OpenML
Supervised Classification on mfeat-fourier

Supervised Classification on mfeat-fourier

Task 14 Supervised Classification mfeat-fourier 19118 runs submitted
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  • at2 basic OpenML-CC18 OpenML100 study_1 study_107 study_123 study_14 study_41 study_50 study_7 study_70 study_73 study_98 study_99 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8905, f_measure: 0.7542, kappa: 0.7278, kb_relative_information_score: 1507.8419, mean_absolute_error: 0.0506, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7564, predictive_accuracy: 0.755, prior_entropy: 3.3219, recall: 0.755, relative_absolute_error: 0.2811, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2104, root_relative_squared_error: 0.7012, scimark_benchmark: 1466.6185, usercpu_time_millis: 1790, usercpu_time_millis_training: 1790,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8717, f_measure: 0.7621, kappa: 0.7433, kb_relative_information_score: 1516.86, mean_absolute_error: 0.0462, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7738, predictive_accuracy: 0.769, prior_entropy: 3.3219, recall: 0.769, relative_absolute_error: 0.2567, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2149, root_relative_squared_error: 0.7165, scimark_benchmark: 1325.2092, usercpu_time_millis: 9290, usercpu_time_millis_testing: 6690, usercpu_time_millis_training: 2600,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9309, f_measure: 0.7639, kappa: 0.7372, kb_relative_information_score: 1486.1996, mean_absolute_error: 0.0596, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7657, predictive_accuracy: 0.7635, prior_entropy: 3.3219, recall: 0.7635, relative_absolute_error: 0.3311, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1932, root_relative_squared_error: 0.644, scimark_benchmark: 1355.7054, usercpu_time_millis: 2900, usercpu_time_millis_training: 2900,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9765, f_measure: 0.8031, kappa: 0.7811, kb_relative_information_score: 1628.4206, mean_absolute_error: 0.0452, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.8038, predictive_accuracy: 0.803, prior_entropy: 3.3219, recall: 0.803, relative_absolute_error: 0.251, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1689, root_relative_squared_error: 0.5629, scimark_benchmark: 910.8389, usercpu_time_millis: 15190, usercpu_time_millis_training: 15190,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.978, f_measure: 0.8152, kappa: 0.7944, kb_relative_information_score: 1651.8944, mean_absolute_error: 0.04, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.8158, predictive_accuracy: 0.815, prior_entropy: 3.3219, recall: 0.815, relative_absolute_error: 0.2221, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.169, root_relative_squared_error: 0.5632, scimark_benchmark: 902.4773, usercpu_time_millis: 31060, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 31050,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9844, build_cpu_time: 8623.9784, build_memory: 579344192, f_measure: 0.8488, kappa: 0.8311, kb_relative_information_score: 1696.7752, mean_absolute_error: 0.0409, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.8502, predictive_accuracy: 0.848, prior_entropy: 3.3219, recall: 0.848, relative_absolute_error: 0.2271, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1472, root_relative_squared_error: 0.4906, scimark_benchmark: 941.5665,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9829, f_measure: 0.8327, kappa: 0.8156, kb_relative_information_score: 1510.9705, mean_absolute_error: 0.0734, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.8324, predictive_accuracy: 0.834, prior_entropy: 3.3219, recall: 0.834, relative_absolute_error: 0.4077, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1647, root_relative_squared_error: 0.549, scimark_benchmark: 1301.9956, usercpu_time_millis: 2160, usercpu_time_millis_testing: 110, usercpu_time_millis_training: 2050,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9762, f_measure: 0.831, kappa: 0.8128, kb_relative_information_score: 1682.9526, mean_absolute_error: 0.0398, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.8311, predictive_accuracy: 0.8315, prior_entropy: 3.3219, recall: 0.8315, relative_absolute_error: 0.2213, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1572, root_relative_squared_error: 0.524, scimark_benchmark: 1321.7236, usercpu_time_millis: 21070, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 21050,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9636, f_measure: 0.7757, kappa: 0.7522, kb_relative_information_score: 1568.1683, mean_absolute_error: 0.0466, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7791, predictive_accuracy: 0.777, prior_entropy: 3.3219, recall: 0.777, relative_absolute_error: 0.2589, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1923, root_relative_squared_error: 0.6411, scimark_benchmark: 933.1165, usercpu_time_millis: 220, usercpu_time_millis_testing: 90, usercpu_time_millis_training: 130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9772, f_measure: 0.8347, kappa: 0.8172, kb_relative_information_score: 1679.0139, mean_absolute_error: 0.0344, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.8348, predictive_accuracy: 0.8355, prior_entropy: 3.3219, recall: 0.8355, relative_absolute_error: 0.1908, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1674, root_relative_squared_error: 