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OpenML
Task
Supervised Classification on pyrim

Supervised Classification on pyrim

Task 3665 Supervised Classification pyrim 514 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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Metric:

514 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9055, f_measure: 0.8214, kappa: 0.6309, kb_relative_information_score: 44.2489, mean_absolute_error: 0.1967, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.8266, predictive_accuracy: 0.8243, prior_entropy: 0.9819, recall: 0.8243, relative_absolute_error: 0.4038, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.3481, root_relative_squared_error: 0.7055, scimark_benchmark: 942.9518,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9284, f_measure: 0.9323, kappa: 0.8606, kb_relative_information_score: 63.5567, mean_absolute_error: 0.0676, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9325, predictive_accuracy: 0.9324, prior_entropy: 0.9819, recall: 0.9324, relative_absolute_error: 0.1387, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.2599, root_relative_squared_error: 0.5268, scimark_benchmark: 1325.2092, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.4271, kb_relative_information_score: 9.636, mean_absolute_error: 0.4189, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.3377, predictive_accuracy: 0.5811, prior_entropy: 0.9819, recall: 0.5811, relative_absolute_error: 0.8599, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.6472, root_relative_squared_error: 1.3118, scimark_benchmark: 887.6719, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8961, f_measure: 0.9046, kappa: 0.803, kb_relative_information_score: 59.409, mean_absolute_error: 0.0946, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9069, predictive_accuracy: 0.9054, prior_entropy: 0.9819, recall: 0.9054, relative_absolute_error: 0.1942, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.3076, root_relative_squared_error: 0.6234, scimark_benchmark: 1386.5717, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.952, f_measure: 0.9323, kappa: 0.8606, kb_relative_information_score: 53.6708, mean_absolute_error: 0.147, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9325, predictive_accuracy: 0.9324, prior_entropy: 0.9819, recall: 0.9324, relative_absolute_error: 0.3017, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.2604, root_relative_squared_error: 0.5277, scimark_benchmark: 1335.643, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9122, f_measure: 0.9185, kappa: 0.8319, kb_relative_information_score: 61.4829, mean_absolute_error: 0.0811, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9195, predictive_accuracy: 0.9189, prior_entropy: 0.9819, recall: 0.9189, relative_absolute_error: 0.1664, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.2847, root_relative_squared_error: 0.5771, scimark_benchmark: 916.5955,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9497, f_measure: 0.9457, kappa: 0.888, kb_relative_information_score: 52.4805, mean_absolute_error: 0.1584, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9468, predictive_accuracy: 0.9459, prior_entropy: 0.9819, recall: 0.9459, relative_absolute_error: 0.3252, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.2602, root_relative_squared_error: 0.5274, scimark_benchmark: 938.343, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8485, f_measure: 0.8378, kappa: 0.6669, kb_relative_information_score: 44.4026, mean_absolute_error: 0.2023, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.8378, predictive_accuracy: 0.8378, prior_entropy: 0.9819, recall: 0.8378, relative_absolute_error: 0.4152, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.3858, root_relative_squared_error: 0.7819, scimark_benchmark: 1350.9691, usercpu_time_millis: 180, usercpu_time_millis_training: 180,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9284, f_measure: 0.9052, kappa: 0.8048, kb_relative_information_score: 49.7223, mean_absolute_error: 0.1665, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9053, predictive_accuracy: 0.9054, prior_entropy: 0.9819, recall: 0.9054, relative_absolute_error: 0.3417, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.2999, root_relative_squared_error: 0.6079, scimark_benchmark: 1315.0767, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8935, f_measure: 0.8923, kappa: 0.7799, kb_relative_information_score: 57.3351, mean_absolute_error: 0.1081, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.894, predictive_accuracy: 0.8919, prior_entropy: 0.9819, recall: 0.8919, relative_absolute_error: 0.2219, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.3288, root_relative_squared_error: 0.6664, scimark_benchmark: 1333.5799,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7869, f_measure: 0.8228, kappa: 0.6342, kb_relative_information_score: 36.2503, mean_absolute_error: 0.263, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.8241, predictive_accuracy: 0.8243, prior_entropy: 0.9819, recall: 0.8243, relative_absolute_error: 0.5398, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.4057, root_relative_squared_error: 0.8222, scimark_benchmark: 1315.3881,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.835, f_measure: 0.7811, kappa: 0.5477, kb_relative_information_score: 34.9175, mean_absolute_error: 0.2659, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.7833, predictive_accuracy: 0.7838, prior_entropy: 0.9819, recall: 0.7838, relative_absolute_error: 0.5459, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.4152, root_relative_squared_error: 0.8415, scimark_benchmark: 1330.2678,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.898, f_measure: 0.8925, kappa: 0.7819, kb_relative_information_score: 57.3351, mean_absolute_error: 0.1081, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.8984, predictive_accuracy: 0.8919, prior_entropy: 0.9819, recall: 0.8919, relative_absolute_error: 0.2219, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.3288, root_relative_squared_error: 