OpenML
Supervised Classification on primary-tumor

Supervised Classification on primary-tumor

Task 2065 Supervised Classification primary-tumor 543 runs submitted
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  • study_1 study_107 study_41 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8078, f_measure: 0.346, kappa: 0.3208, kb_relative_information_score: 87.3461, mean_absolute_error: 0.0712, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3423, predictive_accuracy: 0.4366, prior_entropy: 3.7542, recall: 0.4366, relative_absolute_error: 0.8764, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1837, root_relative_squared_error: 0.9136, scimark_benchmark: 1301.9956, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8296, f_measure: 0.4366, kappa: 0.379, kb_relative_information_score: 130.5998, mean_absolute_error: 0.0557, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4346, predictive_accuracy: 0.4454, prior_entropy: 3.7542, recall: 0.4454, relative_absolute_error: 0.6855, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1854, root_relative_squared_error: 0.9219, scimark_benchmark: 942.9518, usercpu_time_millis: 200, usercpu_time_millis_training: 200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.837, f_measure: 0.4312, kappa: 0.3837, kb_relative_information_score: 133.8184, mean_absolute_error: 0.0559, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4151, predictive_accuracy: 0.4543, prior_entropy: 3.7542, recall: 0.4543, relative_absolute_error: 0.6887, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1793, root_relative_squared_error: 0.8916, scimark_benchmark: 942.9518, usercpu_time_millis: 110, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8109, f_measure: 0.3841, kappa: 0.3598, kb_relative_information_score: 110.2788, mean_absolute_error: 0.0653, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.369, predictive_accuracy: 0.4513, prior_entropy: 3.7542, recall: 0.4513, relative_absolute_error: 0.8047, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1791, root_relative_squared_error: 0.8908, scimark_benchmark: 1315.395, usercpu_time_millis: 550, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 530,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8132, f_measure: 0.3709, kappa: 0.3484, kb_relative_information_score: 111.6418, mean_absolute_error: 0.0651, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3374, predictive_accuracy: 0.4425, prior_entropy: 3.7542, recall: 0.4425, relative_absolute_error: 0.8022, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1789, root_relative_squared_error: 0.8898, scimark_benchmark: 939.449, usercpu_time_millis: 330, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 310,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8103, f_measure: 0.3677, kappa: 0.342, kb_relative_information_score: 110.0993, mean_absolute_error: 0.0653, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3331, predictive_accuracy: 0.4366, prior_entropy: 3.7542, recall: 0.4366, relative_absolute_error: 0.8037, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1795, root_relative_squared_error: 0.8928, scimark_benchmark: 940.3347, usercpu_time_millis: 160, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 150,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8029, f_measure: 0.3806, kappa: 0.3576, kb_relative_information_score: 108.3462, mean_absolute_error: 0.0653, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.349, predictive_accuracy: 0.4484, prior_entropy: 3.7542, recall: 0.4484, relative_absolute_error: 0.8044, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1803, root_relative_squared_error: 0.8965, scimark_benchmark: 1369.9744, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7172, f_measure: 0.3494, kappa: 0.3098, kb_relative_information_score: 108.2828, mean_absolute_error: 0.0635, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3189, predictive_accuracy: 0.4012, prior_entropy: 3.7542, recall: 0.4012, relative_absolute_error: 0.7813, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1944, root_relative_squared_error: 0.9669, scimark_benchmark: 869.6028, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6371, f_measure: 0.1864, kappa: 0.152, kb_relative_information_score: 55.41, mean_absolute_error: 0.0746, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.151, predictive_accuracy: 0.2891, prior_entropy: 3.7542, recall: 0.2891, relative_absolute_error: 0.9182, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1935, root_relative_squared_error: 0.9624, scimark_benchmark: 1304.9611,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6371, f_measure: 0.1864, kappa: 0.152, kb_relative_information_score: 55.41, mean_absolute_error: 0.0746, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.151, predictive_accuracy: 0.2891, prior_entropy: 3.7542, recall: 0.2891, relative_absolute_error: 0.9182, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1935, root_relative_squared_error: 0.9624, scimark_benchmark: 932.0242, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6371, f_measure: 0.1864, kappa: 0.152, kb_relative_information_score: 55.41, mean_absolute_error: 0.0746, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.151, predictive_accuracy: 0.2891, prior_entropy: 3.7542, recall: 0.2891, relative_absolute_error: 0.9182, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1935, root_relative_squared_error: 0.9624, scimark_benchmark: 1372.2145,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6371, f_measure: 0.1864, kappa: 0.152, kb_relative_information_score: 55.41, mean_absolute_error: 0.0746, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.151, predictive_accuracy: 0.2891, prior_entropy: 3.7542, recall: 0.2891, relative_absolute_error: 0.9182, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1935, root_relative_squared_error: 0.9624, scimark_benchmark: 889.3151,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6371, f_measure: 0.1864, kappa: 0.152, kb_relative_information_score: 55.41, mean_absolute_error: 