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OpenML
OpenML
Supervised Classification on kin8nm

Supervised Classification on kin8nm

Task 3672 Supervised Classification kin8nm 561 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_107 study_15 study_20 study_41 study_7 under100k under1m
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561 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.904, f_measure: 0.8361, kappa: 0.6721, kb_relative_information_score: 4891.3019, mean_absolute_error: 0.2066, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.8362, predictive_accuracy: 0.8361, prior_entropy: 0.9998, recall: 0.8361, relative_absolute_error: 0.4133, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3455, root_relative_squared_error: 0.6912, scimark_benchmark: 1324.8395, usercpu_time_millis: 6350, usercpu_time_millis_testing: 6350,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6579, f_measure: 0.639, kappa: 0.3186, kb_relative_information_score: 2657.5335, mean_absolute_error: 0.3376, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.711, predictive_accuracy: 0.6624, prior_entropy: 0.9998, recall: 0.6624, relative_absolute_error: 0.6755, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5811, root_relative_squared_error: 1.1623, scimark_benchmark: 1318.1432, usercpu_time_millis: 740, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 730,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7352, f_measure: 0.7352, kappa: 0.4704, kb_relative_information_score: 3852.0656, mean_absolute_error: 0.2648, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7353, predictive_accuracy: 0.7352, prior_entropy: 0.9998, recall: 0.7352, relative_absolute_error: 0.5297, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5146, root_relative_squared_error: 1.0293, scimark_benchmark: 1315.395, usercpu_time_millis: 87500, usercpu_time_millis_testing: 8300, usercpu_time_millis_training: 79200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7358, f_measure: 0.7357, kappa: 0.4714, kb_relative_information_score: 3860.0692, mean_absolute_error: 0.2643, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7359, predictive_accuracy: 0.7357, prior_entropy: 0.9998, recall: 0.7357, relative_absolute_error: 0.5287, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5141, root_relative_squared_error: 1.0283, scimark_benchmark: 1287.514, usercpu_time_millis: 2260, usercpu_time_millis_training: 2260,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8133, f_measure: 0.7326, kappa: 0.4651, kb_relative_information_score: 2572.9496, mean_absolute_error: 0.358, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7326, predictive_accuracy: 0.7327, prior_entropy: 0.9998, recall: 0.7327, relative_absolute_error: 0.7161, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4205, root_relative_squared_error: 0.8412, scimark_benchmark: 938.343, usercpu_time_millis: 1330, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 1320,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7329, f_measure: 0.733, kappa: 0.4658, kb_relative_information_score: 3816.0496, mean_absolute_error: 0.267, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.733, predictive_accuracy: 0.733, prior_entropy: 0.9998, recall: 0.733, relative_absolute_error: 0.5341, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5167, root_relative_squared_error: 1.0335, scimark_benchmark: 1331.6907, usercpu_time_millis: 220, usercpu_time_millis_training: 220,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9098, f_measure: 0.8286, kappa: 0.6573, kb_relative_information_score: 4145.1639, mean_absolute_error: 0.2633, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.829, predictive_accuracy: 0.8286, prior_entropy: 0.9998, recall: 0.8286, relative_absolute_error: 0.5269, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.349, root_relative_squared_error: 0.6982, scimark_benchmark: 938.343, usercpu_time_millis: 1224350, usercpu_time_millis_testing: 8040, usercpu_time_millis_training: 1216310,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8346, f_measure: 0.7678, kappa: 0.5357, kb_relative_information_score: 3148.715, mean_absolute_error: 0.3227, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7682, predictive_accuracy: 0.7678, prior_entropy: 0.9998, recall: 0.7678, relative_absolute_error: 0.6455, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4063, root_relative_squared_error: 0.8127, scimark_benchmark: 1372.2145, usercpu_time_millis: 1150, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 1110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9326, f_measure: 0.8481, kappa: 0.6962, kb_relative_information_score: 4267.7534, mean_absolute_error: 0.2575, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.8481, predictive_accuracy: 0.8481, prior_entropy: 0.9998, recall: 0.8481, relative_absolute_error: 0.5152, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3317, root_relative_squared_error: 0.6635, scimark_benchmark: 1336.2509, usercpu_time_millis: 5330, usercpu_time_millis_testing: 1010, usercpu_time_millis_training: 