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OpenML
OpenML
Supervised Classification on fishcatch

Supervised Classification on fishcatch

Task 3719 Supervised Classification fishcatch 463 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • study_1 study_107 study_123 study_41 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9732, f_measure: 0.9432, kappa: 0.8821, kb_relative_information_score: 132.3028, mean_absolute_error: 0.08, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9441, predictive_accuracy: 0.943, prior_entropy: 0.971, recall: 0.943, relative_absolute_error: 0.1668, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2169, root_relative_squared_error: 0.443, scimark_benchmark: 942.9518, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9789, f_measure: 0.9748, kappa: 0.9478, kb_relative_information_score: 149.3975, mean_absolute_error: 0.0253, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9762, predictive_accuracy: 0.9747, prior_entropy: 0.971, recall: 0.9747, relative_absolute_error: 0.0528, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.1591, root_relative_squared_error: 0.325, scimark_benchmark: 930.5999, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4515, kb_relative_information_score: 24.2885, mean_absolute_error: 0.3987, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.3615, predictive_accuracy: 0.6013, prior_entropy: 0.971, recall: 0.6013, relative_absolute_error: 0.8311, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.6315, root_relative_squared_error: 1.2896, scimark_benchmark: 916.6405, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.95, f_measure: 0.9434, kappa: 0.8834, kb_relative_information_score: 138.7951, mean_absolute_error: 0.057, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9476, predictive_accuracy: 0.943, prior_entropy: 0.971, recall: 0.943, relative_absolute_error: 0.1187, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2387, root_relative_squared_error: 0.4874, scimark_benchmark: 1250.8301, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9988, f_measure: 0.9874, kappa: 0.9737, kb_relative_information_score: 139.3821, mean_absolute_error: 0.0645, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9877, predictive_accuracy: 0.9873, prior_entropy: 0.971, recall: 0.9873, relative_absolute_error: 0.1344, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.1398, root_relative_squared_error: 0.2856, scimark_benchmark: 1335.643, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7781, f_measure: 0.7947, kappa: 0.5684, kb_relative_information_score: 90.0237, mean_absolute_error: 0.2025, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.7963, predictive_accuracy: 0.7975, prior_entropy: 0.971, recall: 0.7975, relative_absolute_error: 0.4222, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.45, root_relative_squared_error: 0.9191, scimark_benchmark: 916.5955, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9968, f_measure: 0.9622, kappa: 0.9216, kb_relative_information_score: 135.6453, mean_absolute_error: 0.0752, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9636, predictive_accuracy: 0.962, prior_entropy: 0.971, recall: 0.962, relative_absolute_error: 0.1567, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.1624, root_relative_squared_error: 0.3316, scimark_benchmark: 1028.5889, usercpu_time_millis: 120, usercpu_time_millis_training: 120,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9519, f_measure: 0.918, kappa: 0.8298, kb_relative_information_score: 128.6833, mean_absolute_error: 0.089, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.919, predictive_accuracy: 0.9177, prior_entropy: 0.971, recall: 0.9177, relative_absolute_error: 0.1855, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2766, root_relative_squared_error: 0.5648, scimark_benchmark: 1350.9691, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.992, f_measure: 0.9496, kappa: 0.8955, kb_relative_information_score: 139.1779, mean_absolute_error: 0.0589, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9511, predictive_accuracy: 0.9494, prior_entropy: 0.971, recall: 0.9494, relative_absolute_error: 0.1227, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.1733, root_relative_squared_error: 0.3539, scimark_benchmark: 1327.8711, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9578, f_measure: 0.9559, kappa: 0.9083, kb_relative_information_score: 143.0361, mean_absolute_error: 0.0443, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9567, predictive_accuracy: 0.9557, prior_entropy: 0.971, recall: 0.9557, relative_absolute_error: 0.0923, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2105, root_relative_squared_error: 0.4299, scimark_benchmark: 1280.6952,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.948, f_measure: 0.9497, kappa: 0.8961, kb_relative_information_score: 131.141, mean_absolute_error: 0.0901, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9528, predictive_accuracy: 0.9494, prior_entropy: 0.971, recall: 0.9494, relative_absolute_error: 