Task
Supervised Classification on dermatology

Supervised Classification on dermatology

Task 4578 Supervised Classification dermatology 227 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9951, f_measure: 0.9858, kappa: 0.9667, kb_relative_information_score: 3483.8147, mean_absolute_error: 0.0205, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.986, predictive_accuracy: 0.9858, prior_entropy: 0.8898, recall: 0.9858, relative_absolute_error: 0.0482, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.1189, root_relative_squared_error: 0.258, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 0.9986, kappa: 0.9968, kb_relative_information_score: 3588.9213, mean_absolute_error: 0.0097, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9986, predictive_accuracy: 0.9986, prior_entropy: 0.8898, recall: 0.9986, relative_absolute_error: 0.0229, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0417, root_relative_squared_error: 0.0905, scimark_benchmark: 972.587, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9999, f_measure: 0.9962, kappa: 0.991, kb_relative_information_score: 3593.575, mean_absolute_error: 0.0076, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9962, predictive_accuracy: 0.9962, prior_entropy: 0.8898, recall: 0.9962, relative_absolute_error: 0.0178, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0537, root_relative_squared_error: 0.1165, scimark_benchmark: 934.3687, usercpu_time_millis: 330, usercpu_time_millis_training: 330,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9567, f_measure: 0.9731, kappa: 0.9361, kb_relative_information_score: 3411.5139, mean_absolute_error: 0.0265, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9745, predictive_accuracy: 0.9735, prior_entropy: 0.8898, recall: 0.9735, relative_absolute_error: 0.0623, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.1628, root_relative_squared_error: 0.3533, scimark_benchmark: 916.0735, usercpu_time_millis: 120, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 0.9973, kappa: 0.9936, kb_relative_information_score: 3631.045, mean_absolute_error: 0.0026, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9973, predictive_accuracy: 0.9973, prior_entropy: 0.8898, recall: 0.9973, relative_absolute_error: 0.006, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0438, root_relative_squared_error: 0.0949, scimark_benchmark: 941.6675, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9988, f_measure: 0.9825, kappa: 0.9588, kb_relative_information_score: 3416.978, mean_absolute_error: 0.0292, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9825, predictive_accuracy: 0.9825, prior_entropy: 0.8898, recall: 0.9825, relative_absolute_error: 0.0686, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.1067, root_relative_squared_error: 0.2316, scimark_benchmark: 941.6675, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9997, f_measure: 0.9893, kappa: 0.9748, kb_relative_information_score: 3360.5321, mean_absolute_error: 0.0416, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9894, predictive_accuracy: 0.9893, prior_entropy: 0.8898, recall: 0.9893, relative_absolute_error: 0.0978, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.1019, root_relative_squared_error: 0.2211, scimark_benchmark: 936.8075, usercpu_time_millis: 670, usercpu_time_millis_testing: 130, usercpu_time_millis_training: 540,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9996, f_measure: 0.9935, kappa: 0.9846, kb_relative_information_score: 3589.5402, mean_absolute_error: 0.0073, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9935, predictive_accuracy: 0.9934, prior_entropy: 0.8898, recall: 0.9934, relative_absolute_error: 0.0173, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.074, root_relative_squared_error: 0.1606, scimark_benchmark: 931.771, usercpu_time_millis: 320, usercpu_time_millis_training: 320,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 0.9984, kappa: 0.9961, kb_relative_information_score: 3385.2396, mean_absolute_error: 0.0396, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9984, predictive_accuracy: 0.9984, prior_entropy: 0.8898, recall: 0.9984, relative_absolute_error: 0.0932, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0862, root_relative_squared_error: 0.187, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9567, f_measure: 0.9731, kappa: 0.9361, kb_relative_information_score: 3411.5139, mean_absolute_error: 0.0265, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9745, predictive_accuracy: 0.9735, prior_entropy: 0.8898, recall: 0.9735, relative_absolute_error: 0.0623, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.1628, root_relative_squared_error: 0.3533, scimark_benchmark: 939.8002,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9567, f_measure: 0.9731, kappa: 0.9361, kb_relative_information_score: 3411.5139, mean_absolute_error: 0.0265, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9745, predictive_accuracy: 0.9735, prior_entropy: 0.8898, recall: 0.9735, relative_absolute_error: 0.0623, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.1628, root_relative_squared_error: 0.3533, scimark_benchmark: 932.438, usercpu_time_millis: 120, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 0.9973, kappa: 0.9936, kb_relative_information_score: 