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: 0.6578, f_measure: 0.2803, kappa: 0.2411, kb_relative_information_score: 71.816, mean_absolute_error: 0.0695, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.2627, predictive_accuracy: 0.3835, prior_entropy: 3.7542, recall: 0.3835, relative_absolute_error: 0.8561, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1928, root_relative_squared_error: 0.9589, scimark_benchmark: 940.588,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7892, f_measure: 0.3673, kappa: 0.3296, kb_relative_information_score: 109.9019, mean_absolute_error: 0.065, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3421, predictive_accuracy: 0.4248, prior_entropy: 3.7542, recall: 0.4248, relative_absolute_error: 0.8007, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1809, root_relative_squared_error: 0.8994, scimark_benchmark: 931.0783,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.782, f_measure: 0.4141, kappa: 0.3616, kb_relative_information_score: 112.7724, mean_absolute_error: 0.0577, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3982, predictive_accuracy: 0.4366, prior_entropy: 3.7542, recall: 0.4366, relative_absolute_error: 0.71, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1914, root_relative_squared_error: 0.9521, scimark_benchmark: 906.9603,
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: 940.6874,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7744, f_measure: 0.395, kappa: 0.3526, kb_relative_information_score: 114.8454, mean_absolute_error: 0.0623, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3736, predictive_accuracy: 0.4307, prior_entropy: 3.7542, recall: 0.4307, relative_absolute_error: 0.7672, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1841, root_relative_squared_error: 0.9155, scimark_benchmark: 937.2388,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7433, f_measure: 0.3687, kappa: 0.3357, kb_relative_information_score: 116.7786, mean_absolute_error: 0.0618, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3374, predictive_accuracy: 0.4248, prior_entropy: 3.7542, recall: 0.4248, relative_absolute_error: 0.7611, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.188, root_relative_squared_error: 0.9351,
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: 939.8097,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6715, f_measure: 0.387, kappa: 0.3221, kb_relative_information_score: 103.1822, mean_absolute_error: 0.0595, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3929, predictive_accuracy: 0.3923, prior_entropy: 3.7542, recall: 0.3923, relative_absolute_error: 0.733, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2209, root_relative_squared_error: 1.0988, scimark_benchmark: 931.1904,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7902, f_measure: 0.4132, kappa: 0.3513, kb_relative_information_score: 118.8389, mean_absolute_error: 0.0594, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4091, predictive_accuracy: 0.4248, prior_entropy: 3.7542, recall: 0.4248, relative_absolute_error: 0.7317, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1928, root_relative_squared_error: 0.9586, scimark_benchmark: 935.7732,
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: 942.175,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7913, f_measure: 0.425, kappa: 0.3982, kb_relative_information_score: 118.7594, mean_absolute_error: 0.0638, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4465, predictive_accuracy: 0.469, prior_entropy: 3.7542, recall: 0.469, relative_absolute_error: 0.7852, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1803, root_relative_squared_error: 0.8965, scimark_benchmark: 939.6049,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7505, f_measure: 0.3658, kappa: 0.3184, kb_relative_information_score: 80.0656, mean_absolute_error: 0.0726, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3529, predictive_accuracy: 0.3982, prior_entropy: 3.7542, recall: 0.3982, relative_absolute_error: 0.8943, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1881, root_relative_squared_error: 0.9354, scimark_benchmark: 922.0429,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7221, f_measure: 0.3864, kappa: 0.348, kb_relative_information_score: 15.7165, mean_absolute_error: 0.0853, 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: 1.0503, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2049, root_relative_squared_error: 1.0189, scimark_benchmark: 942.9175,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7873, f_measure: 0.4142, kappa: 0.3524, kb_relative_information_score: 120.5809, mean_absolute_error: 0.0578, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4075, predictive_accuracy: 0.4248, prior_entropy: 3.7542, recall: 0.4248, relative_absolute_error: 0.7119, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1962, root_relative_squared_error: 0.9756, scimark_benchmark: 945.8041,
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: 935.1179,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7994, f_measure: 0.3247, kappa: 0.2877, kb_relative_information_score: 71.6715, mean_absolute_error: 0.0728, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3335, predictive_accuracy: 0.3923, prior_entropy: 3.7542, recall: 0.3923, relative_absolute_error: 0.896, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.189, root_relative_squared_error: 0.9401, scimark_benchmark: 944.8216,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7228, f_measure: 0.3474, kappa: 0.2884, kb_relative_information_score: 107.3764, mean_absolute_error: 0.0626, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3248, predictive_accuracy: 0.3864, prior_entropy: 3.7542, recall: 0.3864, relative_absolute_error: 0.7703, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1967, root_relative_squared_error: 0.9784, scimark_benchmark: 939.3132,