0.1878, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2156, root_relative_squared_error: 0.4403, scimark_benchmark: 1073.494,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9485, f_measure: 0.9434, kappa: 0.8828, kb_relative_information_score: 134.5741, mean_absolute_error: 0.0741, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9456, predictive_accuracy: 0.943, prior_entropy: 0.971, recall: 0.943, relative_absolute_error: 0.1546, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2327, root_relative_squared_error: 0.4753, scimark_benchmark: 1336.3256, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9525, f_measure: 0.9496, kappa: 0.8955, kb_relative_information_score: 140.9156, mean_absolute_error: 0.0506, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9511, predictive_accuracy: 0.9494, prior_entropy: 0.971, recall: 0.9494, relative_absolute_error: 0.1055, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.225, root_relative_squared_error: 0.4596, scimark_benchmark: 1291.6995,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8175, f_measure: 0.846, kappa: 0.6765, kb_relative_information_score: 109.1082, mean_absolute_error: 0.1456, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.8828, predictive_accuracy: 0.8544, prior_entropy: 0.971, recall: 0.8544, relative_absolute_error: 0.3034, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.3815, root_relative_squared_error: 0.7792, scimark_benchmark: 1363.454,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9672, f_measure: 0.9685, kappa: 0.9345, kb_relative_information_score: 142.4277, mean_absolute_error: 0.05, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9693, predictive_accuracy: 0.9684, prior_entropy: 0.971, recall: 0.9684, relative_absolute_error: 0.1041, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.1864, root_relative_squared_error: 0.3807, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9579, f_measure: 0.9498, kappa: 0.8966, kb_relative_information_score: 140.9156, mean_absolute_error: 0.0506, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9551, predictive_accuracy: 0.9494, prior_entropy: 0.971, recall: 0.9494, relative_absolute_error: 0.1055, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.225, root_relative_squared_error: 0.4596, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8944, f_measure: 0.8987, kappa: 0.7888, kb_relative_information_score: 123.9516, mean_absolute_error: 0.1013, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.8987, predictive_accuracy: 0.8987, prior_entropy: 0.971, recall: 0.8987, relative_absolute_error: 0.2111, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.3182, root_relative_squared_error: 0.6499, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4704, f_measure: 0.4515, kb_relative_information_score: -0.144, mean_absolute_error: 0.4799, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.3615, predictive_accuracy: 0.6013, prior_entropy: 0.971, recall: 0.6013, relative_absolute_error: 1.0004, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.4898, root_relative_squared_error: 1.0004, scimark_benchmark: 1505.597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.951, f_measure: 0.9434, kappa: 0.8834, kb_relative_information_score: 135.1589, mean_absolute_error: 0.0717, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9476, predictive_accuracy: 0.943, prior_entropy: 0.971, recall: 0.943, relative_absolute_error: 0.1495, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2329, root_relative_squared_error: 0.4756, scimark_benchmark: 1605.6303,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9975, f_measure: 0.956, kappa: 0.9093, kb_relative_information_score: 143.041, mean_absolute_error: 0.0441, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9601, predictive_accuracy: 0.9557, prior_entropy: 0.971, recall: 0.9557, relative_absolute_error: 0.0919, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.1963, root_relative_squared_error: 0.401, scimark_benchmark: 931.2336, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9988, f_measure: 0.9747, kappa: 0.9472, kb_relative_information_score: 149.9744, mean_absolute_error: 0.0239, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9747, predictive_accuracy: 0.9747, prior_entropy: 0.971, recall: 0.9747, relative_absolute_error: 0.0497, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.142, root_relative_squared_error: 0.2899, scimark_benchmark: 941.7954, usercpu_time_millis: 60, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9982, f_measure: 0.981, kappa: 0.9605, kb_relative_information_score: 150.6648, mean_absolute_error: 0.0223, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9811, predictive_accuracy: 0.981, prior_entropy: 0.971, recall: 0.981, relative_absolute_error: 0.0464, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.1296, root_relative_squared_error: 0.2647, scimark_benchmark: 923.7642, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9978, f_measure: 0.9747, kappa: 0.9475, kb_relative_information_score: 148.6548, mean_absolute_error: 0.0281, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9751, predictive_accuracy: 