OpenML
Supervised Classification on breast-cancer

Supervised Classification on breast-cancer

Task 13 Supervised Classification breast-cancer 767 runs submitted
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  • basic mythbusting mythbusting_1 study_1 study_107 study_15 study_20 study_41 study_73 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5897, f_measure: 0.5847, kappa: 0.1474, kb_relative_information_score: -32.5162, mean_absolute_error: 0.4336, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.6586, predictive_accuracy: 0.5664, prior_entropy: 0.8796, recall: 0.5664, relative_absolute_error: 1.0365, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.6585, root_relative_squared_error: 1.4407, scimark_benchmark: 915.3502,
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: 0.4641, f_measure: 0.5298, kappa: -0.0657, kb_relative_information_score: -70.9781, mean_absolute_error: 0.486, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.5536, predictive_accuracy: 0.514, prior_entropy: 0.8796, recall: 0.514, relative_absolute_error: 1.1618, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.6971, root_relative_squared_error: 1.5254, scimark_benchmark: 913.6045,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6548, f_measure: 0.7035, kappa: 0.2656, kb_relative_information_score: 47.021, mean_absolute_error: 0.3305, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.6999, predictive_accuracy: 0.7203, prior_entropy: 0.8796, recall: 0.7203, relative_absolute_error: 0.7901, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4647, root_relative_squared_error: 1.0167, scimark_benchmark: 947.5094,
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: 0.6666, f_measure: 0.6996, kappa: 0.2627, kb_relative_information_score: 76.1136, mean_absolute_error: 0.2851, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.6946, predictive_accuracy: 0.7098, prior_entropy: 0.8796, recall: 0.7098, relative_absolute_error: 0.6814, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.523, root_relative_squared_error: 1.1444, scimark_benchmark: 576.6112,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6969, f_measure: 0.7126, kappa: 0.2932, kb_relative_information_score: 53.3575, mean_absolute_error: 0.3303, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7084, predictive_accuracy: 0.7238, prior_entropy: 0.8796, recall: 0.7238, relative_absolute_error: 0.7896, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4483, root_relative_squared_error: 0.9808, scimark_benchmark: 944.2805,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6367, f_measure: 0.6998, kappa: 0.2505, kb_relative_information_score: 26.1364, mean_absolute_error: 0.3722, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.703, predictive_accuracy: 0.7273, prior_entropy: 0.8796, recall: 0.7273, relative_absolute_error: 0.8896, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4501, root_relative_squared_error: 0.9849,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6458, f_measure: 0.7167, kappa: 0.2971, kb_relative_information_score: 82.845, mean_absolute_error: 0.2802, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7153, predictive_accuracy: 0.7343, prior_entropy: 0.8796, recall: 0.7343, relative_absolute_error: 0.6699, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4973, root_relative_squared_error: 1.088, scimark_benchmark: 865.626,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6164, f_measure: 0.6748, kappa: 0.1923, kb_relative_information_score: 64.9554, mean_absolute_error: 0.3004, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.6689, predictive_accuracy: 0.6958, prior_entropy: 0.8796, recall: 0.6958, relative_absolute_error: 0.7181, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.5408, root_relative_squared_error: 1.1833, scimark_benchmark: 924.7264,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6176, f_measure: 0.6739, kappa: 0.1921, kb_relative_information_score: 24.4223, mean_absolute_error: 0.3689, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.6674, predictive_accuracy: 0.6923, prior_entropy: 0.8796, recall: 0.6923, relative_absolute_error: 0.8818, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.485, root_relative_squared_error: 1.0612, scimark_benchmark: 918.4453,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6425, f_measure: 0.6923, kappa: 0.245, kb_relative_information_score: 65.6641, mean_absolute_error: 0.2999, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.687, predictive_accuracy: 0.7028, prior_entropy: 0.8796, recall: 0.7028, relative_absolute_error: 0.717, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.5201, root_relative_squared_error: 1.1379, scimark_benchmark: 942.6424,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6765, f_measure: 0.7066, kappa: 0.266, kb_relative_information_score: 43.1163, mean_absolute_error: 0.3542, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7226, predictive_accuracy: 0.7413, prior_entropy: 0.8796, recall: 0.7413, relative_absolute_error: 0.8468, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4296, root_relative_squared_error: 0.9399, scimark_benchmark: 947.5366,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5754, f_measure: 0.6605, kappa: 0.168, kb_relative_information_score: 11.7757, mean_absolute_error: 0.3933, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.6539, predictive_accuracy: 0.6713, prior_entropy: 0.8796, recall: 