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OpenML
OpenML
Supervised Classification on cloud

Supervised Classification on cloud

Task 3753 Supervised Classification cloud 854 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • study_1 study_107 study_123 study_41 study_7 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.3553, f_measure: 0.4862, kappa: -0.2833, kb_relative_information_score: -24.6964, mean_absolute_error: 0.4724, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.4507, predictive_accuracy: 0.5278, prior_entropy: 0.8813, recall: 0.5278, relative_absolute_error: 1.1288, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.5574, root_relative_squared_error: 1.2207, scimark_benchmark: 1325.2092,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5074, f_measure: 0.6063, kappa: 0.0187, kb_relative_information_score: 18.0265, mean_absolute_error: 0.3241, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.5963, predictive_accuracy: 0.6759, prior_entropy: 0.8813, recall: 0.6759, relative_absolute_error: 0.7743, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.5693, root_relative_squared_error: 1.2467, scimark_benchmark: 1442.7264,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5813, kb_relative_information_score: 25.691, mean_absolute_error: 0.2963, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.4952, predictive_accuracy: 0.7037, prior_entropy: 0.8813, recall: 0.7037, relative_absolute_error: 0.708, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.5443, root_relative_squared_error: 1.192, scimark_benchmark: 1333.5799, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5813, kb_relative_information_score: 25.691, mean_absolute_error: 0.2963, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.4952, predictive_accuracy: 0.7037, prior_entropy: 0.8813, recall: 0.7037, relative_absolute_error: 0.708, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.5443, root_relative_squared_error: 1.192, scimark_benchmark: 1386.5717,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4677, f_measure: 0.5813, kb_relative_information_score: -3.4481, mean_absolute_error: 0.4191, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.4952, predictive_accuracy: 0.7037, prior_entropy: 0.8813, recall: 0.7037, relative_absolute_error: 1.0013, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.463, root_relative_squared_error: 1.0139, scimark_benchmark: 887.6719, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4605, f_measure: 0.5483, kappa: -0.0782, kb_relative_information_score: -17.741, mean_absolute_error: 0.4537, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.5503, predictive_accuracy: 0.5463, prior_entropy: 0.8813, recall: 0.5463, relative_absolute_error: 1.0841, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.6736, root_relative_squared_error: 1.4751, scimark_benchmark: 938.343, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4453, f_measure: 0.577, kappa: -0.0452, kb_relative_information_score: -7.1612, mean_absolute_error: 0.4273, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.5392, predictive_accuracy: 0.6667, prior_entropy: 0.8813, recall: 0.6667, relative_absolute_error: 1.021, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.481, root_relative_squared_error: 1.0533, scimark_benchmark: 929.0363, usercpu_time_millis: 100, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.815, f_measure: 0.8731, kappa: 0.6858, kb_relative_information_score: 74.2325, mean_absolute_error: 0.1204, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8832, predictive_accuracy: 0.8796, prior_entropy: 0.8813, recall: 0.8796, relative_absolute_error: 0.2876, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3469, root_relative_squared_error: 0.7598, scimark_benchmark: 1306.6379, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8826, f_measure: 0.845, kappa: 0.617, kb_relative_information_score: 54.3407, mean_absolute_error: 0.2112, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8501, predictive_accuracy: 0.8519, prior_entropy: 0.8813, recall: 0.8519, relative_absolute_error: 0.5047, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3393, root_relative_squared_error: 0.743, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8777, f_measure: 0.845, kappa: 0.617, kb_relative_information_score: 56.2012, mean_absolute_error: 0.201, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8501, predictive_accuracy: 0.8519, prior_entropy: 0.8813, recall: 0.8519, relative_absolute_error: 0.4802, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.344, root_relative_squared_error: 0.7533, scimark_benchmark: 1325.942,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8781, f_measure: 0.845, kappa: 0.617, kb_relative_information_score: 56.4618, mean_absolute_error: 0.1997, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8501, predictive_accuracy: 0.8519, prior_entropy: 0.8813, recall: 0.8519, relative_absolute_error: 0.4772, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3426, root_relative_squared_error: 0.7502, scimark_benchmark: 932.251,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8828, f_measure: 0.845, kappa: 0.617, kb_relative_information_score: 51.2705, mean_absolute_error: 0.227, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8501, predictive_accuracy: 0.8519, prior_entropy: 0.8813, recall: 0.8519, relative_absolute_error: 0.5423, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3391, root_relative_squared_error: 0.7425, scimark_benchmark: 924.1296, usercpu_time_millis: 90, usercpu_time_millis_training: 90,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.721, f_measure: 0.695, kappa: 