entropy: 2.5222, recall: 0.6527, relative_absolute_error: 1.2859, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2305, root_relative_squared_error: 1.1217, scimark_benchmark: 943.9694,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7842, f_measure: 0.6814, kappa: 0.5576, kb_relative_information_score: 198.9581, mean_absolute_error: 0.0522, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.663, predictive_accuracy: 0.7168, prior_entropy: 2.5222, recall: 0.7168, relative_absolute_error: 0.6104, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.1696, root_relative_squared_error: 0.8252, scimark_benchmark: 909.8614,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4903, f_measure: 0.3811, kb_relative_information_score: -25.5579, mean_absolute_error: 0.1108, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.2938, predictive_accuracy: 0.542, prior_entropy: 2.5222, recall: 0.542, relative_absolute_error: 1.2955, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2323, root_relative_squared_error: 1.1304, scimark_benchmark: 946.8508,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8632, f_measure: 0.596, kappa: 0.4023, kb_relative_information_score: 173.7616, mean_absolute_error: 0.0637, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.5963, predictive_accuracy: 0.6704, prior_entropy: 2.5222, recall: 0.6704, relative_absolute_error: 0.7443, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.17, root_relative_squared_error: 0.8271, scimark_benchmark: 946.6048,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7256, f_measure: 0.4451, kappa: 0.1054, kb_relative_information_score: 134.1074, mean_absolute_error: 0.064, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.5568, predictive_accuracy: 0.5752, prior_entropy: 2.5222, recall: 0.5752, relative_absolute_error: 0.7486, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.1965, root_relative_squared_error: 0.9561, scimark_benchmark: 944.4307,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5846, f_measure: 0.4893, kappa: 0.2091, kb_relative_information_score: 123.1916, mean_absolute_error: 0.0501, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.4507, predictive_accuracy: 0.5996, prior_entropy: 2.5222, recall: 0.5996, relative_absolute_error: 0.5852, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2237, root_relative_squared_error: 1.0887, scimark_benchmark: 949.7301,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7274, f_measure: 0.6168, kappa: 0.4389, kb_relative_information_score: 179.503, mean_absolute_error: 0.0497, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.5982, predictive_accuracy: 0.6394, prior_entropy: 2.5222, recall: 0.6394, relative_absolute_error: 0.581, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2013, root_relative_squared_error: 0.9795, scimark_benchmark: 947.1786,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4908, f_measure: 0.3811, kb_relative_information_score: -25.5579, mean_absolute_error: 0.1108, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.2938, predictive_accuracy: 0.542, prior_entropy: 2.5222, recall: 0.542, relative_absolute_error: 1.2955, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2323, root_relative_squared_error: 1.1304, scimark_benchmark: 947.7304,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7219, f_measure: 0.6151, kappa: 0.4364, kb_relative_information_score: 179.7434, mean_absolute_error: 0.0497, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.5969, predictive_accuracy: 0.6372, prior_entropy: 2.5222, recall: 0.6372, relative_absolute_error: 0.5807, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2022, root_relative_squared_error: 0.984, scimark_benchmark: 909.3933,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.721, f_measure: 0.5725, kappa: 0.3657, kb_relative_information_score: -7.6321, mean_absolute_error: 0.11, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.5604, predictive_accuracy: 0.6615, prior_entropy: 2.5222, recall: 0.6615, relative_absolute_error: 1.2859, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2305, root_relative_squared_error: 1.1217, scimark_benchmark: 947.0465,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7196, f_measure: 0.4554, kappa: 0.1329, kb_relative_information_score: 133.5415, mean_absolute_error: 0.0639, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.4925, predictive_accuracy: 0.5819, prior_entropy: 2.5222, recall: 0.5819, relative_absolute_error: 0.7476, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.197, root_relative_squared_error: 0.9589, scimark_benchmark: 943.2146,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8806, f_measure: 0.698, kappa: 0.5741, kb_relative_information_score: 211.4689, mean_absolute_error: 0.0538, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.6838, predictive_accuracy: 0.7389, prior_entropy: 2.5222, recall: 0.7389, relative_absolute_error: 0.6294, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.1574, root_relative_squared_error: 0.7662, scimark_benchmark: 948.8009,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6504, f_measure: 0.4822, kappa: 0.1855, kb_relative_information_score: 129.2056, mean_absolute_error: 0.0611, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.5212, predictive_accuracy: 0.573, prior_entropy: 2.5222, recall: 0.573, relative_absolute_error: 0.7144, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2138, root_relative_squared_error: 1.0404, scimark_benchmark: 930.9275,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4929, f_measure: 