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OpenML
OpenML
Supervised Classification on schlvote

Supervised Classification on schlvote

Task 3713 Supervised Classification schlvote 523 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_41 under100k under1m
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523 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5375, f_measure: 0.7334, kappa: 0.2723, kb_relative_information_score: 2.8379, mean_absolute_error: 0.3365, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.7384, predictive_accuracy: 0.7632, prior_entropy: 0.8485, recall: 0.7632, relative_absolute_error: 0.8554, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4692, root_relative_squared_error: 1.0652, scimark_benchmark: 942.9518,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6786, f_measure: 0.759, kappa: 0.369, kb_relative_information_score: 12.5832, mean_absolute_error: 0.2368, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.756, predictive_accuracy: 0.7632, prior_entropy: 0.8485, recall: 0.7632, relative_absolute_error: 0.602, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4867, root_relative_squared_error: 1.1048, scimark_benchmark: 1313.9994,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6252, kb_relative_information_score: 9.8416, mean_absolute_error: 0.2632, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.5429, predictive_accuracy: 0.7368, prior_entropy: 0.8485, recall: 0.7368, relative_absolute_error: 0.6689, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.513, root_relative_squared_error: 1.1645, scimark_benchmark: 916.6405,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6252, kb_relative_information_score: 9.8416, mean_absolute_error: 0.2632, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.5429, predictive_accuracy: 0.7368, prior_entropy: 0.8485, recall: 0.7368, relative_absolute_error: 0.6689, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.513, root_relative_squared_error: 1.1645, scimark_benchmark: 1337.7959, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6089, f_measure: 0.6487, kappa: 0.0369, kb_relative_information_score: -0.0882, mean_absolute_error: 0.3675, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.6351, predictive_accuracy: 0.7105, prior_entropy: 0.8485, recall: 0.7105, relative_absolute_error: 0.9342, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4427, root_relative_squared_error: 1.005, scimark_benchmark: 930.5999,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5071, f_measure: 0.6111, kappa: 0.0138, kb_relative_information_score: -3.8668, mean_absolute_error: 0.3947, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.6176, predictive_accuracy: 0.6053, prior_entropy: 0.8485, recall: 0.6053, relative_absolute_error: 1.0033, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.6283, root_relative_squared_error: 1.4263, scimark_benchmark: 916.5955,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6929, f_measure: 0.6656, kappa: 0.0865, kb_relative_information_score: 4.1393, mean_absolute_error: 0.3365, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.6842, predictive_accuracy: 0.7368, prior_entropy: 0.8485, recall: 0.7368, relative_absolute_error: 0.8553, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4167, root_relative_squared_error: 0.9459, scimark_benchmark: 933.3136, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6839, f_measure: 0.759, kappa: 0.369, kb_relative_information_score: 7.4932, mean_absolute_error: 0.3039, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.756, predictive_accuracy: 0.7632, prior_entropy: 0.8485, recall: 0.7632, relative_absolute_error: 0.7726, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4048, root_relative_squared_error: 0.919, scimark_benchmark: 1336.2509, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7607, f_measure: 0.7951, kappa: 0.4899, kb_relative_information_score: 15.3249, mean_absolute_error: 0.2105, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.8053, predictive_accuracy: 0.7895, prior_entropy: 0.8485, recall: 0.7895, relative_absolute_error: 0.5351, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4588, root_relative_squared_error: 1.0416, scimark_benchmark: 1313.5726,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6179, f_measure: 0.7325, kappa: 0.2692, kb_relative_information_score: 7.9466, mean_absolute_error: 0.3124, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.8363, predictive_accuracy: 0.7895, prior_entropy: 0.8485, recall: 0.7895, relative_absolute_error: 0.7941, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4046, root_relative_squared_error: 0.9186, scimark_benchmark: 1066.7184,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5661, f_measure: 0.7545, kappa: 0.3274, kb_relative_information_score: 9.1917, mean_absolute_error: 0.297, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.7825, predictive_accuracy: 0.7895, prior_entropy: 0.8485, recall: 0.7895, relative_absolute_error: 0.7548, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4204, root_relative_squared_error: 0.9544, scimark_benchmark: 1336.3256, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.7487, kappa: 0.3987, kb_relative_information_score: 9.8416, mean_absolute_error: 0.2632, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.7763, predictive_accuracy: 0.7368, prior_entropy: 0.8485, recall: 0.7368, relative_absolute_error: 0.6689, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.513, root_relative_squared_error: 1.1645, scimark_benchmark: 1341.5768,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4464, f_measure: 0.5848, kappa: -0.1382, kb_relative_information_score: 1.6165, mean_absolute_error: 0.3421, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.5263, predictive_accuracy: 0.6579, prior_entropy: 0.8485, recall: 0.6579, relative_absolute_error: 0.8696, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.5849, root_relative_squared_error: 1.3278, scimark_benchmark: 1290.1085,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7518, f_measure: 0.8519, kappa: 0.5957, kb_relative_information_score: 19.3633, mean_absolute_error: 