0.5578, scimark_benchmark: 1064.8317, usercpu_time_millis: 39280, usercpu_time_millis_testing: 35700, usercpu_time_millis_training: 3580,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9829, f_measure: 0.8327, kappa: 0.8156, kb_relative_information_score: 1510.9705, mean_absolute_error: 0.0734, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.8324, predictive_accuracy: 0.834, prior_entropy: 3.3219, recall: 0.834, relative_absolute_error: 0.4077, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1647, root_relative_squared_error: 0.549, scimark_benchmark: 1345.7204, usercpu_time_millis: 1940, usercpu_time_millis_testing: 110, usercpu_time_millis_training: 1830,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8896, f_measure: 0.672, kappa: 0.6333, kb_relative_information_score: 1262.6983, mean_absolute_error: 0.0787, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.6785, predictive_accuracy: 0.67, prior_entropy: 3.3219, recall: 0.67, relative_absolute_error: 0.4374, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2257, root_relative_squared_error: 0.7524, scimark_benchmark: 1354.7191, usercpu_time_millis: 200550, usercpu_time_millis_testing: 1740, usercpu_time_millis_training: 198810,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9767, f_measure: 0.8205, kappa: 0.8017, kb_relative_information_score: 1661.0549, mean_absolute_error: 0.0367, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.821, predictive_accuracy: 0.8215, prior_entropy: 3.3219, recall: 0.8215, relative_absolute_error: 0.2041, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1716, root_relative_squared_error: 0.5721, scimark_benchmark: 1449.4352, usercpu_time_millis: 350, usercpu_time_millis_testing: 240, usercpu_time_millis_training: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.0182, mean_absolute_error: 0.18, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.01, predictive_accuracy: 0.1, prior_entropy: 3.3219, recall: 0.1, relative_absolute_error: 1, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.3, root_relative_squared_error: 1, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8553, f_measure: 0.7396, kappa: 0.7106, kb_relative_information_score: 1455.1603, mean_absolute_error: 0.0521, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7416, predictive_accuracy: 0.7395, prior_entropy: 3.3219, recall: 0.7395, relative_absolute_error: 0.2894, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2283, root_relative_squared_error: 0.7608, scimark_benchmark: 1054.3694, usercpu_time_millis: 68390, usercpu_time_millis_training: 68390,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9391, f_measure: 0.7861, kappa: 0.7639, kb_relative_information_score: 1363.9367, mean_absolute_error: 0.0833, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7881, predictive_accuracy: 0.7875, prior_entropy: 3.3219, recall: 0.7875, relative_absolute_error: 0.4628, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.185, root_relative_squared_error: 0.6167, scimark_benchmark: 943.2817, usercpu_time_millis: 11340, usercpu_time_millis_testing: 3560, usercpu_time_millis_training: 7780,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9391, f_measure: 0.7861, kappa: 0.7639, kb_relative_information_score: 1363.9367, mean_absolute_error: 0.0833, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7881, predictive_accuracy: 0.7875, prior_entropy: 3.3219, recall: 0.7875, relative_absolute_error: 0.4628, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.185, root_relative_squared_error: 0.6167, scimark_benchmark: 940.2922, usercpu_time_millis: 12100, usercpu_time_millis_testing: 4020, usercpu_time_millis_training: 8080,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9353, f_measure: 0.7876, kappa: 0.7656, kb_relative_information_score: 1380.3939, mean_absolute_error: 0.0802, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7898, predictive_accuracy: 0.789, prior_entropy: 3.3219, recall: 0.789, relative_absolute_error: 0.4454, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.186, root_relative_squared_error: 0.6201, scimark_benchmark: 945.6434, usercpu_time_millis: 11400, usercpu_time_millis_testing: 3570, usercpu_time_millis_training: 7830,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9372, f_measure: 0.7639, kappa: 0.7378, kb_relative_information_score: 1526.8622, mean_absolute_error: 0.0473, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.768, predictive_accuracy: 0.764, prior_entropy: 3.3219, recall: 0.764, relative_absolute_error: 0.2628, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2063, root_relative_squared_error: 0.6875, scimark_benchmark: 945.6434, usercpu_time_millis: 8610, usercpu_time_millis_testing: 3080, usercpu_time_millis_training: 5530,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9002, f_measure: 0.7609, kappa: 0.7361, kb_relative_information_score: 1532.2688, mean_absolute_error: 0.0499, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7624, predictive_accuracy: 0.7625, prior_entropy: 3.3219, recall: 0.7625, relative_absolute_error: 0.277, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2029, root_relative_squared_error: 0.6763, scimark_benchmark: 1054.3694, usercpu_time_millis: 410, usercpu_time_millis_training: 410,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7158, f_measure: 0.0662, kappa: 0.1078, kb_relative_information_score: 477.7284, mean_absolute_error: 