Task
Supervised Classification on breast-w

Supervised Classification on breast-w

Task 15 Supervised Classification breast-w 24533 runs submitted
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  • at2 basic mythbusting mythbusting_1 OpenML-CC18 OpenML100 study_1 study_107 study_123 study_14 study_15 study_20 study_41 study_50 study_70 study_98 study_99 under100k under1m
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24533 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8973, f_measure: 0.9147, kappa: 0.8096, kb_relative_information_score: 562.5512, mean_absolute_error: 0.0844, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9154, predictive_accuracy: 0.9156, prior_entropy: 0.9297, recall: 0.9156, relative_absolute_error: 0.1868, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2905, root_relative_squared_error: 0.6113, scimark_benchmark: 1975.2999,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.989, f_measure: 0.9701, kappa: 0.9342, kb_relative_information_score: 649.9413, mean_absolute_error: 0.0303, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9708, predictive_accuracy: 0.97, prior_entropy: 0.9297, recall: 0.97, relative_absolute_error: 0.0671, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1682, root_relative_squared_error: 0.354, scimark_benchmark: 1978.2045,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9634, f_measure: 0.9515, kappa: 0.893, kb_relative_information_score: 590.2138, mean_absolute_error: 0.0752, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9518, predictive_accuracy: 0.9514, prior_entropy: 0.9297, recall: 0.9514, relative_absolute_error: 0.1664, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2098, root_relative_squared_error: 0.4414, scimark_benchmark: 1977.8698,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9891, f_measure: 0.9513, kappa: 0.8919, kb_relative_information_score: 605.6027, mean_absolute_error: 0.0611, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9512, predictive_accuracy: 0.9514, prior_entropy: 0.9297, recall: 0.9514, relative_absolute_error: 0.1351, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1985, root_relative_squared_error: 0.4177, scimark_benchmark: 2004.0877,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.963, f_measure: 0.9657, kappa: 0.9242, kb_relative_information_score: 643.313, mean_absolute_error: 0.0343, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9657, predictive_accuracy: 0.9657, prior_entropy: 0.9297, recall: 0.9657, relative_absolute_error: 0.076, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1853, root_relative_squared_error: 0.3899, scimark_benchmark: 2013.9215,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9253, f_measure: 0.9327, kappa: 0.8507, kb_relative_information_score: 587.6449, mean_absolute_error: 0.0692, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9326, predictive_accuracy: 0.9328, prior_entropy: 0.9297, recall: 0.9328, relative_absolute_error: 0.1531, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2599, root_relative_squared_error: 0.5467, scimark_benchmark: 2004.7455,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4964, f_measure: 0.5187, kb_relative_information_score: -0.1304, mean_absolute_error: 0.452, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.4293, predictive_accuracy: 0.6552, prior_entropy: 0.9297, recall: 0.6552, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.4753, root_relative_squared_error: 1, scimark_benchmark: 1958.0255,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9939, f_measure: 0.9657, kappa: 0.924, kb_relative_information_score: 626.2672, mean_absolute_error: 0.0488, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9657, predictive_accuracy: 0.9657, prior_entropy: 0.9297, recall: 0.9657, relative_absolute_error: 0.108, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1655, root_relative_squared_error: 0.3482, scimark_benchmark: 2009.7967,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9895, f_measure: 0.9585, kappa: 0.9083, kb_relative_information_score: 595.6603, mean_absolute_error: 0.0724, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9586, predictive_accuracy: 0.9585, prior_entropy: 0.9297, recall: 0.9585, relative_absolute_error: 0.1603, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1781, root_relative_squared_error: 0.3747, scimark_benchmark: 2014.7594,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9726, f_measure: 0.9443, kappa: 0.8771, kb_relative_information_score: 599.9492, mean_absolute_error: 0.0633, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9446, predictive_accuracy: 0.9442, prior_entropy: 0.9297, recall: 0.9442, relative_absolute_error: 0.14, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2174, root_relative_squared_error: 0.4574, scimark_benchmark: 944.3886,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9939, f_measure: 0.9657, kappa: 0.924, kb_relative_information_score: 626.2672, mean_absolute_error: 0.0488, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9657, predictive_accuracy: 