0.1923, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.8884, predictive_accuracy: 0.8684, prior_entropy: 0.8485, recall: 0.8684, relative_absolute_error: 0.4887, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3374, root_relative_squared_error: 0.766, scimark_benchmark: 1392.1129,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4643, f_measure: 0.5987, kappa: -0.0962, kb_relative_information_score: 4.3582, mean_absolute_error: 0.3158, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.5322, predictive_accuracy: 0.6842, prior_entropy: 0.8485, recall: 0.6842, relative_absolute_error: 0.8027, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.562, root_relative_squared_error: 1.2757, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7321, f_measure: 0.8276, kappa: 0.5328, kb_relative_information_score: 20.8083, mean_absolute_error: 0.1579, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.841, predictive_accuracy: 0.8421, prior_entropy: 0.8485, recall: 0.8421, relative_absolute_error: 0.4013, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3974, root_relative_squared_error: 0.9021, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4714, f_measure: 0.6252, kb_relative_information_score: -0.2513, mean_absolute_error: 0.3943, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.5429, predictive_accuracy: 0.7368, prior_entropy: 0.8485, recall: 0.7368, relative_absolute_error: 1.0023, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4408, root_relative_squared_error: 1.0006, scimark_benchmark: 1505.597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5982, f_measure: 0.8159, kappa: 0.4956, kb_relative_information_score: 14.7816, mean_absolute_error: 0.2437, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.87, predictive_accuracy: 0.8421, prior_entropy: 0.8485, recall: 0.8421, relative_absolute_error: 0.6194, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3674, root_relative_squared_error: 0.8339, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3929, f_measure: 0.5263, kappa: -0.2214, kb_relative_information_score: -12.8405, mean_absolute_error: 0.4734, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.5263, predictive_accuracy: 0.5263, prior_entropy: 0.8485, recall: 0.5263, relative_absolute_error: 1.2032, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.5876, root_relative_squared_error: 1.334, scimark_benchmark: 931.2336,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3607, f_measure: 0.5074, kappa: -0.2491, kb_relative_information_score: -15.5054, mean_absolute_error: 0.4965, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.5152, predictive_accuracy: 0.5, prior_entropy: 0.8485, recall: 0.5, relative_absolute_error: 1.2621, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.5757, root_relative_squared_error: 1.3069, scimark_benchmark: 941.7954,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3607, f_measure: 0.5074, kappa: -0.2491, kb_relative_information_score: -15.5054, mean_absolute_error: 0.4965, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.5152, predictive_accuracy: 0.5, prior_entropy: 0.8485, recall: 0.5, relative_absolute_error: 1.2621, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.5757, root_relative_squared_error: 1.3069, scimark_benchmark: 923.7642, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3607, f_measure: 0.5074, kappa: -0.2491, kb_relative_information_score: -15.5054, mean_absolute_error: 0.4965, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.5152, predictive_accuracy: 0.5, prior_entropy: 0.8485, recall: 0.5, relative_absolute_error: 1.2621, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.5757, root_relative_squared_error: 1.3069, scimark_benchmark: 894.7455, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7, f_measure: 0.7814, kappa: 0.4198, kb_relative_information_score: 15.8125, mean_absolute_error: 0.204, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.7785, predictive_accuracy: 0.7895, prior_entropy: 0.8485, recall: 0.7895, relative_absolute_error: 0.5185, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4461, root_relative_squared_error: 1.0126, scimark_benchmark: 894.7455, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, f_measure: 0.8126, kappa: 0.5092, kb_relative_information_score: 16.4105, mean_absolute_error: 0.2008, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.8106, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.5103, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4351, root_relative_squared_error: 0.9878, scimark_benchmark: 938.2848, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6893, f_measure: 0.759, kappa: 0.369, kb_relative_information_score: 13.9183, mean_absolute_error: 0.2227, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.756, predictive_accuracy: 0.7632, prior_entropy: 0.8485, recall: 0.7632, relative_absolute_error: 0.5661, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.455, root_relative_squared_error: 1.0329, scimark_benchmark: 936.6206, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6536, f_measure: 0.7483, kappa: 0.3241, kb_relative_information_score: 12.9859, mean_absolute_error: 0.2315, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.7446, predictive_accuracy: 0.7632, prior_entropy: 0.8485, recall: 0.7632, relative_absolute_error: 0.5883, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4714, root_relative_squared_error: 1.07, scimark_benchmark: 922.9039,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6071, f_measure: 0.7926, kappa: 0.434, kb_relative_information_score: 16.1711, mean_absolute_error: 0.2024, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.8134, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.5145, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4319, root_relative_squared_error: 0.9805, scimark_benchmark: 938.4278,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7268, f_measure: 0.7212, kappa: 0.3192, kb_relative_information_score: 7.7285, mean_absolute_error: 0.2806, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.7404, predictive_accuracy: 0.7105, prior_entropy: 0.8485, recall: 0.7105, relative_absolute_error: 