0.1654, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.0399, predictive_accuracy: 0.197, prior_entropy: 3.3219, recall: 0.197, relative_absolute_error: 0.9189, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2877, root_relative_squared_error: 0.9591, scimark_benchmark: 933.8635, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9717, f_measure: 0.8341, kappa: 0.815, kb_relative_information_score: 1664.4149, mean_absolute_error: 0.0377, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.835, predictive_accuracy: 0.8335, prior_entropy: 3.3219, recall: 0.8335, relative_absolute_error: 0.2092, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1671, root_relative_squared_error: 0.5571, scimark_benchmark: 931.2336, usercpu_time_millis: 244330, usercpu_time_millis_testing: 130, usercpu_time_millis_training: 244200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7158, f_measure: 0.0662, kappa: 0.1078, kb_relative_information_score: 477.7284, mean_absolute_error: 0.1654, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.0399, predictive_accuracy: 0.197, prior_entropy: 3.3219, recall: 0.197, relative_absolute_error: 0.9189, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2877, root_relative_squared_error: 0.9591, scimark_benchmark: 938.4278, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7158, f_measure: 0.0662, kappa: 0.1078, kb_relative_information_score: 477.7284, mean_absolute_error: 0.1654, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.0399, predictive_accuracy: 0.197, prior_entropy: 3.3219, recall: 0.197, relative_absolute_error: 0.9189, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2877, root_relative_squared_error: 0.9591, scimark_benchmark: 942.1229, usercpu_time_millis: 80, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7158, f_measure: 0.0662, kappa: 0.1078, kb_relative_information_score: 477.7284, mean_absolute_error: 0.1654, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.0399, predictive_accuracy: 0.197, prior_entropy: 3.3219, recall: 0.197, relative_absolute_error: 0.9189, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2877, root_relative_squared_error: 0.9591, scimark_benchmark: 939.7623, usercpu_time_millis: 110, usercpu_time_millis_training: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7158, f_measure: 0.0662, kappa: 0.1078, kb_relative_information_score: 477.7284, mean_absolute_error: 0.1654, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.0399, predictive_accuracy: 0.197, prior_entropy: 3.3219, recall: 0.197, relative_absolute_error: 0.9189, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2877, root_relative_squared_error: 0.9591, scimark_benchmark: 934.5243, usercpu_time_millis: 90, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9438, f_measure: 0.7713, kappa: 0.7478, kb_relative_information_score: 1554.4578, mean_absolute_error: 0.0451, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7726, predictive_accuracy: 0.773, prior_entropy: 3.3219, recall: 0.773, relative_absolute_error: 0.2506, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2009, root_relative_squared_error: 0.6698, scimark_benchmark: 945.6434, usercpu_time_millis: 21330, usercpu_time_millis_testing: 6650, usercpu_time_millis_training: 14680,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9761, f_measure: 0.8042, kappa: 0.7822, kb_relative_information_score: 1610.7975, mean_absolute_error: 0.0504, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.8049, predictive_accuracy: 0.804, prior_entropy: 3.3219, recall: 0.804, relative_absolute_error: 0.2798, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1664, root_relative_squared_error: 0.5548, scimark_benchmark: 933.8635, usercpu_time_millis: 9710, usercpu_time_millis_training: 9710,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9722, f_measure: 0.7923, kappa: 0.7689, kb_relative_information_score: 1568.5482, mean_absolute_error: 0.0569, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7931, predictive_accuracy: 0.792, prior_entropy: 3.3219, recall: 0.792, relative_absolute_error: 0.3163, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1707, root_relative_squared_error: 0.569, scimark_benchmark: 938.9865, usercpu_time_millis: 3290, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 3280,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9636, f_measure: 0.7757, kappa: 0.7522, kb_relative_information_score: 1568.1683, mean_absolute_error: 0.0466, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7791, predictive_accuracy: 0.777, prior_entropy: 3.3219, recall: 0.777, relative_absolute_error: 0.2589, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1923, root_relative_squared_error: 0.6411, scimark_benchmark: 1028.5889, usercpu_time_millis: 230, usercpu_time_millis_testing: 100, usercpu_time_millis_training: 130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.98, f_measure: 0.8185, kappa: 0.7994, kb_relative_information_score: 1661.6864, mean_absolute_error: 0.046, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.8181, predictive_accuracy: 0.8195, prior_entropy: 3.3219, recall: 0.8195, relative_absolute_error: 0.2556, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1548, root_relative_squared_error: 0.5161, scimark_benchmark: 880.8372, usercpu_time_millis: 7550, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 7530,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7986, f_measure: 0.6396, kappa: 0.5972, kb_relative_information_score: 