4320,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7547, f_measure: 0.7548, kappa: 0.5094, kb_relative_information_score: 4172.2083, mean_absolute_error: 0.2452, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7548, predictive_accuracy: 0.7548, prior_entropy: 0.9998, recall: 0.7548, relative_absolute_error: 0.4906, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4952, root_relative_squared_error: 0.9906, scimark_benchmark: 825.5282, usercpu_time_millis: 100, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8274, f_measure: 0.7718, kappa: 0.5435, kb_relative_information_score: 3708.8129, mean_absolute_error: 0.2853, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7718, predictive_accuracy: 0.7719, prior_entropy: 0.9998, recall: 0.7719, relative_absolute_error: 0.5707, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4155, root_relative_squared_error: 0.8311, scimark_benchmark: 1066.7184, usercpu_time_millis: 90, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8233, f_measure: 0.7799, kappa: 0.5597, kb_relative_information_score: 3877.254, mean_absolute_error: 0.2758, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7799, predictive_accuracy: 0.7799, prior_entropy: 0.9998, recall: 0.7799, relative_absolute_error: 0.5518, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4187, root_relative_squared_error: 0.8375, scimark_benchmark: 1354.2491, usercpu_time_millis: 1600, usercpu_time_millis_training: 1600,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4858, f_measure: 0.3676, kappa: -0.0288, kb_relative_information_score: -107.6985, mean_absolute_error: 0.5063, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.4333, predictive_accuracy: 0.4937, prior_entropy: 0.9998, recall: 0.4937, relative_absolute_error: 1.013, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.7116, root_relative_squared_error: 1.4234, scimark_benchmark: 1290.1085, usercpu_time_millis: 8110, usercpu_time_millis_testing: 1290, usercpu_time_millis_training: 6820,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8322, f_measure: 0.7529, kappa: 0.5073, kb_relative_information_score: 3316.2337, mean_absolute_error: 0.3078, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7564, predictive_accuracy: 0.7533, prior_entropy: 0.9998, recall: 0.7533, relative_absolute_error: 0.6158, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4107, root_relative_squared_error: 0.8215, scimark_benchmark: 1358.4523, usercpu_time_millis: 470, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 460,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6649, f_measure: 0.6645, kappa: 0.3295, kb_relative_information_score: 2693.5495, mean_absolute_error: 0.3354, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.6654, predictive_accuracy: 0.6646, prior_entropy: 0.9998, recall: 0.6646, relative_absolute_error: 0.6711, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5792, root_relative_squared_error: 1.1585, scimark_benchmark: 1465.2979, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7563, f_measure: 0.756, kappa: 0.514, kb_relative_information_score: 4220.2297, mean_absolute_error: 0.2423, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7629, predictive_accuracy: 0.7577, prior_entropy: 0.9998, recall: 0.7577, relative_absolute_error: 0.4848, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4923, root_relative_squared_error: 0.9847, scimark_benchmark: 1353.5686, usercpu_time_millis: 1670, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 1650,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4995, f_measure: 0.3431, kb_relative_information_score: -0.0017, mean_absolute_error: 0.4998, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.2589, predictive_accuracy: 0.5088, prior_entropy: 0.9998, recall: 0.5088, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4999, root_relative_squared_error: 1, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.818, f_measure: 0.7785, kappa: 0.5569, kb_relative_information_score: 3930.0455, mean_absolute_error: 0.2699, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7786, predictive_accuracy: 0.7784, prior_entropy: 0.9998, recall: 0.7784, relative_absolute_error: 0.54, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4195, root_relative_squared_error: 0.8391, scimark_benchmark: 1465.2979, usercpu_time_millis: 200, usercpu_time_millis_training: 200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8133, f_measure: 0.7368, kappa: 0.4735, kb_relative_information_score: 3879.5175, mean_absolute_error: 0.2632, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7368, predictive_accuracy: 0.7368, prior_entropy: 0.9998, recall: 0.7368, relative_absolute_error: 0.5266, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4933, root_relative_squared_error: 0.9867, scimark_benchmark: 931.2336, usercpu_time_millis: 920, usercpu_time_millis_testing: 260, usercpu_time_millis_training: 660,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7949, f_measure: 0.736, kappa: 0.4718, kb_relative_information_score: 3406.0111, mean_absolute_error: 