0.2373, kb_relative_information_score: 14.3465, mean_absolute_error: 0.3563, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.6963, predictive_accuracy: 0.7222, prior_entropy: 0.8813, recall: 0.7222, relative_absolute_error: 0.8513, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4211, root_relative_squared_error: 0.9222, scimark_benchmark: 1280.6952, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5074, f_measure: 0.5808, kappa: 0.0143, kb_relative_information_score: -10.0765, mean_absolute_error: 0.4259, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.589, predictive_accuracy: 0.5741, prior_entropy: 0.8813, recall: 0.5741, relative_absolute_error: 1.0177, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.6526, root_relative_squared_error: 1.4292, scimark_benchmark: 1313.5726,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9132, f_measure: 0.9074, kappa: 0.778, kb_relative_information_score: 75.3209, mean_absolute_error: 0.1259, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.9074, predictive_accuracy: 0.9074, prior_entropy: 0.8813, recall: 0.9074, relative_absolute_error: 0.3008, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.2978, root_relative_squared_error: 0.6521, scimark_benchmark: 1372.2145,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8886, f_measure: 0.8691, kappa: 0.6834, kb_relative_information_score: 67.8643, mean_absolute_error: 0.1498, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8686, predictive_accuracy: 0.8704, prior_entropy: 0.8813, recall: 0.8704, relative_absolute_error: 0.3579, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3443, root_relative_squared_error: 0.754, scimark_benchmark: 1354.2491, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.5913, kb_relative_information_score: -2.412, mean_absolute_error: 0.3981, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.583, predictive_accuracy: 0.6019, prior_entropy: 0.8813, recall: 0.6019, relative_absolute_error: 0.9513, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.631, root_relative_squared_error: 1.3818, scimark_benchmark: 1372.2145,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5066, f_measure: 0.3976, kappa: 0.0092, kb_relative_information_score: -56.0632, mean_absolute_error: 0.5926, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.5915, predictive_accuracy: 0.4074, prior_entropy: 0.8813, recall: 0.4074, relative_absolute_error: 1.4159, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.7698, root_relative_squared_error: 1.6858, scimark_benchmark: 1363.454,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.906, f_measure: 0.9177, kappa: 0.8054, kb_relative_information_score: 82.1079, mean_absolute_error: 0.0961, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.9203, predictive_accuracy: 0.9167, prior_entropy: 0.8813, recall: 0.9167, relative_absolute_error: 0.2295, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.2811, root_relative_squared_error: 0.6156, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6859, f_measure: 0.7683, kappa: 0.4212, kb_relative_information_score: 48.6843, mean_absolute_error: 0.213, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7797, predictive_accuracy: 0.787, prior_entropy: 0.8813, recall: 0.787, relative_absolute_error: 0.5089, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4615, root_relative_squared_error: 1.0106, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6546, f_measure: 0.7435, kappa: 0.3578, kb_relative_information_score: 43.5747, mean_absolute_error: 0.2315, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7582, predictive_accuracy: 0.7685, prior_entropy: 0.8813, recall: 0.7685, relative_absolute_error: 0.5531, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4811, root_relative_squared_error: 1.0536, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4597, f_measure: 0.5813, kb_relative_information_score: -0.3948, mean_absolute_error: 0.419, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.4952, predictive_accuracy: 0.7037, prior_entropy: 0.8813, recall: 0.7037, relative_absolute_error: 1.0011, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.457, root_relative_squared_error: 1.0007, scimark_benchmark: 1505.597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9165, f_measure: 0.9177, kappa: 0.8054, kb_relative_information_score: 82.3815, mean_absolute_error: 0.0941, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.9203, predictive_accuracy: 0.9167, prior_entropy: 0.8813, recall: 0.9167, relative_absolute_error: 0.225, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.2818, root_relative_squared_error: 0.6172, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4698, f_measure: 0.5613, kappa: -0.0993, kb_relative_information_score: -6.8912, mean_absolute_error: 0.4204, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.5271, predictive_accuracy: 0.6204, prior_entropy: 0.8813, recall: 0.6204, relative_absolute_error: 1.0044, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.5265, root_relative_squared_error: 1.1531, scimark_benchmark: 927.0753,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4597, f_measure: 0.5613, kappa: -0.0993, kb_relative_information_score: -10.4373, mean_absolute_error: 0.4358, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.5271, predictive_accuracy: 0.6204, prior_entropy: 0.8813, recall: 0.6204, relative_absolute_error: 1.0414, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.499, root_relative_squared_error: 1.0928, scimark_benchmark: 941.7954, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4597, f_measure: 0.5613, kappa: -0.0993, kb_relative_information_score: -10.4373, mean_absolute_error: 