0.6664, scimark_benchmark: 1291.6995,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7787, f_measure: 0.7997, kappa: 0.5892, kb_relative_information_score: 44.8919, mean_absolute_error: 0.1892, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.8406, predictive_accuracy: 0.8108, prior_entropy: 0.9819, recall: 0.8108, relative_absolute_error: 0.3883, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.435, root_relative_squared_error: 0.8816, scimark_benchmark: 1280.6952,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8976, f_measure: 0.9046, kappa: 0.803, kb_relative_information_score: 55.8943, mean_absolute_error: 0.1255, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9069, predictive_accuracy: 0.9054, prior_entropy: 0.9819, recall: 0.9054, relative_absolute_error: 0.2576, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.2992, root_relative_squared_error: 0.6063, scimark_benchmark: 1358.4523,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6714, f_measure: 0.6769, kappa: 0.3398, kb_relative_information_score: 24.1531, mean_absolute_error: 0.3243, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.6791, predictive_accuracy: 0.6757, prior_entropy: 0.9819, recall: 0.6757, relative_absolute_error: 0.6657, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.5695, root_relative_squared_error: 1.1543, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.829, f_measure: 0.837, kappa: 0.6639, kb_relative_information_score: 49.0396, mean_absolute_error: 0.1622, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.8374, predictive_accuracy: 0.8378, prior_entropy: 0.9819, recall: 0.8378, relative_absolute_error: 0.3328, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.4027, root_relative_squared_error: 0.8162, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4617, f_measure: 0.4271, kb_relative_information_score: -0.1011, mean_absolute_error: 0.4876, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.3377, predictive_accuracy: 0.5811, prior_entropy: 0.9819, recall: 0.5811, relative_absolute_error: 1.0008, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.4937, root_relative_squared_error: 1.0007, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8368, f_measure: 0.8378, kappa: 0.6669, kb_relative_information_score: 44.5335, mean_absolute_error: 0.2007, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.8378, predictive_accuracy: 0.8378, prior_entropy: 0.9819, recall: 0.8378, relative_absolute_error: 0.412, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.3895, root_relative_squared_error: 0.7894, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8728, f_measure: 0.8641, kappa: 0.7199, kb_relative_information_score: 52.5831, mean_absolute_error: 0.1395, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.8647, predictive_accuracy: 0.8649, prior_entropy: 0.9819, recall: 0.8649, relative_absolute_error: 0.2862, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.3637, root_relative_squared_error: 0.7371, scimark_benchmark: 931.2336, usercpu_time_millis: 50, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8901, f_measure: 0.851, kappa: 0.6933, kb_relative_information_score: 52.2629, mean_absolute_error: 0.1403, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.8509, predictive_accuracy: 0.8514, prior_entropy: 0.9819, recall: 0.8514, relative_absolute_error: 0.2879, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.3642, root_relative_squared_error: 0.7382, scimark_benchmark: 945.6434, usercpu_time_millis: 60, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8848, f_measure: 0.8906, kappa: 0.7739, kb_relative_information_score: 56.6798, mean_absolute_error: 0.113, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.8948, predictive_accuracy: 0.8919, prior_entropy: 0.9819, recall: 0.8919, relative_absolute_error: 0.2319, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.3314, root_relative_squared_error: 0.6717, scimark_benchmark: 941.7954, usercpu_time_millis: 140, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 100,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8927, f_measure: 0.8913, kappa: 0.7759, kb_relative_information_score: 57.1126, mean_absolute_error: 0.11, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.8921, predictive_accuracy: 0.8919, prior_entropy: 0.9819, recall: 0.8919, relative_absolute_error: 0.2258, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.3291, root_relative_squared_error: 0.667, scimark_benchmark: 923.7642, usercpu_time_millis: 280, usercpu_time_millis_testing: 90, usercpu_time_millis_training: 190,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9122, f_measure: 0.8649, kappa: 0.7224, kb_relative_information_score: 53.5944, mean_absolute_error: 0.1322, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.8649, predictive_accuracy: 0.8649, prior_entropy: 0.9819, recall: 0.8649, relative_absolute_error: 0.2713, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.3578, root_relative_squared_error: 0.7252, scimark_benchmark: 894.7455, usercpu_time_millis: 610, usercpu_time_millis_testing: 220, usercpu_time_millis_training: 390,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9239, f_measure: 0.9323, kappa: 0.8606, kb_relative_information_score: 63.374, mean_absolute_error: 0.069, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9325, predictive_accuracy: 0.9324, prior_entropy: 0.9819, recall: 0.9324, relative_absolute_error: 0.1416, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.2558, root_relative_squared_error: 0.5185, scimark_benchmark: 936.7115, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9302, f_measure: 0.9189, kappa: 0.8335, kb_relative_information_score: 61.9804, mean_absolute_error: 0.0785, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9189, predictive_accuracy: 0.9189, prior_entropy: 0.9819, recall: 0.9189, relative_absolute_error: 0.161, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.2564, root_relative_squared_error: 0.5197, scimark_benchmark: 938.2848, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9385, f_measure: 0.8913, kappa: 