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: 938.725,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7824, f_measure: 0.4141, kappa: 0.3616, kb_relative_information_score: 112.53, mean_absolute_error: 0.0578, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3982, predictive_accuracy: 0.4366, prior_entropy: 3.7542, recall: 0.4366, relative_absolute_error: 0.7119, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1912, root_relative_squared_error: 0.9508, scimark_benchmark: 940.6371,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7302, f_measure: 0.3801, kappa: 0.3118, kb_relative_information_score: 88.4638, mean_absolute_error: 0.0656, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3752, predictive_accuracy: 0.3923, prior_entropy: 3.7542, recall: 0.3923, relative_absolute_error: 0.8077, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1938, root_relative_squared_error: 0.9637, scimark_benchmark: 939.5945,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8373, f_measure: 0.4534, kappa: 0.4213, kb_relative_information_score: 139.7803, mean_absolute_error: 0.0549, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4337, predictive_accuracy: 0.4926, prior_entropy: 3.7542, recall: 0.4926, relative_absolute_error: 0.6763, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1745, root_relative_squared_error: 0.8679,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8193, f_measure: 0.4339, kappa: 0.3845, kb_relative_information_score: 128.0274, mean_absolute_error: 0.058, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4212, predictive_accuracy: 0.4572, prior_entropy: 3.7542, recall: 0.4572, relative_absolute_error: 0.7147, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1808, root_relative_squared_error: 0.8991, scimark_benchmark: 575.2168,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7968, f_measure: 0.3851, kappa: 0.3559, kb_relative_information_score: 111.265, mean_absolute_error: 0.0655, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3624, predictive_accuracy: 0.4454, prior_entropy: 3.7542, recall: 0.4454, relative_absolute_error: 0.8072, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1804, root_relative_squared_error: 0.8973, scimark_benchmark: 576.6402,
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: 934.7364,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7221, f_measure: 0.3864, kappa: 0.348, kb_relative_information_score: 15.7165, mean_absolute_error: 0.0853, 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: 1.0503, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2049, root_relative_squared_error: 1.0189, scimark_benchmark: 943.4416,
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: 943.089,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7455, f_measure: 0.3351, kappa: 0.3079, kb_relative_information_score: 104.5717, mean_absolute_error: 0.0661, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3076, predictive_accuracy: 0.41, prior_entropy: 3.7542, recall: 0.41, relative_absolute_error: 0.8133, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1861, root_relative_squared_error: 0.9257, scimark_benchmark: 943.5518,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.793, f_measure: 0.4319, kappa: 0.4034, kb_relative_information_score: 120.9926, mean_absolute_error: 0.0632, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4563, predictive_accuracy: 0.472, prior_entropy: 3.7542, recall: 0.472, relative_absolute_error: 0.7778, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1803, root_relative_squared_error: 0.8968, scimark_benchmark: 947.5062,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7994, f_measure: 0.3247, kappa: 0.2877, kb_relative_information_score: 71.6715, mean_absolute_error: 0.0728, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3335, predictive_accuracy: 0.3923, prior_entropy: 3.7542, recall: 0.3923, relative_absolute_error: 0.896, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.189, root_relative_squared_error: 0.9401, scimark_benchmark: 1059.8591, usercpu_time_millis: 120, usercpu_time_millis_testing: 120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8404, f_measure: 0.4589, kappa: 0.4238, kb_relative_information_score: 140.3374, mean_absolute_error: 0.0553, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4444, predictive_accuracy: 0.4926, prior_entropy: 3.7542, recall: 0.4926, relative_absolute_error: 0.6804, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1745, root_relative_squared_error: 0.8679, scimark_benchmark: 918.0213, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8202, f_measure: 0.4319, kappa: 0.3985, kb_relative_information_score: 132.0644, mean_absolute_error: 0.0577, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4138, predictive_accuracy: 0.472, prior_entropy: 3.7542, recall: 0.472, relative_absolute_error: 0.7108, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1782, root_relative_squared_error: 0.8861, scimark_benchmark: 935.5075, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8404, f_measure: 0.4589, kappa: 0.4238, kb_relative_information_score: 140.3374, mean_absolute_error: 0.0553, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4444, predictive_accuracy: 0.4926, prior_entropy: 3.7542, recall: 0.4926, relative_absolute_error: 0.6804, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1745, root_relative_squared_error: 0.8679, scimark_benchmark: 932.5646, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.801, f_measure: 0.4187, kappa: 0.3707, kb_relative_information_score: 117.0588, mean_absolute_error: 0.0609, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3999, predictive_accuracy: 0.4484, prior_entropy: 3.7542, recall: 0.4484, relative_absolute_error: 0.7503, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.18, root_relative_squared_error: 0.895, scimark_benchmark: 1371.9645, usercpu_time_millis: 120, usercpu_time_millis_training: 120,