0.0746, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.151, predictive_accuracy: 0.2891, prior_entropy: 3.7542, recall: 0.2891, relative_absolute_error: 0.9182, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1935, root_relative_squared_error: 0.9624, scimark_benchmark: 825.5282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7837, f_measure: 0.4283, kappa: 0.3962, kb_relative_information_score: 123.7883, mean_absolute_error: 0.0621, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4178, predictive_accuracy: 0.4661, prior_entropy: 3.7542, recall: 0.4661, relative_absolute_error: 0.7652, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1818, root_relative_squared_error: 0.9041, scimark_benchmark: 1324.8395, usercpu_time_millis: 30, usercpu_time_millis_testing: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7783, f_measure: 0.4154, kappa: 0.3741, kb_relative_information_score: 124.0009, mean_absolute_error: 0.0612, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4013, predictive_accuracy: 0.4484, prior_entropy: 3.7542, recall: 0.4484, relative_absolute_error: 0.7541, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1852, root_relative_squared_error: 0.9212, scimark_benchmark: 889.3151, usercpu_time_millis: 40, usercpu_time_millis_testing: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5603, f_measure: 0.0984, kb_relative_information_score: 10.5299, mean_absolute_error: 0.0842, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.0614, predictive_accuracy: 0.2478, prior_entropy: 3.7542, recall: 0.2478, relative_absolute_error: 1.0372, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.204, root_relative_squared_error: 1.0144, scimark_benchmark: 918.6005, usercpu_time_millis: 1000, usercpu_time_millis_testing: 300, usercpu_time_millis_training: 700,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7918, f_measure: 0.4385, kappa: 0.3976, kb_relative_information_score: 27.5214, mean_absolute_error: 0.0836, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4177, predictive_accuracy: 0.4749, prior_entropy: 3.7542, recall: 0.4749, relative_absolute_error: 1.0296, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2024, root_relative_squared_error: 1.0063, scimark_benchmark: 1318.1432, usercpu_time_millis: 770, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 760,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8217, f_measure: 0.4336, kappa: 0.3956, kb_relative_information_score: 126.4268, mean_absolute_error: 0.0595, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4123, predictive_accuracy: 0.472, prior_entropy: 3.7542, recall: 0.472, relative_absolute_error: 0.7323, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1775, root_relative_squared_error: 0.8825, scimark_benchmark: 938.202, usercpu_time_millis: 670, usercpu_time_millis_training: 670,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7029, f_measure: 0.4328, kappa: 0.4023, kb_relative_information_score: 131.464, mean_absolute_error: 0.0475, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4071, predictive_accuracy: 0.4779, prior_entropy: 3.7542, recall: 0.4779, relative_absolute_error: 0.5845, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2179, root_relative_squared_error: 1.0835, scimark_benchmark: 916.9356, usercpu_time_millis: 110, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.836, f_measure: 0.4664, kappa: 0.4408, kb_relative_information_score: 137.2529, mean_absolute_error: 0.0565, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4457, predictive_accuracy: 0.5074, prior_entropy: 3.7542, recall: 0.5074, relative_absolute_error: 0.6954, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1746, root_relative_squared_error: 0.8684, scimark_benchmark: 1072.3689, usercpu_time_millis: 720, usercpu_time_millis_testing: 320, usercpu_time_millis_training: 400,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7934, f_measure: 0.4085, kappa: 0.3623, kb_relative_information_score: 115.1541, mean_absolute_error: 0.0625, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.395, predictive_accuracy: 0.4395, prior_entropy: 3.7542, recall: 0.4395, relative_absolute_error: 0.7691, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1852, root_relative_squared_error: 0.9211, scimark_benchmark: 1319.9043, usercpu_time_millis: 310, usercpu_time_millis_testing: 100, usercpu_time_millis_training: 210,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.675, f_measure: 0.3532, kappa: 0.2813, kb_relative_information_score: 101.2104, mean_absolute_error: 0.0613, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.349, predictive_accuracy: 0.3628, prior_entropy: 3.7542, recall: 0.3628, relative_absolute_error: 0.7542, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2189, root_relative_squared_error: 1.0886, scimark_benchmark: 1315.3881, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7495, f_measure: 0.346, kappa: 0.3185, kb_relative_information_score: 105.756, mean_absolute_error: 0.0658, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3157, predictive_accuracy: 0.4159, prior_entropy: 3.7542, recall: 0.4159, relative_absolute_error: 0.81, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1858, root_relative_squared_error: 0.924, scimark_benchmark: 1280.6952,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7222, f_measure: 0.342, kappa: 0.3055, kb_relative_information_score: 97.2, mean_absolute_error: 0.0661, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3073, predictive_accuracy: 0.3982, prior_entropy: 3.7542, recall: 0.3982, relative_absolute_error: 0.814, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1892, root_relative_squared_error: 0.9408, scimark_benchmark: 1354.2491, usercpu_time_millis: 160, usercpu_time_millis_training: 160,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.652, f_measure: 0.3705, kappa: 0.2961, kb_relative_information_score: 101.6264, mean_absolute_error: 0.0569, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3756, predictive_accuracy: 0.3746, prior_entropy: 3.7542, recall: 