0.9747, prior_entropy: 0.971, recall: 0.9747, relative_absolute_error: 0.0585, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.1478, root_relative_squared_error: 0.3018, scimark_benchmark: 894.7455, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9696, f_measure: 0.9496, kappa: 0.8955, kb_relative_information_score: 140.9224, mean_absolute_error: 0.0506, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9511, predictive_accuracy: 0.9494, prior_entropy: 0.971, recall: 0.9494, relative_absolute_error: 0.1055, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2249, root_relative_squared_error: 0.4593, scimark_benchmark: 936.6206, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.981, f_measure: 0.9496, kappa: 0.8955, kb_relative_information_score: 140.9219, mean_absolute_error: 0.0506, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9511, predictive_accuracy: 0.9494, prior_entropy: 0.971, recall: 0.9494, relative_absolute_error: 0.1055, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2249, root_relative_squared_error: 0.4592, scimark_benchmark: 936.6206, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9806, f_measure: 0.9559, kappa: 0.9088, kb_relative_information_score: 142.904, mean_absolute_error: 0.0448, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9581, predictive_accuracy: 0.9557, prior_entropy: 0.971, recall: 0.9557, relative_absolute_error: 0.0934, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2084, root_relative_squared_error: 0.4256, scimark_benchmark: 911.3823, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9851, f_measure: 0.956, kappa: 0.9093, kb_relative_information_score: 142.1986, mean_absolute_error: 0.0475, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9601, predictive_accuracy: 0.9557, prior_entropy: 0.971, recall: 0.9557, relative_absolute_error: 0.0991, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2042, root_relative_squared_error: 0.417, scimark_benchmark: 934.5243, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9886, f_measure: 0.9498, kappa: 0.8966, kb_relative_information_score: 140.6578, mean_absolute_error: 0.0516, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9551, predictive_accuracy: 0.9494, prior_entropy: 0.971, recall: 0.9494, relative_absolute_error: 0.1076, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2239, root_relative_squared_error: 0.4573, scimark_benchmark: 938.4285,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9663, f_measure: 0.9496, kappa: 0.8955, kb_relative_information_score: 140.778, mean_absolute_error: 0.0512, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9511, predictive_accuracy: 0.9494, prior_entropy: 0.971, recall: 0.9494, relative_absolute_error: 0.1067, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2242, root_relative_squared_error: 0.4578, scimark_benchmark: 936.6206, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9881, f_measure: 0.9559, kappa: 0.9083, kb_relative_information_score: 143.4561, mean_absolute_error: 0.0434, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9567, predictive_accuracy: 0.9557, prior_entropy: 0.971, recall: 0.9557, relative_absolute_error: 0.0904, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2001, root_relative_squared_error: 0.4087, scimark_benchmark: 924.6116, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9898, f_measure: 0.9621, kappa: 0.9212, kb_relative_information_score: 143.5473, mean_absolute_error: 0.0436, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9625, predictive_accuracy: 0.962, prior_entropy: 0.971, recall: 0.962, relative_absolute_error: 0.0909, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.1939, root_relative_squared_error: 0.3959, scimark_benchmark: 945.6434, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9914, f_measure: 0.9685, kappa: 0.9345, kb_relative_information_score: 142.8214, mean_absolute_error: 0.0472, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9693, predictive_accuracy: 0.9684, prior_entropy: 0.971, recall: 0.9684, relative_absolute_error: 0.0983, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.1746, root_relative_squared_error: 0.3566, scimark_benchmark: 947.9494,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9936, f_measure: 0.9748, kappa: 0.9478, kb_relative_information_score: 141.2659, mean_absolute_error: 0.0547, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9762, predictive_accuracy: 0.9747, prior_entropy: 0.971, recall: 0.9747, relative_absolute_error: 0.1141, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.1655, root_relative_squared_error: 0.338, scimark_benchmark: 929.566,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9575, build_cpu_time: 6.4381, build_memory: 858341786.6329, f_measure: 0.9434, kappa: 0.8828, kb_relative_information_score: 139.5538, mean_absolute_error: 0.0544, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9456, predictive_accuracy: 0.943, prior_entropy: 0.971, recall: 0.943, relative_absolute_error: 0.1135, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.23, root_relative_squared_error: 