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: 1326.8946, usercpu_time_millis: 240, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 200,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8404, f_measure: 0.4589, kappa: 0.4238, kb_relative_information_score: 140.3374, mean_absolute_error: 0.0553, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4444, predictive_accuracy: 0.4926, prior_entropy: 3.7542, recall: 0.4926, relative_absolute_error: 0.6804, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1745, root_relative_squared_error: 0.8679, scimark_benchmark: 1340.5125,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8404, f_measure: 0.4589, kappa: 0.4238, kb_relative_information_score: 140.3374, mean_absolute_error: 0.0553, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4444, predictive_accuracy: 0.4926, prior_entropy: 3.7542, recall: 0.4926, relative_absolute_error: 0.6804, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1745, root_relative_squared_error: 0.8679, scimark_benchmark: 1322.5413, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8404, f_measure: 0.4589, kappa: 0.4238, kb_relative_information_score: 140.3374, mean_absolute_error: 0.0553, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4444, predictive_accuracy: 0.4926, prior_entropy: 3.7542, recall: 0.4926, relative_absolute_error: 0.6804, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1745, root_relative_squared_error: 0.8679, scimark_benchmark: 1362.9924, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8404, f_measure: 0.4589, kappa: 0.4238, kb_relative_information_score: 140.3374, mean_absolute_error: 0.0553, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4444, predictive_accuracy: 0.4926, prior_entropy: 3.7542, recall: 0.4926, relative_absolute_error: 0.6804, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1745, root_relative_squared_error: 0.8679, scimark_benchmark: 1303.5632,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8404, f_measure: 0.4589, kappa: 0.4238, kb_relative_information_score: 140.3374, mean_absolute_error: 0.0553, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4444, predictive_accuracy: 0.4926, prior_entropy: 3.7542, recall: 0.4926, relative_absolute_error: 0.6804, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1745, root_relative_squared_error: 0.8679, scimark_benchmark: 1303.5632,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6307, f_measure: 0.3102, kappa: 0.2744, kb_relative_information_score: 98.6482, mean_absolute_error: 0.0539, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.2705, predictive_accuracy: 0.4071, prior_entropy: 3.7542, recall: 0.4071, relative_absolute_error: 0.6637, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.2322, root_relative_squared_error: 1.1546, scimark_benchmark: 1346.2927, usercpu_time_millis: 90, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8404, f_measure: 0.4589, kappa: 0.4238, kb_relative_information_score: 140.3374, mean_absolute_error: 0.0553, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4444, predictive_accuracy: 0.4926, prior_entropy: 3.7542, recall: 0.4926, relative_absolute_error: 0.6804, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1745, root_relative_squared_error: 0.8679, scimark_benchmark: 1362.9924,
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: 1309.4998,
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: 1325.7874, usercpu_time_millis: 220, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8404, f_measure: 0.4589, kappa: 0.4238, kb_relative_information_score: 140.3374, mean_absolute_error: 0.0553, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4444, predictive_accuracy: 0.4926, prior_entropy: 3.7542, recall: 0.4926, relative_absolute_error: 0.6804, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1745, root_relative_squared_error: 0.8679, scimark_benchmark: 1324.7884,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7892, f_measure: 0.3673, kappa: 0.3296, kb_relative_information_score: 109.9019, mean_absolute_error: 0.065, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.3421, predictive_accuracy: 0.4248, prior_entropy: 3.7542, recall: 0.4248, relative_absolute_error: 0.8007, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1809, root_relative_squared_error: 0.8994, scimark_benchmark: 1324.7884, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8404, f_measure: 0.4589, kappa: 0.4238, kb_relative_information_score: 140.3374, mean_absolute_error: 0.0553, mean_prior_absolute_error: 0.0812, number_of_instances: 339, precision: 0.4444, predictive_accuracy: 0.4926, prior_entropy: 3.7542, recall: 0.4926, relative_absolute_error: 0.6804, root_mean_prior_squared_error: 0.2011, root_mean_squared_error: 0.1745, root_relative_squared_error: 0.8679, scimark_benchmark: 1322.5413, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,

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