0.3011, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.736, predictive_accuracy: 0.736, prior_entropy: 0.9998, recall: 0.736, relative_absolute_error: 0.6023, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4425, root_relative_squared_error: 0.8851, scimark_benchmark: 945.6434, usercpu_time_millis: 1910, usercpu_time_millis_testing: 520, usercpu_time_millis_training: 1390,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8081, f_measure: 0.7352, kappa: 0.4703, kb_relative_information_score: 3060.0695, mean_absolute_error: 0.3281, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7352, predictive_accuracy: 0.7352, prior_entropy: 0.9998, recall: 0.7352, relative_absolute_error: 0.6565, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.423, root_relative_squared_error: 0.8462, scimark_benchmark: 941.7954, usercpu_time_millis: 1060, usercpu_time_millis_testing: 260, usercpu_time_millis_training: 800,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8081, f_measure: 0.7352, kappa: 0.4703, kb_relative_information_score: 3060.0695, mean_absolute_error: 0.3281, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7352, predictive_accuracy: 0.7352, prior_entropy: 0.9998, recall: 0.7352, relative_absolute_error: 0.6565, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.423, root_relative_squared_error: 0.8462, scimark_benchmark: 923.7642, usercpu_time_millis: 1050, usercpu_time_millis_testing: 270, usercpu_time_millis_training: 780,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8081, f_measure: 0.7352, kappa: 0.4703, kb_relative_information_score: 3060.0695, mean_absolute_error: 0.3281, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7352, predictive_accuracy: 0.7352, prior_entropy: 0.9998, recall: 0.7352, relative_absolute_error: 0.6565, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.423, root_relative_squared_error: 0.8462, scimark_benchmark: 894.7455, usercpu_time_millis: 1050, usercpu_time_millis_testing: 270, usercpu_time_millis_training: 780,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8215, f_measure: 0.7345, kappa: 0.4711, kb_relative_information_score: 3763.401, mean_absolute_error: 0.272, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7388, predictive_accuracy: 0.7351, prior_entropy: 0.9998, recall: 0.7351, relative_absolute_error: 0.5442, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4638, root_relative_squared_error: 0.9278, scimark_benchmark: 936.6206, usercpu_time_millis: 5520, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 5470,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8166, f_measure: 0.7316, kappa: 0.4649, kb_relative_information_score: 3698.0309, mean_absolute_error: 0.2759, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7351, predictive_accuracy: 0.7321, prior_entropy: 0.9998, recall: 0.7321, relative_absolute_error: 0.552, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4677, root_relative_squared_error: 0.9355, scimark_benchmark: 936.6206, usercpu_time_millis: 2770, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 2740,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8108, f_measure: 0.7222, kappa: 0.449, kb_relative_information_score: 3582.0905, mean_absolute_error: 0.2829, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7309, predictive_accuracy: 0.7238, prior_entropy: 0.9998, recall: 0.7238, relative_absolute_error: 0.5661, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.476, root_relative_squared_error: 0.9521, scimark_benchmark: 942.1229, usercpu_time_millis: 1320, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 1300,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.79, f_measure: 0.7131, kappa: 0.433, kb_relative_information_score: 3397.6997, mean_absolute_error: 0.2947, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7258, predictive_accuracy: 0.7156, prior_entropy: 0.9998, recall: 0.7156, relative_absolute_error: 0.5895, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4885, root_relative_squared_error: 0.9772, scimark_benchmark: 922.9039, usercpu_time_millis: 660, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 650,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7752, f_measure: 0.6888, kappa: 0.3918, kb_relative_information_score: 3173.5178, mean_absolute_error: 0.3077, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7134, predictive_accuracy: 0.6945, prior_entropy: 0.9998, recall: 0.6945, relative_absolute_error: 0.6156, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5024, root_relative_squared_error: 1.0049, scimark_benchmark: 938.9865, usercpu_time_millis: 370, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 360,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8202, f_measure: 0.7424, kappa: 0.485, kb_relative_information_score: 2926.4544, mean_absolute_error: 0.3348, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7428, predictive_accuracy: 0.7424, prior_entropy: 0.9998, recall: 0.7424, relative_absolute_error: 0.6699, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.416, root_relative_squared_error: 0.8321, scimark_benchmark: 