0.9657, prior_entropy: 0.9297, recall: 0.9657, relative_absolute_error: 0.108, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1655, root_relative_squared_error: 0.3482, scimark_benchmark: 931.1385,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9661, f_measure: 0.9516, kappa: 0.8936, kb_relative_information_score: 605.1372, mean_absolute_error: 0.0623, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9525, predictive_accuracy: 0.9514, prior_entropy: 0.9297, recall: 0.9514, relative_absolute_error: 0.1378, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2058, root_relative_squared_error: 0.4331, scimark_benchmark: 947.2067,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9874, f_measure: 0.9441, kappa: 0.8759, kb_relative_information_score: 600.2457, mean_absolute_error: 0.0648, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.944, predictive_accuracy: 0.9442, prior_entropy: 0.9297, recall: 0.9442, relative_absolute_error: 0.1434, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1915, root_relative_squared_error: 0.403, scimark_benchmark: 902.1244,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9654, f_measure: 0.9589, kappa: 0.9102, kb_relative_information_score: 631.7756, mean_absolute_error: 0.0415, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9615, predictive_accuracy: 0.9585, prior_entropy: 0.9297, recall: 0.9585, relative_absolute_error: 0.0918, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2037, root_relative_squared_error: 0.4285, scimark_benchmark: 894.6907,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8973, f_measure: 0.9147, kappa: 0.8096, kb_relative_information_score: 562.5512, mean_absolute_error: 0.0844, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9154, predictive_accuracy: 0.9156, prior_entropy: 0.9297, recall: 0.9156, relative_absolute_error: 0.1868, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2905, root_relative_squared_error: 0.6113, scimark_benchmark: 922.2795,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9691, f_measure: 0.9686, kappa: 0.9309, kb_relative_information_score: 647.928, mean_absolute_error: 0.0315, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.969, predictive_accuracy: 0.9685, prior_entropy: 0.9297, recall: 0.9685, relative_absolute_error: 0.0696, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1774, root_relative_squared_error: 0.3733, scimark_benchmark: 947.147,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9394, f_measure: 0.9524, kappa: 0.8937, kb_relative_information_score: 622.5457, mean_absolute_error: 0.0472, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9532, predictive_accuracy: 0.9528, prior_entropy: 0.9297, recall: 0.9528, relative_absolute_error: 0.1045, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2173, root_relative_squared_error: 0.4571, scimark_benchmark: 948.6013,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5187, kb_relative_information_score: 142.5898, mean_absolute_error: 0.3448, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.4293, predictive_accuracy: 0.6552, prior_entropy: 0.9297, recall: 0.6552, relative_absolute_error: 0.7629, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.5872, root_relative_squared_error: 1.2354, scimark_benchmark: 948.1814,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5187, kb_relative_information_score: 142.5898, mean_absolute_error: 0.3448, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.4293, predictive_accuracy: 0.6552, prior_entropy: 0.9297, recall: 0.6552, relative_absolute_error: 0.7629, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.5872, root_relative_squared_error: 1.2354, scimark_benchmark: 946.1777,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9505, f_measure: 0.946, kappa: 0.8815, kb_relative_information_score: 579.0618, mean_absolute_error: 0.0825, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9475, predictive_accuracy: 0.9456, prior_entropy: 0.9297, recall: 0.9456, relative_absolute_error: 0.1826, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2233, root_relative_squared_error: 0.4698, scimark_benchmark: 910.09,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9594, f_measure: 0.943, kappa: 0.8743, kb_relative_information_score: 586.5814, mean_absolute_error: 0.0748, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9435, predictive_accuracy: 0.9428, prior_entropy: 0.9297, recall: 0.9428, relative_absolute_error: 0.1656, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2251, root_relative_squared_error: 0.4737, scimark_benchmark: 946.6023,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9591, f_measure: 0.9444, kappa: 0.8776, kb_relative_information_score: 590.9346, mean_absolute_error: 0.0717, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.945, predictive_accuracy: 0.9442, prior_entropy: 0.9297, recall: 0.9442, relative_absolute_error: 0.1586, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2233, root_relative_squared_error: 0.4697, scimark_benchmark: 