0.7759, kb_relative_information_score: 55.4248, mean_absolute_error: 0.1236, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.8921, predictive_accuracy: 0.8919, prior_entropy: 0.9819, recall: 0.8919, relative_absolute_error: 0.2537, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.3225, root_relative_squared_error: 0.6537, scimark_benchmark: 911.3823, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9055, f_measure: 0.8773, kappa: 0.7468, kb_relative_information_score: 54.5502, mean_absolute_error: 0.1289, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.8793, predictive_accuracy: 0.8784, prior_entropy: 0.9819, recall: 0.8784, relative_absolute_error: 0.2646, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.3322, root_relative_squared_error: 0.6733, scimark_benchmark: 933.8635, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8743, f_measure: 0.8632, kappa: 0.7173, kb_relative_information_score: 48.2889, mean_absolute_error: 0.1736, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.8669, predictive_accuracy: 0.8649, prior_entropy: 0.9819, recall: 0.8649, relative_absolute_error: 0.3564, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.3658, root_relative_squared_error: 0.7413, scimark_benchmark: 938.4285,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9197, f_measure: 0.9185, kappa: 0.8319, kb_relative_information_score: 61.7751, mean_absolute_error: 0.0786, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9195, predictive_accuracy: 0.9189, prior_entropy: 0.9819, recall: 0.9189, relative_absolute_error: 0.1614, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.2768, root_relative_squared_error: 0.5611, scimark_benchmark: 936.6206, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9441, f_measure: 0.9185, kappa: 0.8319, kb_relative_information_score: 61.6674, mean_absolute_error: 0.0796, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9195, predictive_accuracy: 0.9189, prior_entropy: 0.9819, recall: 0.9189, relative_absolute_error: 0.1633, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.2773, root_relative_squared_error: 0.562, scimark_benchmark: 924.6116, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.949, f_measure: 0.9185, kappa: 0.8319, kb_relative_information_score: 61.121, mean_absolute_error: 0.0849, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9195, predictive_accuracy: 0.9189, prior_entropy: 0.9819, recall: 0.9189, relative_absolute_error: 0.1743, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.2662, root_relative_squared_error: 0.5396, scimark_benchmark: 924.6116, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.946, f_measure: 0.9185, kappa: 0.8319, kb_relative_information_score: 57.7039, mean_absolute_error: 0.113, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9195, predictive_accuracy: 0.9189, prior_entropy: 0.9819, recall: 0.9189, relative_absolute_error: 0.2318, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.2643, root_relative_squared_error: 0.5356, scimark_benchmark: 947.9494, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9441, f_measure: 0.8913, kappa: 0.7759, kb_relative_information_score: 50.4922, mean_absolute_error: 0.1658, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.8921, predictive_accuracy: 0.8919, prior_entropy: 0.9819, recall: 0.8919, relative_absolute_error: 0.3404, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.287, root_relative_squared_error: 0.5817, scimark_benchmark: 929.566,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9452, build_cpu_time: 0.9819, build_memory: 205549562.8108, f_measure: 0.9189, kappa: 0.8335, kb_relative_information_score: 60.8777, mean_absolute_error: 0.0848, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9189, predictive_accuracy: 0.9189, prior_entropy: 0.9819, recall: 0.9189, relative_absolute_error: 0.174, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.2819, root_relative_squared_error: 0.5713, scimark_benchmark: 937.9603,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9381, build_cpu_time: 0.4919, build_memory: 260523729.5135, f_measure: 0.9457, kappa: 0.888, kb_relative_information_score: 65.1111, mean_absolute_error: 0.0589, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9468, predictive_accuracy: 0.9459, prior_entropy: 0.9819, recall: 0.9459, relative_absolute_error: 0.1209, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.2183, root_relative_squared_error: 0.4424, scimark_benchmark: 913.3372,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.91, build_cpu_time: 1.8941, build_memory: 869997666.1622, f_measure: 0.9052, kappa: 0.8048, kb_relative_information_score: 59.8053, mean_absolute_error: 0.0914, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9053, predictive_accuracy: 0.9054, prior_entropy: 0.9819, recall: 0.9054, relative_absolute_error: 0.1876, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.2982, root_relative_squared_error: 0.6045, scimark_benchmark: 937.6343,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9089, build_cpu_time: 0.0696, build_memory: 361739193.5135, f_measure: 0.9046, kappa: 0.803, kb_relative_information_score: 57.6261, mean_absolute_error: 0.1074, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9069, predictive_accuracy: 0.9054, prior_entropy: 0.9819, recall: 0.9054, relative_absolute_error: 0.2204, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.2971, root_relative_squared_error: 0.6021, scimark_benchmark: 920.7965,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9089, build_cpu_time: 0.0515, build_memory: 681975418.7027, f_measure: 0.9046, kappa: 0.803, kb_relative_information_score: 57.6261, mean_absolute_error: 0.1074, mean_prior_absolute_error: 0.4872, number_of_instances: 74, precision: 0.9069, predictive_accuracy: 0.9054, prior_entropy: 0.9819, recall: 0.9054, relative_absolute_error: 0.2204, root_mean_prior_squared_error: 0.4934, root_mean_squared_error: 0.2971, root_relative_squared_error: 0.6021, scimark_benchmark: 939.6298,

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

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