936.6206, usercpu_time_millis: 3680, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 3670,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8217, f_measure: 0.7445, kappa: 0.4891, kb_relative_information_score: 2926.6979, mean_absolute_error: 0.3351, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7449, predictive_accuracy: 0.7445, prior_entropy: 0.9998, recall: 0.7445, relative_absolute_error: 0.6704, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.415, root_relative_squared_error: 0.8301, scimark_benchmark: 924.6116, usercpu_time_millis: 1740, usercpu_time_millis_training: 1740,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.82, f_measure: 0.7408, kappa: 0.4819, kb_relative_information_score: 2867.7936, mean_absolute_error: 0.339, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7414, predictive_accuracy: 0.7408, prior_entropy: 0.9998, recall: 0.7408, relative_absolute_error: 0.6782, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.416, root_relative_squared_error: 0.8322, scimark_benchmark: 947.9494, usercpu_time_millis: 410, usercpu_time_millis_training: 410,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.675, build_cpu_time: 4.8139, build_memory: 380769012.2764, f_measure: 0.6379, kappa: 0.2756, kb_relative_information_score: 2250.4029, mean_absolute_error: 0.3626, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.6379, predictive_accuracy: 0.6379, prior_entropy: 0.9998, recall: 0.6379, relative_absolute_error: 0.7254, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.59, root_relative_squared_error: 1.1803, scimark_benchmark: 927.3354,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6857, build_cpu_time: 2.1552, build_memory: 934615208.8232, f_measure: 0.639, kappa: 0.2778, kb_relative_information_score: 2273.6727, mean_absolute_error: 0.3612, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.639, predictive_accuracy: 0.639, prior_entropy: 0.9998, recall: 0.639, relative_absolute_error: 0.7227, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5794, root_relative_squared_error: 1.1591, scimark_benchmark: 939.0159,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6843, build_cpu_time: 1.3344, build_memory: 771394961.7422, f_measure: 0.6379, kappa: 0.2755, kb_relative_information_score: 2147.5213, mean_absolute_error: 0.3696, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.6379, predictive_accuracy: 0.6379, prior_entropy: 0.9998, recall: 0.6379, relative_absolute_error: 0.7394, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5683, root_relative_squared_error: 1.1369, scimark_benchmark: 916.8903,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6666, build_cpu_time: 0.2633, build_memory: 561796803.5576, f_measure: 0.6236, kappa: 0.247, kb_relative_information_score: 1678.704, mean_absolute_error: 0.4005, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.6236, predictive_accuracy: 0.6237, prior_entropy: 0.9998, recall: 0.6237, relative_absolute_error: 0.8012, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.538, root_relative_squared_error: 1.0762, scimark_benchmark: 943.5504,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8081, build_cpu_time: 0.4056, build_memory: 926686128.3652, f_measure: 0.7352, kappa: 0.4703, kb_relative_information_score: 3060.0695, mean_absolute_error: 0.3281, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7352, predictive_accuracy: 0.7352, prior_entropy: 0.9998, recall: 0.7352, relative_absolute_error: 0.6565, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.423, root_relative_squared_error: 0.8462, scimark_benchmark: 929.5397,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8496, build_cpu_time: 4158.2509, build_memory: 44810654.9629, f_measure: 0.7665, kappa: 0.5332, kb_relative_information_score: 3482.1906, mean_absolute_error: 0.2995, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7671, predictive_accuracy: 0.7665, prior_entropy: 0.9998, recall: 0.7665, relative_absolute_error: 0.5992, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3997, root_relative_squared_error: 0.7996, scimark_benchmark: 937.9119,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8705, build_cpu_time: 8279.8146, build_memory: 307358988.0166, f_measure: 0.7817, kappa: 0.5636, kb_relative_information_score: 3885.6512, mean_absolute_error: 0.2735, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7821, predictive_accuracy: 0.7817, prior_entropy: 0.9998, recall: 0.7817, relative_absolute_error: 0.5472, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3855, root_relative_squared_error: 0.7712, scimark_benchmark: 937.9119,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9291, build_cpu_time: 63047.277, build_memory: 617135147.4424, f_measure: 0.8446, kappa: 0.6892, kb_relative_information_score: 5377.9784, mean_absolute_error: 0.1761, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.8447, predictive_accuracy: 0.8446, prior_entropy: 0.9998, recall: 0.8446, relative_absolute_error: 0.3522, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3381, root_relative_squared_error: 0.6763, scimark_benchmark: 