0.6713, relative_absolute_error: 0.9403, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4547, root_relative_squared_error: 0.9949, scimark_benchmark: 945.833,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6677, f_measure: 0.6982, kappa: 0.2454, kb_relative_information_score: 31.7598, mean_absolute_error: 0.3627, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7069, predictive_accuracy: 0.7308, prior_entropy: 0.8796, recall: 0.7308, relative_absolute_error: 0.8672, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.443, root_relative_squared_error: 0.9693, scimark_benchmark: 938.1812,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5229, f_measure: 0.6159, kappa: 0.061, kb_relative_information_score: 70.049, mean_absolute_error: 0.2937, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.663, predictive_accuracy: 0.7063, prior_entropy: 0.8796, recall: 0.7063, relative_absolute_error: 0.7021, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.5419, root_relative_squared_error: 1.1858, scimark_benchmark: 911.0954,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5567, f_measure: 0.6809, kappa: 0.2087, kb_relative_information_score: 27.6918, mean_absolute_error: 0.3818, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7462, predictive_accuracy: 0.7413, prior_entropy: 0.8796, recall: 0.7413, relative_absolute_error: 0.9128, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4404, root_relative_squared_error: 0.9637, scimark_benchmark: 944.0138,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6267, f_measure: 0.6864, kappa: 0.2518, kb_relative_information_score: 54.6642, mean_absolute_error: 0.3147, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.6875, predictive_accuracy: 0.6853, prior_entropy: 0.8796, recall: 0.6853, relative_absolute_error: 0.7523, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.561, root_relative_squared_error: 1.2274, scimark_benchmark: 949.9364,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5801, kb_relative_information_score: 67.4849, mean_absolute_error: 0.2972, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.4939, predictive_accuracy: 0.7028, prior_entropy: 0.8796, recall: 0.7028, relative_absolute_error: 0.7105, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.5452, root_relative_squared_error: 1.1928, scimark_benchmark: 943.8097,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6264, f_measure: 0.6665, kappa: 0.1738, kb_relative_information_score: 27.0862, mean_absolute_error: 0.3675, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.6592, predictive_accuracy: 0.6853, prior_entropy: 0.8796, recall: 0.6853, relative_absolute_error: 0.8784, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4637, root_relative_squared_error: 1.0145,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5229, f_measure: 0.6159, kappa: 0.061, kb_relative_information_score: 70.049, mean_absolute_error: 0.2937, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.663, predictive_accuracy: 0.7063, prior_entropy: 0.8796, recall: 0.7063, relative_absolute_error: 0.7021, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.5419, root_relative_squared_error: 1.1858, scimark_benchmark: 949.0443,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6654, f_measure: 0.6712, kappa: 0.1874, kb_relative_information_score: 39.1715, mean_absolute_error: 0.3575, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7478, predictive_accuracy: 0.7378, prior_entropy: 0.8796, recall: 0.7378, relative_absolute_error: 0.8547, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.437, root_relative_squared_error: 0.9562, scimark_benchmark: 921.6462,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5861, f_measure: 0.6855, kappa: 0.2141, kb_relative_information_score: 33.3579, mean_absolute_error: 0.3684, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7087, predictive_accuracy: 0.7308, prior_entropy: 0.8796, recall: 0.7308, relative_absolute_error: 0.8806, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4481, root_relative_squared_error: 0.9804, scimark_benchmark: 942.5029,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6742, f_measure: 0.6989, kappa: 0.2496, kb_relative_information_score: 47.8321, mean_absolute_error: 0.3422, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7466, predictive_accuracy: 0.7483, prior_entropy: 0.8796, recall: 0.7483, relative_absolute_error: 0.8181, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4349, root_relative_squared_error: 0.9515, scimark_benchmark: 947.8301,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5801, kb_relative_information_score: 67.4849, mean_absolute_error: 0.2972, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.4939, predictive_accuracy: 0.7028, prior_entropy: 0.8796, recall: 0.7028, relative_absolute_error: 0.7105, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.5452, root_relative_squared_error: 1.1928, scimark_benchmark: 948.1407,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6555, f_measure: 0.7017, kappa: 0.254, kb_relative_information_score: 40.7422, mean_absolute_error: 0.3579, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7245, predictive_accuracy: 0.7413, prior_entropy: 0.8796, recall: 0.7413, relative_absolute_error: 0.8556, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4341, root_relative_squared_error: 0.9499, scimark_benchmark: 940.868,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5801, kb_relative_information_score: 