0.4358, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.5271, predictive_accuracy: 0.6204, prior_entropy: 0.8813, recall: 0.6204, relative_absolute_error: 1.0414, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.499, root_relative_squared_error: 1.0928, scimark_benchmark: 923.7642, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4597, f_measure: 0.5613, kappa: -0.0993, kb_relative_information_score: -10.4373, mean_absolute_error: 0.4358, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.5271, predictive_accuracy: 0.6204, prior_entropy: 0.8813, recall: 0.6204, relative_absolute_error: 1.0414, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.499, root_relative_squared_error: 1.0928, scimark_benchmark: 894.7455, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8775, f_measure: 0.8256, kappa: 0.5691, kb_relative_information_score: 62.588, mean_absolute_error: 0.1633, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8294, predictive_accuracy: 0.8333, prior_entropy: 0.8813, recall: 0.8333, relative_absolute_error: 0.3901, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3825, root_relative_squared_error: 0.8376, scimark_benchmark: 936.7115, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8629, f_measure: 0.8002, kappa: 0.5018, kb_relative_information_score: 56.1244, mean_absolute_error: 0.1882, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8128, predictive_accuracy: 0.8148, prior_entropy: 0.8813, recall: 0.8148, relative_absolute_error: 0.4496, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4042, root_relative_squared_error: 0.8851, scimark_benchmark: 938.2848, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.787, f_measure: 0.726, kappa: 0.3147, kb_relative_information_score: 43.993, mean_absolute_error: 0.2287, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7793, predictive_accuracy: 0.7685, prior_entropy: 0.8813, recall: 0.7685, relative_absolute_error: 0.5464, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4469, root_relative_squared_error: 0.9787, scimark_benchmark: 911.3823, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6955, f_measure: 0.7107, kappa: 0.2827, kb_relative_information_score: 39.1607, mean_absolute_error: 0.249, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8258, predictive_accuracy: 0.7685, prior_entropy: 0.8813, recall: 0.7685, relative_absolute_error: 0.5949, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4607, root_relative_squared_error: 1.0089, scimark_benchmark: 934.5243, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6657, f_measure: 0.7107, kappa: 0.2827, kb_relative_information_score: 38.9183, mean_absolute_error: 0.2526, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8258, predictive_accuracy: 0.7685, prior_entropy: 0.8813, recall: 0.7685, relative_absolute_error: 0.6036, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4701, root_relative_squared_error: 1.0294, scimark_benchmark: 938.4278,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8859, f_measure: 0.917, kappa: 0.802, kb_relative_information_score: 83.4544, mean_absolute_error: 0.0886, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.9176, predictive_accuracy: 0.9167, prior_entropy: 0.8813, recall: 0.9167, relative_absolute_error: 0.2118, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.2891, root_relative_squared_error: 0.6331, scimark_benchmark: 938.4285, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8847, f_measure: 0.9074, kappa: 0.778, kb_relative_information_score: 77.4161, mean_absolute_error: 0.1181, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.9074, predictive_accuracy: 0.9074, prior_entropy: 0.8813, recall: 0.9074, relative_absolute_error: 0.2821, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.2944, root_relative_squared_error: 0.6448, scimark_benchmark: 924.6116, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8908, f_measure: 0.9074, kappa: 0.778, kb_relative_information_score: 66.5782, mean_absolute_error: 0.1673, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.9074, predictive_accuracy: 0.9074, prior_entropy: 0.8813, recall: 0.9074, relative_absolute_error: 0.3998, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3028, root_relative_squared_error: 0.6631, scimark_benchmark: 924.6116, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4597, build_cpu_time: 0.0036, build_memory: 2320620054.4444, f_measure: 0.5613, kappa: -0.0993, kb_relative_information_score: -10.4373, mean_absolute_error: 0.4358, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.5271, predictive_accuracy: 0.6204, prior_entropy: 0.8813, recall: 0.6204, relative_absolute_error: 1.0414, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.499, root_relative_squared_error: 1.0928, scimark_benchmark: 943.5504,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7492, build_cpu_time: 0.5096, build_memory: 43085901.7778, f_measure: 0.6585, kappa: 0.154, kb_relative_information_score: 24.0165, mean_absolute_error: 0.3042, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.6504, predictive_accuracy: 0.6759, prior_entropy: 0.8813, recall: 0.6759, relative_absolute_error: 0.727, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.459, root_relative_squared_error: 1.0052, scimark_benchmark: 929.5397,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8055, build_cpu_time: 1.1029, build_memory: 31848983.5556, f_measure: 0.7325, kappa: 0.3342, kb_relative_information_score: 38.6192, mean_absolute_error: 0.2549, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7334, predictive_accuracy: 0.75, prior_entropy: 0.8813, recall: 0.75, relative_absolute_error: 