OpenML
Supervised Classification on chatfield_4

Supervised Classification on chatfield_4

Task 4390 Supervised Classification chatfield_4 233 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8888, f_measure: 0.8886, kappa: 0.7686, kb_relative_information_score: 1645.9564, mean_absolute_error: 0.1501, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8904, predictive_accuracy: 0.8881, prior_entropy: 0.9689, recall: 0.8881, relative_absolute_error: 0.3137, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3073, root_relative_squared_error: 0.6285, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9341, f_measure: 0.8668, kappa: 0.7227, kb_relative_information_score: 1519.5276, mean_absolute_error: 0.1752, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8678, predictive_accuracy: 0.8664, prior_entropy: 0.9689, recall: 0.8664, relative_absolute_error: 0.3663, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3101, root_relative_squared_error: 0.6341, scimark_benchmark: 972.587, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.927, f_measure: 0.8719, kappa: 0.7333, kb_relative_information_score: 1621.695, mean_absolute_error: 0.1511, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8729, predictive_accuracy: 0.8715, prior_entropy: 0.9689, recall: 0.8715, relative_absolute_error: 0.3157, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3188, root_relative_squared_error: 0.652, scimark_benchmark: 934.3687, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4552, kb_relative_information_score: 368.5952, mean_absolute_error: 0.3957, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.3651, predictive_accuracy: 0.6043, prior_entropy: 0.9689, recall: 0.6043, relative_absolute_error: 0.8271, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.6291, root_relative_squared_error: 1.2864, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4552, kb_relative_information_score: 368.5952, mean_absolute_error: 0.3957, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.3651, predictive_accuracy: 0.6043, prior_entropy: 0.9689, recall: 0.6043, relative_absolute_error: 0.8271, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.6291, root_relative_squared_error: 1.2864, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9449, f_measure: 0.8635, kappa: 0.7158, kb_relative_information_score: 1619.9907, mean_absolute_error: 0.1478, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8646, predictive_accuracy: 0.863, prior_entropy: 0.9689, recall: 0.863, relative_absolute_error: 0.309, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3232, root_relative_squared_error: 0.6609, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9449, f_measure: 0.8635, kappa: 0.7158, kb_relative_information_score: 1619.9907, mean_absolute_error: 0.1478, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8646, predictive_accuracy: 0.863, prior_entropy: 0.9689, recall: 0.863, relative_absolute_error: 0.309, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3232, root_relative_squared_error: 0.6609, scimark_benchmark: 934.695,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9449, f_measure: 0.8898, kappa: 0.7706, kb_relative_information_score: 1585.4504, mean_absolute_error: 0.1649, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8909, predictive_accuracy: 0.8894, prior_entropy: 0.9689, recall: 0.8894, relative_absolute_error: 0.3446, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.2885, root_relative_squared_error: 0.59, scimark_benchmark: 934.695,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9621, f_measure: 0.9006, kappa: 0.7916, kb_relative_information_score: 1611.7281, mean_absolute_error: 0.1578, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.9006, predictive_accuracy: 0.9009, prior_entropy: 0.9689, recall: 0.9009, relative_absolute_error: 0.3298, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.2763, root_relative_squared_error: 0.5649, scimark_benchmark: 938.191, usercpu_time_millis: 220, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 210,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9008, f_measure: 0.8669, kappa: 0.723, kb_relative_information_score: 1566.2889, mean_absolute_error: 0.1637, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8681, predictive_accuracy: 0.8664, prior_entropy: 0.9689, recall: 0.8664, relative_absolute_error: 0.3421, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3355, root_relative_squared_error: 0.686, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4552, kb_relative_information_score: 368.5952, mean_absolute_error: 0.3957, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.3651, predictive_accuracy: 0.6043, prior_entropy: 0.9689, recall: 0.6043, relative_absolute_error: 0.8271, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.6291, root_relative_squared_error: 1.2864, scimark_benchmark: 932.438, usercpu_time_millis: 30, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4552, kb_relative_information_score: 368.5952, mean_absolute_error: 