67.4849, mean_absolute_error: 0.2972, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.4939, predictive_accuracy: 0.7028, prior_entropy: 0.8796, recall: 0.7028, relative_absolute_error: 0.7105, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.5452, root_relative_squared_error: 1.1928, scimark_benchmark: 942.7666,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5998, f_measure: 0.6927, kappa: 0.2319, kb_relative_information_score: 82.8696, mean_absolute_error: 0.2762, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.6974, predictive_accuracy: 0.7238, prior_entropy: 0.8796, recall: 0.7238, relative_absolute_error: 0.6603, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.5256, root_relative_squared_error: 1.15, scimark_benchmark: 947.2342,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.633, f_measure: 0.7287, kappa: 0.3218, kb_relative_information_score: 113.6392, mean_absolute_error: 0.2343, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7655, predictive_accuracy: 0.7657, prior_entropy: 0.8796, recall: 0.7657, relative_absolute_error: 0.56, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.484, root_relative_squared_error: 1.059, scimark_benchmark: 936.9946,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6485, f_measure: 0.7063, kappa: 0.2969, kb_relative_information_score: 70.049, mean_absolute_error: 0.2937, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7063, predictive_accuracy: 0.7063, prior_entropy: 0.8796, recall: 0.7063, relative_absolute_error: 0.7021, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.5419, root_relative_squared_error: 1.1858, scimark_benchmark: 945.9313,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5229, f_measure: 0.6159, kappa: 0.061, kb_relative_information_score: 70.049, mean_absolute_error: 0.2937, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.663, predictive_accuracy: 0.7063, prior_entropy: 0.8796, recall: 0.7063, relative_absolute_error: 0.7021, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.5419, root_relative_squared_error: 1.1858, scimark_benchmark: 942.9803,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5832, f_measure: 0.7072, kappa: 0.2682, kb_relative_information_score: 34.7056, mean_absolute_error: 0.3727, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7377, predictive_accuracy: 0.7483, prior_entropy: 0.8796, recall: 0.7483, relative_absolute_error: 0.8908, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4444, root_relative_squared_error: 0.9723, scimark_benchmark: 947.5222,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5801, kb_relative_information_score: 67.4849, mean_absolute_error: 0.2972, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.4939, predictive_accuracy: 0.7028, prior_entropy: 0.8796, recall: 0.7028, relative_absolute_error: 0.7105, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.5452, root_relative_squared_error: 1.1928, scimark_benchmark: 948.0508,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4831, f_measure: 0.5801, kb_relative_information_score: -0.3776, mean_absolute_error: 0.4184, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.4939, predictive_accuracy: 0.7028, prior_entropy: 0.8796, recall: 0.7028, relative_absolute_error: 1.0002, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4571, root_relative_squared_error: 1.0001, scimark_benchmark: 918.0013,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6336, f_measure: 0.6944, kappa: 0.2416, kb_relative_information_score: 23.2934, mean_absolute_error: 0.3805, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.6904, predictive_accuracy: 0.7133, prior_entropy: 0.8796, recall: 0.7133, relative_absolute_error: 0.9097, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4418, root_relative_squared_error: 0.9668,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5881, f_measure: 0.6982, kappa: 0.2454, kb_relative_information_score: 39.0315, mean_absolute_error: 0.3582, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7069, predictive_accuracy: 0.7308, prior_entropy: 0.8796, recall: 0.7308, relative_absolute_error: 0.8563, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.469, root_relative_squared_error: 1.0261, scimark_benchmark: 925.8632,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6483, f_measure: 0.681, kappa: 0.2052, kb_relative_information_score: 32.0501, mean_absolute_error: 0.3613, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.6779, predictive_accuracy: 0.7063, prior_entropy: 0.8796, recall: 0.7063, relative_absolute_error: 0.8637, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4464, root_relative_squared_error: 0.9766, scimark_benchmark: 922.5927,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6485, f_measure: 0.7063, kappa: 0.2969, kb_relative_information_score: 70.049, mean_absolute_error: 0.2937, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7063, predictive_accuracy: 0.7063, prior_entropy: 0.8796, recall: 0.7063, relative_absolute_error: 0.7021, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.5419, root_relative_squared_error: 1.1858, scimark_benchmark: 947.5736,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5903, f_measure: 0.6824, kappa: 0.2409, kb_relative_information_score: 16.8905, mean_absolute_error: 0.3867, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.6829, predictive_accuracy: 0.6818, prior_entropy: 0.8796, recall: 0.6818, relative_absolute_error: 