948.6544,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9589, f_measure: 0.9458, kappa: 0.8806, kb_relative_information_score: 593.6566, mean_absolute_error: 0.0699, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9463, predictive_accuracy: 0.9456, prior_entropy: 0.9297, recall: 0.9456, relative_absolute_error: 0.1546, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2204, root_relative_squared_error: 0.4638, scimark_benchmark: 890.1776,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9918, f_measure: 0.9671, kappa: 0.9274, kb_relative_information_score: 611.8673, mean_absolute_error: 0.0608, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9672, predictive_accuracy: 0.9671, prior_entropy: 0.9297, recall: 0.9671, relative_absolute_error: 0.1345, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1668, root_relative_squared_error: 0.3509, scimark_benchmark: 946.4619,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9846, f_measure: 0.9629, kappa: 0.9183, kb_relative_information_score: 589.2845, mean_absolute_error: 0.08, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9634, predictive_accuracy: 0.9628, prior_entropy: 0.9297, recall: 0.9628, relative_absolute_error: 0.177, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1739, root_relative_squared_error: 0.3658, scimark_benchmark: 948.1968,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9439, f_measure: 0.9369, kappa: 0.8601, kb_relative_information_score: 590.7786, mean_absolute_error: 0.0687, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9369, predictive_accuracy: 0.9371, prior_entropy: 0.9297, recall: 0.9371, relative_absolute_error: 0.152, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2377, root_relative_squared_error: 0.5001, scimark_benchmark: 947.0265,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.955, f_measure: 0.9499, kappa: 0.8891, kb_relative_information_score: 594.3379, mean_absolute_error: 0.0709, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9499, predictive_accuracy: 0.9499, prior_entropy: 0.9297, recall: 0.9499, relative_absolute_error: 0.1569, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2101, root_relative_squared_error: 0.4421, scimark_benchmark: 945.9531,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9485, f_measure: 0.9555, kappa: 0.9014, kb_relative_information_score: 627.1606, mean_absolute_error: 0.0443, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9555, predictive_accuracy: 0.9557, prior_entropy: 0.9297, recall: 0.9557, relative_absolute_error: 0.0981, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2106, root_relative_squared_error: 0.4431, scimark_benchmark: 945.3494,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9919, f_measure: 0.9656, kappa: 0.9239, kb_relative_information_score: 626.5471, mean_absolute_error: 0.0487, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9656, predictive_accuracy: 0.9657, prior_entropy: 0.9297, recall: 0.9657, relative_absolute_error: 0.1078, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1586, root_relative_squared_error: 0.3337, scimark_benchmark: 881.7124,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9544, f_measure: 0.9489, kappa: 0.8882, kb_relative_information_score: 582.58, mean_absolute_error: 0.0804, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.951, predictive_accuracy: 0.9485, prior_entropy: 0.9297, recall: 0.9485, relative_absolute_error: 0.178, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2175, root_relative_squared_error: 0.4575, scimark_benchmark: 945.2858,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9328, f_measure: 0.9439, kappa: 0.8752, kb_relative_information_score: 608.7008, mean_absolute_error: 0.0558, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9441, predictive_accuracy: 0.9442, prior_entropy: 0.9297, recall: 0.9442, relative_absolute_error: 0.1235, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2362, root_relative_squared_error: 0.497, scimark_benchmark: 938.8527,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9712, f_measure: 0.9701, kappa: 0.9341, kb_relative_information_score: 650.2354, mean_absolute_error: 0.03, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9706, predictive_accuracy: 0.97, prior_entropy: 0.9297, recall: 0.97, relative_absolute_error: 0.0665, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1733, root_relative_squared_error: 0.3647, scimark_benchmark: 944.9615,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9915, f_measure: 0.9585, kappa: 0.9083, kb_relative_information_score: 596.1506, mean_absolute_error: 0.0731, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9586, predictive_accuracy: 0.9585, prior_entropy: 0.9297, recall: 0.9585, relative_absolute_error: 0.1618, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1731, root_relative_squared_error: 0.3641, scimark_benchmark: 947.4868,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9893, f_measure: 0.9586, kappa: 0.9086, kb_relative_information_score: 626.5977, mean_absolute_error: 