0.3746, relative_absolute_error: 0.7001, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2384, root_relative_squared_error: 1.1858, scimark_benchmark: 1280.6952, usercpu_time_millis: 60, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6127, f_measure: 0.2972, kappa: 0.2314, kb_relative_information_score: 87.3374, mean_absolute_error: 0.0582, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.331, predictive_accuracy: 0.3599, prior_entropy: 3.7542, recall: 0.3599, relative_absolute_error: 0.7166, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2412, root_relative_squared_error: 1.1997, scimark_benchmark: 1384.4418, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7251, f_measure: 0.3898, kappa: 0.3419, kb_relative_information_score: 114.0234, mean_absolute_error: 0.0614, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3746, predictive_accuracy: 0.4218, prior_entropy: 3.7542, recall: 0.4218, relative_absolute_error: 0.756, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1939, root_relative_squared_error: 0.9643, scimark_benchmark: 1339.4189, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5332, f_measure: 0.1661, kappa: 0.0732, kb_relative_information_score: 53.097, mean_absolute_error: 0.066, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.1436, predictive_accuracy: 0.2743, prior_entropy: 3.7542, recall: 0.2743, relative_absolute_error: 0.8123, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2568, root_relative_squared_error: 1.2773, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6617, f_measure: 0.3671, kappa: 0.3188, kb_relative_information_score: 108.3965, mean_absolute_error: 0.0547, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3476, predictive_accuracy: 0.3982, prior_entropy: 3.7542, recall: 0.3982, relative_absolute_error: 0.6736, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2339, root_relative_squared_error: 1.1632, scimark_benchmark: 1466.6185, usercpu_time_millis: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4473, f_measure: 0.0984, kb_relative_information_score: 0.3006, mean_absolute_error: 0.0813, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.0614, predictive_accuracy: 0.2478, prior_entropy: 3.7542, recall: 0.2478, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2012, root_relative_squared_error: 1.0004, scimark_benchmark: 1054.3694,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7172, f_measure: 0.3864, kappa: 0.348, kb_relative_information_score: 113.4721, mean_absolute_error: 0.0613, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3625, predictive_accuracy: 0.4336, prior_entropy: 3.7542, recall: 0.4336, relative_absolute_error: 0.7542, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1945, root_relative_squared_error: 0.967, scimark_benchmark: 1066.833,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.762, f_measure: 0.4616, kappa: 0.4343, kb_relative_information_score: 74.7031, mean_absolute_error: 0.0709, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4396, predictive_accuracy: 0.5015, prior_entropy: 3.7542, recall: 0.5015, relative_absolute_error: 0.873, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1908, root_relative_squared_error: 0.9491, scimark_benchmark: 942.3168, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7582, f_measure: 0.4664, kappa: 0.4408, kb_relative_information_score: 70.7118, mean_absolute_error: 0.0714, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4457, predictive_accuracy: 0.5074, prior_entropy: 3.7542, recall: 0.5074, relative_absolute_error: 0.8797, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.192, root_relative_squared_error: 0.9549, scimark_benchmark: 942.6953, usercpu_time_millis: 70, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7582, f_measure: 0.4664, kappa: 0.4408, kb_relative_information_score: 70.7118, mean_absolute_error: 0.0714, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4457, predictive_accuracy: 0.5074, prior_entropy: 3.7542, recall: 0.5074, relative_absolute_error: 0.8797, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.192, root_relative_squared_error: 0.9549, scimark_benchmark: 922.9039, usercpu_time_millis: 70, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7582, f_measure: 0.4664, kappa: 0.4408, kb_relative_information_score: 70.7118, mean_absolute_error: 0.0714, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4457, predictive_accuracy: 0.5074, prior_entropy: 3.7542, recall: 0.5074, relative_absolute_error: 0.8797, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.192, root_relative_squared_error: 0.9549, scimark_benchmark: 942.1229, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7582, f_measure: 0.4664, kappa: 0.4408, kb_relative_information_score: 70.7118, mean_absolute_error: 0.0714, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4457, predictive_accuracy: 0.5074, prior_entropy: 3.7542, recall: 0.5074, relative_absolute_error: 0.8797, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.192, root_relative_squared_error: 0.9549, scimark_benchmark: 941.7954, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6371, f_measure: 0.1864, kappa: 0.152, kb_relative_information_score: 55.41, mean_absolute_error: 0.0746, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.151, predictive_accuracy: 0.2891, prior_entropy: 3.7542, recall: 0.2891, relative_absolute_error: 0.9182, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1935, root_relative_squared_error: 0.9624, scimark_benchmark: 876.8277, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6185, build_cpu_time: 0.025, build_memory: 988925112.118, f_measure: 0.2743, kappa: 0.2249, kb_relative_information_score: 67.2716, mean_absolute_error: 0.07, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.2418, predictive_accuracy: 0.3746, prior_entropy: 3.7542, recall: 0.3746, relative_absolute_error: 0.8621, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1944, root_relative_squared_error: 0.9668, scimark_benchmark: 933.4498,
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Metric:

Timeline

Plotting contribution timeline

Leaderboard

Rank Name Top Score Entries Highest rank

Note: The leaderboard ignores resubmissions of previous solutions, as well as parameter variations that do not improve performance.

Challenge

In supervised classification, you are given an input dataset in which instances are labeled with a certain class. The goal is to build a model that predicts the class for future unlabeled instances. The model is evaluated using a train-test procedure, e.g. cross-validation.

To make results by different users comparable, you are given the exact train-test folds to be used, and you need to return at least the predictions generated by your model for each of the test instances. OpenML will use these predictions to calculate a range of evaluation measures on the server.

You can also upload your own evaluation measures, provided that the code for doing so is available from the implementation used. For extremely large datasets, it may be infeasible to upload all predictions. In those cases, you need to compute and provide the evaluations yourself.

Optionally, you can upload the model trained on all the input data. There is no restriction on the file format, but please use a well-known format or PMML.

Given inputs

Expected outputs

evaluations A list of user-defined evaluations of the task as key-value pairs. KeyValue (optional)
model A file containing the model built on all the input data. File (optional)
predictions The desired output format Predictions (optional)

How to submit runs

Using your favorite machine learning environment

Download this task directly in your environment and automatically upload your results

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From your own software

Use one of our APIs to download data from OpenML and upload your results

OpenML APIs