0.3957, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.3651, predictive_accuracy: 0.6043, prior_entropy: 0.9689, recall: 0.6043, relative_absolute_error: 0.8271, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.6291, root_relative_squared_error: 1.2864, scimark_benchmark: 936.3373, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9449, f_measure: 0.8635, kappa: 0.7158, kb_relative_information_score: 1619.9907, mean_absolute_error: 0.1478, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8646, predictive_accuracy: 0.863, prior_entropy: 0.9689, recall: 0.863, relative_absolute_error: 0.309, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3232, root_relative_squared_error: 0.6609, scimark_benchmark: 932.438, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9568, f_measure: 0.8934, kappa: 0.7775, kb_relative_information_score: 1597.3504, mean_absolute_error: 0.161, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8937, predictive_accuracy: 0.8932, prior_entropy: 0.9689, recall: 0.8932, relative_absolute_error: 0.3364, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.2818, root_relative_squared_error: 0.5763, scimark_benchmark: 947.1781, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8888, f_measure: 0.8886, kappa: 0.7686, kb_relative_information_score: 1645.9564, mean_absolute_error: 0.1501, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8904, predictive_accuracy: 0.8881, prior_entropy: 0.9689, recall: 0.8881, relative_absolute_error: 0.3137, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3073, root_relative_squared_error: 0.6285, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9341, f_measure: 0.8668, kappa: 0.7227, kb_relative_information_score: 1519.5276, mean_absolute_error: 0.1752, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8678, predictive_accuracy: 0.8664, prior_entropy: 0.9689, recall: 0.8664, relative_absolute_error: 0.3663, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3101, root_relative_squared_error: 0.6341, scimark_benchmark: 908.9569, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.927, f_measure: 0.8719, kappa: 0.7333, kb_relative_information_score: 1621.695, mean_absolute_error: 0.1511, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8729, predictive_accuracy: 0.8715, prior_entropy: 0.9689, recall: 0.8715, relative_absolute_error: 0.3157, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3188, root_relative_squared_error: 0.652, scimark_benchmark: 940.1541, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4552, kb_relative_information_score: 368.5952, mean_absolute_error: 0.3957, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.3651, predictive_accuracy: 0.6043, prior_entropy: 0.9689, recall: 0.6043, relative_absolute_error: 0.8271, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.6291, root_relative_squared_error: 1.2864, scimark_benchmark: 859.5223, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9449, f_measure: 0.8635, kappa: 0.7158, kb_relative_information_score: 1619.9907, mean_absolute_error: 0.1478, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8646, predictive_accuracy: 0.863, prior_entropy: 0.9689, recall: 0.863, relative_absolute_error: 0.309, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3232, root_relative_squared_error: 0.6609, scimark_benchmark: 930.404, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9449, f_measure: 0.8635, kappa: 0.7158, kb_relative_information_score: 1619.9907, mean_absolute_error: 0.1478, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8646, predictive_accuracy: 0.863, prior_entropy: 0.9689, recall: 0.863, relative_absolute_error: 0.309, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3232, root_relative_squared_error: 0.6609, scimark_benchmark: 903.2737,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9449, f_measure: 0.8635, kappa: 0.7158, kb_relative_information_score: 1619.9907, mean_absolute_error: 0.1478, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8646, predictive_accuracy: 0.863, prior_entropy: 0.9689, recall: 0.863, relative_absolute_error: 0.309, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3232, root_relative_squared_error: 0.6609, scimark_benchmark: 933.3455,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9449, f_measure: 0.8898, kappa: 0.7706, kb_relative_information_score: 1585.4504, mean_absolute_error: 0.1649, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8909, predictive_accuracy: 0.8894, prior_entropy: 0.9689, recall: 0.8894, relative_absolute_error: 0.3446, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.2885, root_relative_squared_error: 0.59, scimark_benchmark: 930.404, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9621, f_measure: 0.9006, kappa: 0.7916, kb_relative_information_score: 1611.7281, mean_absolute_error: 0.1578, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.9006, predictive_accuracy: 0.9009, prior_entropy: 0.9689, recall: 0.9009, relative_absolute_error: 0.3298, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.2763, root_relative_squared_error: 