0.0455, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9588, predictive_accuracy: 0.9585, prior_entropy: 0.9297, recall: 0.9585, relative_absolute_error: 0.1007, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1932, root_relative_squared_error: 0.4064, scimark_benchmark: 940.8792,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.99, f_measure: 0.9599, kappa: 0.9113, kb_relative_information_score: 592.5191, mean_absolute_error: 0.0751, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9599, predictive_accuracy: 0.9599, prior_entropy: 0.9297, recall: 0.9599, relative_absolute_error: 0.1662, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1776, root_relative_squared_error: 0.3737, scimark_benchmark: 946.4135,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9915, f_measure: 0.96, kappa: 0.9115, kb_relative_information_score: 596.5467, mean_absolute_error: 0.0728, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.96, predictive_accuracy: 0.9599, prior_entropy: 0.9297, recall: 0.9599, relative_absolute_error: 0.161, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1731, root_relative_squared_error: 0.3642, scimark_benchmark: 947.0854,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9625, f_measure: 0.9387, kappa: 0.865, kb_relative_information_score: 566.5225, mean_absolute_error: 0.0904, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9393, predictive_accuracy: 0.9385, prior_entropy: 0.9297, recall: 0.9385, relative_absolute_error: 0.2001, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2333, root_relative_squared_error: 0.4909, scimark_benchmark: 948.7816,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9039, f_measure: 0.8771, kappa: 0.7435, kb_relative_information_score: 495.6343, mean_absolute_error: 0.1259, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9078, predictive_accuracy: 0.8741, prior_entropy: 0.9297, recall: 0.8741, relative_absolute_error: 0.2786, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.3548, root_relative_squared_error: 0.7465, scimark_benchmark: 949.9397,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9559, f_measure: 0.9627, kappa: 0.9172, kb_relative_information_score: 638.698, mean_absolute_error: 0.0372, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9627, predictive_accuracy: 0.9628, prior_entropy: 0.9297, recall: 0.9628, relative_absolute_error: 0.0823, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1929, root_relative_squared_error: 0.4058, scimark_benchmark: 924.2893,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9871, f_measure: 0.9714, kappa: 0.9369, kb_relative_information_score: 635.8249, mean_absolute_error: 0.0416, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9716, predictive_accuracy: 0.9714, prior_entropy: 0.9297, recall: 0.9714, relative_absolute_error: 0.0919, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.164, root_relative_squared_error: 0.345, scimark_benchmark: 917.7559,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.967, f_measure: 0.9672, kappa: 0.9277, kb_relative_information_score: 645.6205, mean_absolute_error: 0.0329, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9675, predictive_accuracy: 0.9671, prior_entropy: 0.9297, recall: 0.9671, relative_absolute_error: 0.0728, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1814, root_relative_squared_error: 0.3816, scimark_benchmark: 878.4023,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9908, f_measure: 0.9671, kappa: 0.9272, kb_relative_information_score: 627.6957, mean_absolute_error: 0.0479, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9671, predictive_accuracy: 0.9671, prior_entropy: 0.9297, recall: 0.9671, relative_absolute_error: 0.1061, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.16, root_relative_squared_error: 0.3367, scimark_benchmark: 910.8609,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8973, f_measure: 0.9147, kappa: 0.8096, kb_relative_information_score: 562.5512, mean_absolute_error: 0.0844, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9154, predictive_accuracy: 0.9156, prior_entropy: 0.9297, recall: 0.9156, relative_absolute_error: 0.1868, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2905, root_relative_squared_error: 0.6113, scimark_benchmark: 943.185,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9311, f_measure: 0.9465, kappa: 0.8804, kb_relative_information_score: 613.3158, mean_absolute_error: 0.0529, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9478, predictive_accuracy: 0.9471, prior_entropy: 0.9297, recall: 0.9471, relative_absolute_error: 0.1171, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2301, root_relative_squared_error: 0.4841, scimark_benchmark: 947.1308,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9503, f_measure: 0.9543, kappa: 0.8989, kb_relative_information_score: 624.8532, mean_absolute_error: 0.0458, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9543, predictive_accuracy: 0.9542, prior_entropy: 0.9297, recall: 0.9542, relative_absolute_error: 