0.7133, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.5095, root_relative_squared_error: 1.1566, scimark_benchmark: 936.6206, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6661, f_measure: 0.7439, kappa: 0.3624, kb_relative_information_score: 8.5963, mean_absolute_error: 0.2704, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.7551, predictive_accuracy: 0.7368, prior_entropy: 0.8485, recall: 0.7368, relative_absolute_error: 0.6873, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.477, root_relative_squared_error: 1.0829, scimark_benchmark: 924.6116, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6893, f_measure: 0.8126, kappa: 0.5092, kb_relative_information_score: 13.1679, mean_absolute_error: 0.2329, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.8106, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.592, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4261, root_relative_squared_error: 0.9672, scimark_benchmark: 924.6116,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.675, f_measure: 0.7895, kappa: 0.4571, kb_relative_information_score: 11.3478, mean_absolute_error: 0.2522, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.7895, predictive_accuracy: 0.7895, prior_entropy: 0.8485, recall: 0.7895, relative_absolute_error: 0.6411, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4293, root_relative_squared_error: 0.9746, scimark_benchmark: 947.9494,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6661, f_measure: 0.7666, kappa: 0.4083, kb_relative_information_score: 8.8543, mean_absolute_error: 0.28, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.7712, predictive_accuracy: 0.7632, prior_entropy: 0.8485, recall: 0.7632, relative_absolute_error: 0.7117, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4304, root_relative_squared_error: 0.9771, scimark_benchmark: 929.566,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4714, f_measure: 0.6252, kb_relative_information_score: -0.2513, mean_absolute_error: 0.3943, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.5429, predictive_accuracy: 0.7368, prior_entropy: 0.8485, recall: 0.7368, relative_absolute_error: 1.0023, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4408, root_relative_squared_error: 1.0006, scimark_benchmark: 938.9865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7607, f_measure: 0.6271, kappa: 0.248, kb_relative_information_score: -3.3065, mean_absolute_error: 0.383, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.7504, predictive_accuracy: 0.6053, prior_entropy: 0.8485, recall: 0.6053, relative_absolute_error: 0.9736, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.462, root_relative_squared_error: 1.0487, scimark_benchmark: 934.5243,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7607, f_measure: 0.8159, kappa: 0.4956, kb_relative_information_score: 13.7354, mean_absolute_error: 0.2386, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.87, predictive_accuracy: 0.8421, prior_entropy: 0.8485, recall: 0.8421, relative_absolute_error: 0.6065, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.3823, root_relative_squared_error: 0.8678, scimark_benchmark: 933.8635,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6821, build_cpu_time: 0.0136, build_memory: 500521169.6842, f_measure: 0.8126, kappa: 0.5092, kb_relative_information_score: 17.7428, mean_absolute_error: 0.1892, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.8106, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.4809, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4226, root_relative_squared_error: 0.9594, scimark_benchmark: 937.6343,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7143, build_cpu_time: 0.0414, build_memory: 387580768.4211, f_measure: 0.7895, kappa: 0.4571, kb_relative_information_score: 16.1872, mean_absolute_error: 0.2007, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.7895, predictive_accuracy: 0.7895, prior_entropy: 0.8485, recall: 0.7895, relative_absolute_error: 0.5101, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.439, root_relative_squared_error: 0.9967, scimark_benchmark: 916.1588,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7214, build_cpu_time: 0.057, build_memory: 75334788.2105, f_measure: 0.7895, kappa: 0.4571, kb_relative_information_score: 15.3137, mean_absolute_error: 0.2107, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.7895, predictive_accuracy: 0.7895, prior_entropy: 0.8485, recall: 0.7895, relative_absolute_error: 0.5356, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4588, root_relative_squared_error: 1.0415, scimark_benchmark: 937.279,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.725, build_cpu_time: 0.1649, build_memory: 259292882.5263, f_measure: 0.7895, kappa: 0.4571, kb_relative_information_score: 15.3249, mean_absolute_error: 0.2105, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.7895, predictive_accuracy: 0.7895, prior_entropy: 0.8485, recall: 0.7895, relative_absolute_error: 0.5351, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4588, root_relative_squared_error: 1.0416, scimark_benchmark: 920.7965,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7357, build_cpu_time: 0.2206, build_memory: 238937394.9474, f_measure: 0.8126, kappa: 0.5092, kb_relative_information_score: 18.0575, mean_absolute_error: 0.1844, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.8106, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.4686, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4292, root_relative_squared_error: 0.9743, scimark_benchmark: 920.2874,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7357, build_cpu_time: 0.0047, build_memory: 1555426596.6316, f_measure: 0.8126, kappa: 0.5092, kb_relative_information_score: 15.2962, mean_absolute_error: 0.2159, mean_prior_absolute_error: 0.3934, number_of_instances: 38, precision: 0.8106, predictive_accuracy: 0.8158, prior_entropy: 0.8485, recall: 0.8158, relative_absolute_error: 0.5487, root_mean_prior_squared_error: 0.4405, root_mean_squared_error: 0.4186, root_relative_squared_error: 0.9503, scimark_benchmark: 933.4498,

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