942.0692,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8934, build_cpu_time: 16101.6746, build_memory: 988129504.0313, f_measure: 0.809, kappa: 0.6179, kb_relative_information_score: 4408.0924, mean_absolute_error: 0.2402, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.8091, predictive_accuracy: 0.809, prior_entropy: 0.9998, recall: 0.809, relative_absolute_error: 0.4806, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3672, root_relative_squared_error: 0.7345, scimark_benchmark: 943.8134,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.894, build_cpu_time: 999.1416, build_memory: 1689138017.5332, f_measure: 0.8794, kappa: 0.7587, kb_relative_information_score: 6203.2828, mean_absolute_error: 0.1214, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.8794, predictive_accuracy: 0.8794, prior_entropy: 0.9998, recall: 0.8794, relative_absolute_error: 0.2429, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.346, root_relative_squared_error: 0.6922, scimark_benchmark: 908.8705,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9081, build_cpu_time: 66.3073, build_memory: 431749562.8535, f_measure: 0.8298, kappa: 0.6596, kb_relative_information_score: 5400.4086, mean_absolute_error: 0.1705, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.8299, predictive_accuracy: 0.8298, prior_entropy: 0.9998, recall: 0.8298, relative_absolute_error: 0.341, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3821, root_relative_squared_error: 0.7644, scimark_benchmark: 902.712,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8667, build_cpu_time: 8.1375, build_memory: 495967151.3252, f_measure: 0.7795, kappa: 0.5589, kb_relative_information_score: 3835.9872, mean_absolute_error: 0.2775, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7795, predictive_accuracy: 0.7795, prior_entropy: 0.9998, recall: 0.7795, relative_absolute_error: 0.5552, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3887, root_relative_squared_error: 0.7775, scimark_benchmark: 937.6343,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8864, build_cpu_time: 15.3369, build_memory: 261671885.0176, f_measure: 0.7985, kappa: 0.5968, kb_relative_information_score: 4198.3499, mean_absolute_error: 0.254, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.7985, predictive_accuracy: 0.7985, prior_entropy: 0.9998, recall: 0.7985, relative_absolute_error: 0.5082, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3739, root_relative_squared_error: 0.7479, scimark_benchmark: 942.5053,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9214, build_cpu_time: 56.2922, build_memory: 733020725.4883, f_measure: 0.8357, kappa: 0.6713, kb_relative_information_score: 4984.1638, mean_absolute_error: 0.2036, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.8357, predictive_accuracy: 0.8357, prior_entropy: 0.9998, recall: 0.8357, relative_absolute_error: 0.4074, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3403, root_relative_squared_error: 0.6807, scimark_benchmark: 939.521,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9323, build_cpu_time: 119.6548, build_memory: 1779075941.0205, f_measure: 0.8478, kappa: 0.6956, kb_relative_information_score: 5327.4968, mean_absolute_error: 0.1809, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.848, predictive_accuracy: 0.8478, prior_entropy: 0.9998, recall: 0.8478, relative_absolute_error: 0.3619, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3285, root_relative_squared_error: 0.6572, scimark_benchmark: 934.8107,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9277, build_cpu_time: 36.5612, build_memory: 141363219.2266, f_measure: 0.8473, kappa: 0.6946, kb_relative_information_score: 5489.3314, mean_absolute_error: 0.1684, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.8474, predictive_accuracy: 0.8473, prior_entropy: 0.9998, recall: 0.8473, relative_absolute_error: 0.3368, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3426, root_relative_squared_error: 0.6854, scimark_benchmark: 925.481,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9274, build_cpu_time: 34.8449, build_memory: 691050207.5391, f_measure: 0.8473, kappa: 0.6945, kb_relative_information_score: 5484.3453, mean_absolute_error: 0.1687, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.8474, predictive_accuracy: 0.8473, prior_entropy: 0.9998, recall: 0.8473, relative_absolute_error: 0.3375, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.343, root_relative_squared_error: 0.686, scimark_benchmark: 939.6298,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.924, build_cpu_time: 32.902, build_memory: 671492509.4834, f_measure: 0.8438, kappa: 0.6874, kb_relative_information_score: 5408.5639, mean_absolute_error: 0.1736, mean_prior_absolute_error: 0.4998, number_of_instances: 8192, precision: 0.8438, predictive_accuracy: 0.8438, prior_entropy: 0.9998, recall: 0.8438, relative_absolute_error: 0.3474, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3465, root_relative_squared_error: 0.693, scimark_benchmark: 923.9118,

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