0.5649, scimark_benchmark: 938.4601, usercpu_time_millis: 280, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 270,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9449, f_measure: 0.8635, kappa: 0.7158, kb_relative_information_score: 1619.9907, mean_absolute_error: 0.1478, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8646, predictive_accuracy: 0.863, prior_entropy: 0.9689, recall: 0.863, relative_absolute_error: 0.309, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3232, root_relative_squared_error: 0.6609, scimark_benchmark: 932.438,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9008, f_measure: 0.8669, kappa: 0.723, kb_relative_information_score: 1566.2889, mean_absolute_error: 0.1637, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8681, predictive_accuracy: 0.8664, prior_entropy: 0.9689, recall: 0.8664, relative_absolute_error: 0.3421, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3355, root_relative_squared_error: 0.686, scimark_benchmark: 936.3213, usercpu_time_millis: 90, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9568, f_measure: 0.8934, kappa: 0.7775, kb_relative_information_score: 1597.3504, mean_absolute_error: 0.161, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8937, predictive_accuracy: 0.8932, prior_entropy: 0.9689, recall: 0.8932, relative_absolute_error: 0.3364, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.2818, root_relative_squared_error: 0.5763, scimark_benchmark: 730.6551, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9582, f_measure: 0.8903, kappa: 0.7722, kb_relative_information_score: 1587.3537, mean_absolute_error: 0.1642, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8922, predictive_accuracy: 0.8898, prior_entropy: 0.9689, recall: 0.8898, relative_absolute_error: 0.3432, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.2783, root_relative_squared_error: 0.5691, scimark_benchmark: 851.2074, usercpu_time_millis: 2100, usercpu_time_millis_testing: 1170, usercpu_time_millis_training: 930,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9568, f_measure: 0.892, kappa: 0.7755, kb_relative_information_score: 1582.7553, mean_absolute_error: 0.1649, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8936, predictive_accuracy: 0.8915, prior_entropy: 0.9689, recall: 0.8915, relative_absolute_error: 0.3446, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.2804, root_relative_squared_error: 0.5734, scimark_benchmark: 936.3373, usercpu_time_millis: 530, usercpu_time_millis_testing: 140, usercpu_time_millis_training: 390,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9562, f_measure: 0.8936, kappa: 0.7784, kb_relative_information_score: 1585.0414, mean_absolute_error: 0.1644, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8945, predictive_accuracy: 0.8932, prior_entropy: 0.9689, recall: 0.8932, relative_absolute_error: 0.3437, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.2806, root_relative_squared_error: 0.5739, scimark_benchmark: 929.7512, usercpu_time_millis: 250, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 190,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9546, f_measure: 0.8895, kappa: 0.7705, kb_relative_information_score: 1579.4805, mean_absolute_error: 0.1651, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8915, predictive_accuracy: 0.8889, prior_entropy: 0.9689, recall: 0.8889, relative_absolute_error: 0.345, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.2832, root_relative_squared_error: 0.5791, scimark_benchmark: 890.4736, usercpu_time_millis: 120, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9515, f_measure: 0.8864, kappa: 0.7637, kb_relative_information_score: 1573.3611, mean_absolute_error: 0.1657, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8876, predictive_accuracy: 0.886, prior_entropy: 0.9689, recall: 0.886, relative_absolute_error: 0.3463, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.2877, root_relative_squared_error: 0.5883, scimark_benchmark: 939.7241, usercpu_time_millis: 100, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9163, f_measure: 0.8831, kappa: 0.7591, kb_relative_information_score: 1659.1449, mean_absolute_error: 0.144, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8891, predictive_accuracy: 0.8821, prior_entropy: 0.9689, recall: 0.8821, relative_absolute_error: 0.301, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.317, root_relative_squared_error: 0.6483, scimark_benchmark: 929.0296, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9163, f_measure: 0.8831, kappa: 0.7591, kb_relative_information_score: 1659.1449, mean_absolute_error: 0.144, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8891, predictive_accuracy: 0.8821, prior_entropy: 0.9689, recall: 0.8821, relative_absolute_error: 0.301, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.317, root_relative_squared_error: 0.6483, scimark_benchmark: 930.0565,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9163, f_measure: 0.8831, kappa: 