0.3811, kb_relative_information_score: -25.3949, mean_absolute_error: 0.1108, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.2938, predictive_accuracy: 0.542, prior_entropy: 2.5222, recall: 0.542, relative_absolute_error: 1.2954, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2323, root_relative_squared_error: 1.1303, scimark_benchmark: 947.1231,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7291, f_measure: 0.6154, kappa: 0.438, kb_relative_information_score: 184.9536, mean_absolute_error: 0.0487, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.6018, predictive_accuracy: 0.6305, prior_entropy: 2.5222, recall: 0.6305, relative_absolute_error: 0.5697, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2047, root_relative_squared_error: 0.9962, scimark_benchmark: 946.3743,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6129, f_measure: 0.4406, kappa: 0.1856, kb_relative_information_score: -31.9833, mean_absolute_error: 0.1079, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.3814, predictive_accuracy: 0.5531, prior_entropy: 2.5222, recall: 0.5531, relative_absolute_error: 1.2618, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2309, root_relative_squared_error: 1.1235, scimark_benchmark: 947.9957,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8271, f_measure: 0.6674, kappa: 0.5168, kb_relative_information_score: 227.5336, mean_absolute_error: 0.0396, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.6601, predictive_accuracy: 0.6836, prior_entropy: 2.5222, recall: 0.6836, relative_absolute_error: 0.4632, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.1883, root_relative_squared_error: 0.9161, scimark_benchmark: 947.2901,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5538, f_measure: 0.4301, kappa: 0.1128, kb_relative_information_score: 80.4927, mean_absolute_error: 0.0636, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.3996, predictive_accuracy: 0.4912, prior_entropy: 2.5222, recall: 0.4912, relative_absolute_error: 0.7436, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2522, root_relative_squared_error: 1.2273, scimark_benchmark: 948.8022,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8632, f_measure: 0.6948, kappa: 0.559, kb_relative_information_score: 250.1108, mean_absolute_error: 0.0352, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.6768, predictive_accuracy: 0.7212, prior_entropy: 2.5222, recall: 0.7212, relative_absolute_error: 0.4115, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.1693, root_relative_squared_error: 0.8239, scimark_benchmark: 929.468,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7986, f_measure: 0.6666, kappa: 0.5126, kb_relative_information_score: -2.0409, mean_absolute_error: 0.1098, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.6753, predictive_accuracy: 0.708, prior_entropy: 2.5222, recall: 0.708, relative_absolute_error: 1.2834, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.23, root_relative_squared_error: 1.1194, scimark_benchmark: 948.5664,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8714, f_measure: 0.708, kappa: 0.577, kb_relative_information_score: 243.4496, mean_absolute_error: 0.0435, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.6914, predictive_accuracy: 0.7345, prior_entropy: 2.5222, recall: 0.7345, relative_absolute_error: 0.5087, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.1597, root_relative_squared_error: 0.777, scimark_benchmark: 948.7973,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8835, f_measure: 0.7048, kappa: 0.5864, kb_relative_information_score: 211.5081, mean_absolute_error: 0.0538, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.69, predictive_accuracy: 0.7456, prior_entropy: 2.5222, recall: 0.7456, relative_absolute_error: 0.6291, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.1572, root_relative_squared_error: 0.7649, scimark_benchmark: 947.4887,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5543, f_measure: 0.3965, kappa: 0.0195, kb_relative_information_score: -21.9489, mean_absolute_error: 0.1107, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.4165, predictive_accuracy: 0.5442, prior_entropy: 2.5222, recall: 0.5442, relative_absolute_error: 1.2936, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2319, root_relative_squared_error: 1.1286, scimark_benchmark: 949.829,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8048, f_measure: 0.6641, kappa: 0.5008, kb_relative_information_score: -1.692, mean_absolute_error: 0.1099, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.658, predictive_accuracy: 0.6836, prior_entropy: 2.5222, recall: 0.6836, relative_absolute_error: 1.2843, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2302, root_relative_squared_error: 1.1201, scimark_benchmark: 949.8586,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8075, f_measure: 0.6675, kappa: 0.5068, kb_relative_information_score: -1.9556, mean_absolute_error: 0.1099, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.6587, predictive_accuracy: 0.6881, prior_entropy: 2.5222, recall: 0.6881, relative_absolute_error: 1.2843, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2302, root_relative_squared_error: 1.1201, scimark_benchmark: 924.4384,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8075, f_measure: 0.6675, kappa: 0.5068, kb_relative_information_score: -1.9556, mean_absolute_error: 0.1099, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.6587, predictive_accuracy: 0.6881, prior_entropy: 2.5222, recall: 