0.4698, scimark_benchmark: 909.5718,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9654, build_cpu_time: 11.2579, build_memory: 1747570297.5696, f_measure: 0.9683, kappa: 0.9338, kb_relative_information_score: 147.277, mean_absolute_error: 0.0316, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9683, predictive_accuracy: 0.9684, prior_entropy: 0.971, recall: 0.9684, relative_absolute_error: 0.066, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.1779, root_relative_squared_error: 0.3633, scimark_benchmark: 947.7459,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9729, build_cpu_time: 1.2119, build_memory: 139786087.3418, f_measure: 0.962, kappa: 0.9208, kb_relative_information_score: 145.1584, mean_absolute_error: 0.038, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.962, predictive_accuracy: 0.962, prior_entropy: 0.971, recall: 0.962, relative_absolute_error: 0.0791, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.1948, root_relative_squared_error: 0.3979, scimark_benchmark: 942.5053,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9809, build_cpu_time: 0.103, build_memory: 376083142.0759, f_measure: 0.9559, kappa: 0.9083, kb_relative_information_score: 142.7083, mean_absolute_error: 0.0454, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9567, predictive_accuracy: 0.9557, prior_entropy: 0.971, recall: 0.9557, relative_absolute_error: 0.0945, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2074, root_relative_squared_error: 0.4235, scimark_benchmark: 933.4498,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9626, build_cpu_time: 0.2356, build_memory: 231241907.7468, f_measure: 0.9559, kappa: 0.9083, kb_relative_information_score: 143.2591, mean_absolute_error: 0.0434, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9567, predictive_accuracy: 0.9557, prior_entropy: 0.971, recall: 0.9557, relative_absolute_error: 0.0905, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2063, root_relative_squared_error: 0.4214, scimark_benchmark: 942.5053,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9629, build_cpu_time: 0.502, build_memory: 238999595.1899, f_measure: 0.9621, kappa: 0.9212, kb_relative_information_score: 145.1565, mean_absolute_error: 0.038, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9625, predictive_accuracy: 0.962, prior_entropy: 0.971, recall: 0.962, relative_absolute_error: 0.0792, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.1949, root_relative_squared_error: 0.398, scimark_benchmark: 902.712,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9578, build_cpu_time: 2.0876, build_memory: 1652045388.2532, f_measure: 0.9559, kappa: 0.9083, kb_relative_information_score: 143.0361, mean_absolute_error: 0.0443, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9567, predictive_accuracy: 0.9557, prior_entropy: 0.971, recall: 0.9557, relative_absolute_error: 0.0923, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2105, root_relative_squared_error: 0.4299, scimark_benchmark: 914.1182,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9862, build_cpu_time: 0.0173, build_memory: 1338027682.8861, f_measure: 0.9559, kappa: 0.9083, kb_relative_information_score: 143.0924, mean_absolute_error: 0.0441, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9567, predictive_accuracy: 0.9557, prior_entropy: 0.971, recall: 0.9557, relative_absolute_error: 0.0919, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2091, root_relative_squared_error: 0.427, scimark_benchmark: 933.4498,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9862, build_cpu_time: 0.0186, build_memory: 837452438.1772, f_measure: 0.9559, kappa: 0.9083, kb_relative_information_score: 143.0924, mean_absolute_error: 0.0441, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9567, predictive_accuracy: 0.9557, prior_entropy: 0.971, recall: 0.9557, relative_absolute_error: 0.0919, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2091, root_relative_squared_error: 0.427, scimark_benchmark: 930.5854,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9862, build_cpu_time: 0.0173, build_memory: 216211459.3924, f_measure: 0.9559, kappa: 0.9083, kb_relative_information_score: 143.0924, mean_absolute_error: 0.0441, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9567, predictive_accuracy: 0.9557, prior_entropy: 0.971, recall: 0.9557, relative_absolute_error: 0.0919, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2091, root_relative_squared_error: 0.427, scimark_benchmark: 919.5971,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9862, build_cpu_time: 0.023, build_memory: 355075139.6456, f_measure: 0.9559, kappa: 0.9083, kb_relative_information_score: 143.0924, mean_absolute_error: 0.0441, mean_prior_absolute_error: 0.4797, number_of_instances: 158, precision: 0.9567, predictive_accuracy: 0.9557, prior_entropy: 0.971, recall: 0.9557, relative_absolute_error: 0.0919, root_mean_prior_squared_error: 0.4896, root_mean_squared_error: 0.2091, root_relative_squared_error: 0.427, scimark_benchmark: 919.5971,

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