0.1013, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.214, root_relative_squared_error: 0.4502, scimark_benchmark: 947.5756,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9438, f_measure: 0.9428, kappa: 0.8736, kb_relative_information_score: 592.3305, mean_absolute_error: 0.0697, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9429, predictive_accuracy: 0.9428, prior_entropy: 0.9297, recall: 0.9428, relative_absolute_error: 0.1543, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2305, root_relative_squared_error: 0.4849, scimark_benchmark: 917.7677,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9921, f_measure: 0.9585, kappa: 0.9081, kb_relative_information_score: 618.2658, mean_absolute_error: 0.0528, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9585, predictive_accuracy: 0.9585, prior_entropy: 0.9297, recall: 0.9585, relative_absolute_error: 0.1169, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1824, root_relative_squared_error: 0.3839,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9497, f_measure: 0.9583, kappa: 0.9074, kb_relative_information_score: 631.7756, mean_absolute_error: 0.0415, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9585, predictive_accuracy: 0.9585, prior_entropy: 0.9297, recall: 0.9585, relative_absolute_error: 0.0918, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2037, root_relative_squared_error: 0.4285, scimark_benchmark: 947.2819,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9879, f_measure: 0.9571, kappa: 0.905, kb_relative_information_score: 606.1942, mean_absolute_error: 0.063, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9571, predictive_accuracy: 0.9571, prior_entropy: 0.9297, recall: 0.9571, relative_absolute_error: 0.1393, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1788, root_relative_squared_error: 0.3761, scimark_benchmark: 869.5111,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9901, f_measure: 0.9614, kappa: 0.9146, kb_relative_information_score: 594.3517, mean_absolute_error: 0.0743, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9614, predictive_accuracy: 0.9614, prior_entropy: 0.9297, recall: 0.9614, relative_absolute_error: 0.1644, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1762, root_relative_squared_error: 0.3707, scimark_benchmark: 896.1722,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9677, f_measure: 0.9631, kappa: 0.9191, kb_relative_information_score: 638.698, mean_absolute_error: 0.0372, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9648, predictive_accuracy: 0.9628, prior_entropy: 0.9297, recall: 0.9628, relative_absolute_error: 0.0823, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1929, root_relative_squared_error: 0.4058, scimark_benchmark: 946.0039,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9768, f_measure: 0.9586, kappa: 0.9088, kb_relative_information_score: 609.7486, mean_absolute_error: 0.0581, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.959, predictive_accuracy: 0.9585, prior_entropy: 0.9297, recall: 0.9585, relative_absolute_error: 0.1287, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.192, root_relative_squared_error: 0.404, scimark_benchmark: 943.0242,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.964, f_measure: 0.9657, kappa: 0.9243, kb_relative_information_score: 643.313, mean_absolute_error: 0.0343, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9659, predictive_accuracy: 0.9657, prior_entropy: 0.9297, recall: 0.9657, relative_absolute_error: 0.076, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1853, root_relative_squared_error: 0.3899, scimark_benchmark: 940.339,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.968, f_measure: 0.9442, kappa: 0.8766, kb_relative_information_score: 581.1745, mean_absolute_error: 0.08, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9443, predictive_accuracy: 0.9442, prior_entropy: 0.9297, recall: 0.9442, relative_absolute_error: 0.1771, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.2182, root_relative_squared_error: 0.4592, scimark_benchmark: 944.1036,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.992, f_measure: 0.9571, kappa: 0.905, kb_relative_information_score: 611.6533, mean_absolute_error: 0.0581, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9571, predictive_accuracy: 0.9571, prior_entropy: 0.9297, recall: 0.9571, relative_absolute_error: 0.1285, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1848, root_relative_squared_error: 0.3888, scimark_benchmark: 932.7851,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9853, f_measure: 0.9436, kappa: 0.8742, kb_relative_information_score: 629.7252, mean_absolute_error: 0.0443, mean_prior_absolute_error: 0.452, number_of_instances: 699, precision: 0.9446, predictive_accuracy: 0.9442, prior_entropy: 0.9297, recall: 0.9442, relative_absolute_error: 0.098, root_mean_prior_squared_error: 0.4753, root_mean_squared_error: 0.1758, root_relative_squared_error: 0.3698, scimark_benchmark: 917.8814,

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