1241.8258, mean_absolute_error: 0.0725, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.6429, predictive_accuracy: 0.6375, prior_entropy: 3.3219, recall: 0.6375, relative_absolute_error: 0.4028, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2693, root_relative_squared_error: 0.8975, scimark_benchmark: 825.5282, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8981, f_measure: 0.8139, kappa: 0.7961, kb_relative_information_score: 1616.207, mean_absolute_error: 0.0367, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.8133, predictive_accuracy: 0.8165, prior_entropy: 3.3219, recall: 0.8165, relative_absolute_error: 0.2039, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1916, root_relative_squared_error: 0.6386, scimark_benchmark: 1304.9611, usercpu_time_millis: 210, usercpu_time_millis_training: 210,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8692, f_measure: 0.7647, kappa: 0.7383, kb_relative_information_score: 1507.4482, mean_absolute_error: 0.0471, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.7734, predictive_accuracy: 0.7645, prior_entropy: 3.3219, recall: 0.7645, relative_absolute_error: 0.2617, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.217, root_relative_squared_error: 0.7234, scimark_benchmark: 1073.494, usercpu_time_millis: 11530, usercpu_time_millis_testing: 8350, usercpu_time_millis_training: 3180,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9708, f_measure: 0.8399, kappa: 0.8228, kb_relative_information_score: 576.937, mean_absolute_error: 0.161, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.8401, predictive_accuracy: 0.8405, prior_entropy: 3.3219, recall: 0.8405, relative_absolute_error: 0.8947, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2738, root_relative_squared_error: 0.9127, scimark_benchmark: 894.7222, usercpu_time_millis: 810, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 770,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8599, f_measure: 0.688, kappa: 0.6544, kb_relative_information_score: 1348.7534, mean_absolute_error: 0.0689, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.6878, predictive_accuracy: 0.689, prior_entropy: 3.3219, recall: 0.689, relative_absolute_error: 0.3829, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2335, root_relative_squared_error: 0.7782, scimark_benchmark: 1316.5986, usercpu_time_millis: 140, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8897, f_measure: 0.8027, kappa: 0.7794, kb_relative_information_score: 1581.4626, mean_absolute_error: 0.0405, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.8058, predictive_accuracy: 0.8015, prior_entropy: 3.3219, recall: 0.8015, relative_absolute_error: 0.2249, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1987, root_relative_squared_error: 0.6624, scimark_benchmark: 1349.9741, usercpu_time_millis: 2040, usercpu_time_millis_testing: 2040,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9479, f_measure: 0.8091, kappa: 0.7889, kb_relative_information_score: 1659.7603, mean_absolute_error: 0.0439, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.8123, predictive_accuracy: 0.81, prior_entropy: 3.3219, recall: 0.81, relative_absolute_error: 0.2439, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1676, root_relative_squared_error: 0.5586, scimark_benchmark: 939.5205, usercpu_time_millis: 3210, usercpu_time_millis_testing: 3210,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9654, f_measure: 0.8081, kappa: 0.7867, kb_relative_information_score: 1662.0774, mean_absolute_error: 0.0463, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.8118, predictive_accuracy: 0.808, prior_entropy: 3.3219, recall: 0.808, relative_absolute_error: 0.2572, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1607, root_relative_squared_error: 0.5356, scimark_benchmark: 930.5999, usercpu_time_millis: 3650, usercpu_time_millis_testing: 3650,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9205, build_cpu_time: 10757.2946, build_memory: 1300605004, f_measure: 0.8384, kappa: 0.8183, kb_relative_information_score: 1660.5313, mean_absolute_error: 0.0327, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.8411, predictive_accuracy: 0.8365, prior_entropy: 3.3219, recall: 0.8365, relative_absolute_error: 0.1815, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.1798, root_relative_squared_error: 0.5994, scimark_benchmark: 908.8705,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8971, build_cpu_time: 1500.3782, build_memory: 37074636.8, f_measure: 0.5597, kappa: 0.5406, kb_relative_information_score: 611.0189, mean_absolute_error: 0.1576, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.6313, predictive_accuracy: 0.5865, prior_entropy: 3.3219, recall: 0.5865, relative_absolute_error: 0.8756, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2726, root_relative_squared_error: 0.9087, scimark_benchmark: 943.8094,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8971, build_cpu_time: 1484.1615, build_memory: 71800461.6, f_measure: 0.5597, kappa: 0.5406, kb_relative_information_score: 611.0189, mean_absolute_error: 0.1576, mean_prior_absolute_error: 0.18, number_of_instances: 2000, precision: 0.6313, predictive_accuracy: 0.5865, prior_entropy: 3.3219, recall: 0.5865, relative_absolute_error: 0.8756, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.2726, root_relative_squared_error: 0.9087, scimark_benchmark: 937.9406,

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