0.609, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4439, root_relative_squared_error: 0.972, scimark_benchmark: 939.521,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.817, build_cpu_time: 1.8196, build_memory: 966405812.3704, f_measure: 0.7675, kappa: 0.4255, kb_relative_information_score: 43.6779, mean_absolute_error: 0.2362, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7672, predictive_accuracy: 0.7778, prior_entropy: 0.8813, recall: 0.7778, relative_absolute_error: 0.5643, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4451, root_relative_squared_error: 0.9748, scimark_benchmark: 943.521,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7845, build_cpu_time: 3.7472, build_memory: 204879478.0741, f_measure: 0.7786, kappa: 0.4548, kb_relative_information_score: 48.8378, mean_absolute_error: 0.2121, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.778, predictive_accuracy: 0.787, prior_entropy: 0.8813, recall: 0.787, relative_absolute_error: 0.5069, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4593, root_relative_squared_error: 1.0059, scimark_benchmark: 945.0532,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7958, build_cpu_time: 1.0638, build_memory: 75192197.7037, f_measure: 0.7594, kappa: 0.4074, kb_relative_information_score: 43.4895, mean_absolute_error: 0.2308, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7577, predictive_accuracy: 0.7685, prior_entropy: 0.8813, recall: 0.7685, relative_absolute_error: 0.5515, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4684, root_relative_squared_error: 1.0257, scimark_benchmark: 939.521,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7547, build_cpu_time: 0.476, build_memory: 1507397529.5556, f_measure: 0.7275, kappa: 0.3381, kb_relative_information_score: 35.878, mean_absolute_error: 0.2598, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.7247, predictive_accuracy: 0.7315, prior_entropy: 0.8813, recall: 0.7315, relative_absolute_error: 0.6207, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.474, root_relative_squared_error: 1.0379, scimark_benchmark: 906.6607,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8388, build_cpu_time: 0.0537, build_memory: 427805702.8889, f_measure: 0.845, kappa: 0.617, kb_relative_information_score: 62.5845, mean_absolute_error: 0.1662, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8501, predictive_accuracy: 0.8519, prior_entropy: 0.8813, recall: 0.8519, relative_absolute_error: 0.3971, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3657, root_relative_squared_error: 0.8009, scimark_benchmark: 933.4498,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8586, build_cpu_time: 0.1348, build_memory: 207457896.0741, f_measure: 0.8279, kappa: 0.5774, kb_relative_information_score: 61.268, mean_absolute_error: 0.1674, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8286, predictive_accuracy: 0.8333, prior_entropy: 0.8813, recall: 0.8333, relative_absolute_error: 0.4, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3889, root_relative_squared_error: 0.8517, scimark_benchmark: 916.1588,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8583, build_cpu_time: 0.2142, build_memory: 1212974596.5926, f_measure: 0.8062, kappa: 0.5213, kb_relative_information_score: 58.6897, mean_absolute_error: 0.1759, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8086, predictive_accuracy: 0.8148, prior_entropy: 0.8813, recall: 0.8148, relative_absolute_error: 0.4202, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.4081, root_relative_squared_error: 0.8937, scimark_benchmark: 923.3659,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8135, build_cpu_time: 0.4261, build_memory: 1161357177.3333, f_measure: 0.8364, kappa: 0.597, kb_relative_information_score: 63.7353, mean_absolute_error: 0.1589, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.839, predictive_accuracy: 0.8426, prior_entropy: 0.8813, recall: 0.8426, relative_absolute_error: 0.3796, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3969, root_relative_squared_error: 0.8691, scimark_benchmark: 890.3066,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8047, build_cpu_time: 0.8433, build_memory: 387297109.5556, f_measure: 0.847, kappa: 0.6243, kb_relative_information_score: 66.5752, mean_absolute_error: 0.1481, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.8486, predictive_accuracy: 0.8519, prior_entropy: 0.8813, recall: 0.8519, relative_absolute_error: 0.3539, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.3845, root_relative_squared_error: 0.842, scimark_benchmark: 893.4088,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9211, build_cpu_time: 0.0879, build_memory: 541463287.1111, f_measure: 0.9055, kappa: 0.7696, kb_relative_information_score: 80.5004, mean_absolute_error: 0.0992, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.9067, predictive_accuracy: 0.9074, prior_entropy: 0.8813, recall: 0.9074, relative_absolute_error: 0.2371, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.2977, root_relative_squared_error: 0.6519, scimark_benchmark: 945.0554,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9369, build_cpu_time: 0.0795, build_memory: 593716299.1111, f_measure: 0.9055, kappa: 0.7696, kb_relative_information_score: 80.7011, mean_absolute_error: 0.0982, mean_prior_absolute_error: 0.4185, number_of_instances: 108, precision: 0.9067, predictive_accuracy: 0.9074, prior_entropy: 0.8813, recall: 0.9074, relative_absolute_error: 0.2347, root_mean_prior_squared_error: 0.4566, root_mean_squared_error: 0.2924, root_relative_squared_error: 0.6403, scimark_benchmark: 922.3661,

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