0.9244, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4476, root_relative_squared_error: 0.9794, scimark_benchmark: 914.0905,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5213, f_measure: 0.6164, kappa: 0.0558, kb_relative_information_score: 64.9207, mean_absolute_error: 0.3007, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.6392, predictive_accuracy: 0.6993, prior_entropy: 0.8796, recall: 0.6993, relative_absolute_error: 0.7188, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.5484, root_relative_squared_error: 1.1998,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5749, f_measure: 0.6653, kappa: 0.1675, kb_relative_information_score: 57.2283, mean_absolute_error: 0.3112, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.6586, predictive_accuracy: 0.6888, prior_entropy: 0.8796, recall: 0.6888, relative_absolute_error: 0.7439, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.5578, root_relative_squared_error: 1.2206, scimark_benchmark: 873.685,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6608, f_measure: 0.6881, kappa: 0.2211, kb_relative_information_score: 48.1957, mean_absolute_error: 0.3317, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7154, predictive_accuracy: 0.7343, prior_entropy: 0.8796, recall: 0.7343, relative_absolute_error: 0.7929, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4551, root_relative_squared_error: 0.9958, scimark_benchmark: 885.9577,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5801, kb_relative_information_score: 67.4849, mean_absolute_error: 0.2972, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.4939, predictive_accuracy: 0.7028, prior_entropy: 0.8796, recall: 0.7028, relative_absolute_error: 0.7105, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.5452, root_relative_squared_error: 1.1928, scimark_benchmark: 946.8378,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5935, f_measure: 0.7128, kappa: 0.2826, kb_relative_information_score: 38.5871, mean_absolute_error: 0.3678, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7524, predictive_accuracy: 0.7552, prior_entropy: 0.8796, recall: 0.7552, relative_absolute_error: 0.8792, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4362, root_relative_squared_error: 0.9544, scimark_benchmark: 945.6864,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5898, f_measure: 0.6489, kappa: 0.1384, kb_relative_information_score: 9.7273, mean_absolute_error: 0.3876, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.6414, predictive_accuracy: 0.6608, prior_entropy: 0.8796, recall: 0.6608, relative_absolute_error: 0.9267, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4933, root_relative_squared_error: 1.0794, scimark_benchmark: 938.5939,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6533, f_measure: 0.723, kappa: 0.3072, kb_relative_information_score: 35.8793, mean_absolute_error: 0.3601, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7516, predictive_accuracy: 0.7587, prior_entropy: 0.8796, recall: 0.7587, relative_absolute_error: 0.8608, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4273, root_relative_squared_error: 0.935, scimark_benchmark: 911.709,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.674, f_measure: 0.6942, kappa: 0.2372, kb_relative_information_score: 34.0859, mean_absolute_error: 0.358, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.6946, predictive_accuracy: 0.7203, prior_entropy: 0.8796, recall: 0.7203, relative_absolute_error: 0.8558, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4392, root_relative_squared_error: 0.9609, scimark_benchmark: 951.3993,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6665, f_measure: 0.655, kappa: 0.1445, kb_relative_information_score: 19.0905, mean_absolute_error: 0.3879, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.6958, predictive_accuracy: 0.7203, prior_entropy: 0.8796, recall: 0.7203, relative_absolute_error: 0.9274, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4399, root_relative_squared_error: 0.9624, scimark_benchmark: 946.2791,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5935, f_measure: 0.7128, kappa: 0.2826, kb_relative_information_score: 38.5871, mean_absolute_error: 0.3678, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7524, predictive_accuracy: 0.7552, prior_entropy: 0.8796, recall: 0.7552, relative_absolute_error: 0.8792, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4362, root_relative_squared_error: 0.9544, scimark_benchmark: 834.6058,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5801, kb_relative_information_score: 67.4849, mean_absolute_error: 0.2972, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.4939, predictive_accuracy: 0.7028, prior_entropy: 0.8796, recall: 0.7028, relative_absolute_error: 0.7105, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.5452, root_relative_squared_error: 1.1928, scimark_benchmark: 942.1175,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6533, f_measure: 0.723, kappa: 0.3072, kb_relative_information_score: 35.8793, mean_absolute_error: 0.3601, mean_prior_absolute_error: 0.4183, number_of_instances: 286, precision: 0.7516, predictive_accuracy: 0.7587, prior_entropy: 0.8796, recall: 0.7587, relative_absolute_error: 0.8608, root_mean_prior_squared_error: 0.457, root_mean_squared_error: 0.4273, root_relative_squared_error: 0.935, scimark_benchmark: 947.0837,

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