0.6881, relative_absolute_error: 1.2843, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2302, root_relative_squared_error: 1.1201, scimark_benchmark: 948.4337,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8813, f_measure: 0.6998, kappa: 0.5779, kb_relative_information_score: 210.504, mean_absolute_error: 0.054, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.6857, predictive_accuracy: 0.7412, prior_entropy: 2.5222, recall: 0.7412, relative_absolute_error: 0.6316, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.1576, root_relative_squared_error: 0.767, scimark_benchmark: 943.7308,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7842, f_measure: 0.6814, kappa: 0.5576, kb_relative_information_score: 198.9581, mean_absolute_error: 0.0522, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.663, predictive_accuracy: 0.7168, prior_entropy: 2.5222, recall: 0.7168, relative_absolute_error: 0.6104, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.1696, root_relative_squared_error: 0.8252, scimark_benchmark: 950.0768,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4903, f_measure: 0.3811, kb_relative_information_score: -25.5579, mean_absolute_error: 0.1108, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.2938, predictive_accuracy: 0.542, prior_entropy: 2.5222, recall: 0.542, relative_absolute_error: 1.2955, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2323, root_relative_squared_error: 1.1304, scimark_benchmark: 946.2201,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4677, f_measure: 0.3811, kb_relative_information_score: 0.0614, mean_absolute_error: 0.0857, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.2938, predictive_accuracy: 0.542, prior_entropy: 2.5222, recall: 0.542, relative_absolute_error: 1.0016, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2056, root_relative_squared_error: 1.0003, scimark_benchmark: 946.4435,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8048, f_measure: 0.6641, kappa: 0.5008, kb_relative_information_score: -1.692, mean_absolute_error: 0.1099, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.658, predictive_accuracy: 0.6836, prior_entropy: 2.5222, recall: 0.6836, relative_absolute_error: 1.2843, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2302, root_relative_squared_error: 1.1201, scimark_benchmark: 946.6902,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8048, f_measure: 0.6641, kappa: 0.5008, kb_relative_information_score: -1.692, mean_absolute_error: 0.1099, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.658, predictive_accuracy: 0.6836, prior_entropy: 2.5222, recall: 0.6836, relative_absolute_error: 1.2843, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2302, root_relative_squared_error: 1.1201, scimark_benchmark: 941.8034,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7305, f_measure: 0.6231, kappa: 0.4487, kb_relative_information_score: 179.7637, mean_absolute_error: 0.0501, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.6023, predictive_accuracy: 0.6504, prior_entropy: 2.5222, recall: 0.6504, relative_absolute_error: 0.5854, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.1964, root_relative_squared_error: 0.9558, scimark_benchmark: 948.8697,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4951, f_measure: 0.3811, kb_relative_information_score: -25.4128, mean_absolute_error: 0.1108, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.2938, predictive_accuracy: 0.542, prior_entropy: 2.5222, recall: 0.542, relative_absolute_error: 1.2954, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2323, root_relative_squared_error: 1.1303, scimark_benchmark: 938.4398,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6288, f_measure: 0.491, kappa: 0.2413, kb_relative_information_score: 104.984, mean_absolute_error: 0.0636, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.4942, predictive_accuracy: 0.4912, prior_entropy: 2.5222, recall: 0.4912, relative_absolute_error: 0.7436, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2522, root_relative_squared_error: 1.2271, scimark_benchmark: 943.9111,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.798, f_measure: 0.6742, kappa: 0.5172, kb_relative_information_score: -1.845, mean_absolute_error: 0.1099, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.6673, predictive_accuracy: 0.6925, prior_entropy: 2.5222, recall: 0.6925, relative_absolute_error: 1.2846, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.2302, root_relative_squared_error: 1.1203, scimark_benchmark: 947.7873,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7414, f_measure: 0.6328, kappa: 0.4643, kb_relative_information_score: 185.5422, mean_absolute_error: 0.0488, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.6134, predictive_accuracy: 0.6571, prior_entropy: 2.5222, recall: 0.6571, relative_absolute_error: 0.5707, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.195, root_relative_squared_error: 0.9489, scimark_benchmark: 946.6408,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8714, f_measure: 0.708, kappa: 0.577, kb_relative_information_score: 243.4496, mean_absolute_error: 0.0435, mean_prior_absolute_error: 0.0855, number_of_instances: 452, precision: 0.6914, predictive_accuracy: 0.7345, prior_entropy: 2.5222, recall: 0.7345, relative_absolute_error: 0.5087, root_mean_prior_squared_error: 0.2055, root_mean_squared_error: 0.1597, root_relative_squared_error: 0.777, scimark_benchmark: 947.8175,

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