0.7591, kb_relative_information_score: 1659.1449, mean_absolute_error: 0.144, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8891, predictive_accuracy: 0.8821, prior_entropy: 0.9689, recall: 0.8821, relative_absolute_error: 0.301, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.317, root_relative_squared_error: 0.6483, scimark_benchmark: 894.7131,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9163, f_measure: 0.8831, kappa: 0.7591, kb_relative_information_score: 1659.1449, mean_absolute_error: 0.144, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8891, predictive_accuracy: 0.8821, prior_entropy: 0.9689, recall: 0.8821, relative_absolute_error: 0.301, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.317, root_relative_squared_error: 0.6483, scimark_benchmark: 936.1714,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9163, f_measure: 0.8831, kappa: 0.7591, kb_relative_information_score: 1659.1449, mean_absolute_error: 0.144, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8891, predictive_accuracy: 0.8821, prior_entropy: 0.9689, recall: 0.8821, relative_absolute_error: 0.301, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.317, root_relative_squared_error: 0.6483, scimark_benchmark: 929.0296, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4832, f_measure: 0.4552, kb_relative_information_score: -0.9627, mean_absolute_error: 0.4785, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.3651, predictive_accuracy: 0.6043, prior_entropy: 0.9689, recall: 0.6043, relative_absolute_error: 1.0001, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.4891, root_relative_squared_error: 1.0001, scimark_benchmark: 941.9549,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.936, f_measure: 0.8813, kappa: 0.7531, kb_relative_information_score: 1747.0844, mean_absolute_error: 0.1205, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8825, predictive_accuracy: 0.8809, prior_entropy: 0.9689, recall: 0.8809, relative_absolute_error: 0.2518, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3336, root_relative_squared_error: 0.6822, scimark_benchmark: 929.0296, usercpu_time_millis: 90, usercpu_time_millis_training: 90,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8888, f_measure: 0.8886, kappa: 0.7686, kb_relative_information_score: 1645.9564, mean_absolute_error: 0.1501, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8904, predictive_accuracy: 0.8881, prior_entropy: 0.9689, recall: 0.8881, relative_absolute_error: 0.3137, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3073, root_relative_squared_error: 0.6285, scimark_benchmark: 1313.8988,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9008, f_measure: 0.8669, kappa: 0.723, kb_relative_information_score: 1566.2889, mean_absolute_error: 0.1637, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8681, predictive_accuracy: 0.8664, prior_entropy: 0.9689, recall: 0.8664, relative_absolute_error: 0.3421, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3355, root_relative_squared_error: 0.686, scimark_benchmark: 1375.1578, usercpu_time_millis: 80, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8888, f_measure: 0.8886, kappa: 0.7686, kb_relative_information_score: 1645.9564, mean_absolute_error: 0.1501, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8904, predictive_accuracy: 0.8881, prior_entropy: 0.9689, recall: 0.8881, relative_absolute_error: 0.3137, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3073, root_relative_squared_error: 0.6285, scimark_benchmark: 1336.0954,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9449, f_measure: 0.8635, kappa: 0.7158, kb_relative_information_score: 1619.9907, mean_absolute_error: 0.1478, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8646, predictive_accuracy: 0.863, prior_entropy: 0.9689, recall: 0.863, relative_absolute_error: 0.309, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3232, root_relative_squared_error: 0.6609, scimark_benchmark: 1347.1763,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9621, f_measure: 0.9006, kappa: 0.7916, kb_relative_information_score: 1611.7281, mean_absolute_error: 0.1578, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.9006, predictive_accuracy: 0.9009, prior_entropy: 0.9689, recall: 0.9009, relative_absolute_error: 0.3298, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.2763, root_relative_squared_error: 0.5649, scimark_benchmark: 1334.8032, usercpu_time_millis: 170, usercpu_time_millis_training: 170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9449, f_measure: 0.8635, kappa: 0.7158, kb_relative_information_score: 1619.9907, mean_absolute_error: 0.1478, mean_prior_absolute_error: 0.4784, number_of_instances: 2350, precision: 0.8646, predictive_accuracy: 0.863, prior_entropy: 0.9689, recall: 0.863, relative_absolute_error: 0.309, root_mean_prior_squared_error: 0.489, root_mean_squared_error: 0.3232, root_relative_squared_error: 0.6609, scimark_benchmark: 1331.4379,

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