3631.045, mean_absolute_error: 0.0026, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9973, predictive_accuracy: 0.9973, prior_entropy: 0.8898, recall: 0.9973, relative_absolute_error: 0.006, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0438, root_relative_squared_error: 0.0949, scimark_benchmark: 941.3847, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 0.9973, kappa: 0.9936, kb_relative_information_score: 3631.045, mean_absolute_error: 0.0026, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9973, predictive_accuracy: 0.9973, prior_entropy: 0.8898, recall: 0.9973, relative_absolute_error: 0.006, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0438, root_relative_squared_error: 0.0949, scimark_benchmark: 974.2014,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 0.9984, kappa: 0.9961, kb_relative_information_score: 3385.2396, mean_absolute_error: 0.0396, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9984, predictive_accuracy: 0.9984, prior_entropy: 0.8898, recall: 0.9984, relative_absolute_error: 0.0932, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0862, root_relative_squared_error: 0.187, scimark_benchmark: 943.1009, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9951, f_measure: 0.9858, kappa: 0.9667, kb_relative_information_score: 3483.8147, mean_absolute_error: 0.0205, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.986, predictive_accuracy: 0.9858, prior_entropy: 0.8898, recall: 0.9858, relative_absolute_error: 0.0482, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.1189, root_relative_squared_error: 0.258, scimark_benchmark: 942.2392,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 0.9986, kappa: 0.9968, kb_relative_information_score: 3588.9213, mean_absolute_error: 0.0097, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9986, predictive_accuracy: 0.9986, prior_entropy: 0.8898, recall: 0.9986, relative_absolute_error: 0.0229, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0417, root_relative_squared_error: 0.0905, scimark_benchmark: 908.9569, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9999, f_measure: 0.9962, kappa: 0.991, kb_relative_information_score: 3593.575, mean_absolute_error: 0.0076, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9962, predictive_accuracy: 0.9962, prior_entropy: 0.8898, recall: 0.9962, relative_absolute_error: 0.0178, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0537, root_relative_squared_error: 0.1165, scimark_benchmark: 936.2574, usercpu_time_millis: 280, usercpu_time_millis_training: 280,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9567, f_measure: 0.9731, kappa: 0.9361, kb_relative_information_score: 3411.5139, mean_absolute_error: 0.0265, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9745, predictive_accuracy: 0.9735, prior_entropy: 0.8898, recall: 0.9735, relative_absolute_error: 0.0623, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.1628, root_relative_squared_error: 0.3533, scimark_benchmark: 937.5683, usercpu_time_millis: 100, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9567, f_measure: 0.9731, kappa: 0.9361, kb_relative_information_score: 3411.5139, mean_absolute_error: 0.0265, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9745, predictive_accuracy: 0.9735, prior_entropy: 0.8898, recall: 0.9735, relative_absolute_error: 0.0623, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.1628, root_relative_squared_error: 0.3533, scimark_benchmark: 926.5462, usercpu_time_millis: 100, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 0.9973, kappa: 0.9936, kb_relative_information_score: 3633.5469, mean_absolute_error: 0.0022, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9973, predictive_accuracy: 0.9973, prior_entropy: 0.8898, recall: 0.9973, relative_absolute_error: 0.0053, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0392, root_relative_squared_error: 0.0851, scimark_benchmark: 938.1282, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 0.9973, kappa: 0.9936, kb_relative_information_score: 3631.045, mean_absolute_error: 0.0026, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9973, predictive_accuracy: 0.9973, prior_entropy: 0.8898, recall: 0.9973, relative_absolute_error: 0.006, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0438, root_relative_squared_error: 0.0949, scimark_benchmark: 930.404, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 0.9973, kappa: 0.9936, kb_relative_information_score: 3631.045, mean_absolute_error: 0.0026, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9973, predictive_accuracy: 0.9973, prior_entropy: 0.8898, recall: 0.9973, relative_absolute_error: 0.006, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0438, root_relative_squared_error: 0.0949, scimark_benchmark: 930.404, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9988, f_measure: 0.9825, kappa: 0.9588, kb_relative_information_score: 3416.978, mean_absolute_error: 0.0292, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9825, predictive_accuracy: 0.9825, prior_entropy: 0.8898, recall: 0.9825, relative_absolute_error: 0.0686, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.1067, root_relative_squared_error: 0.2316, scimark_benchmark: 933.3455, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9997, f_measure: 0.9893, kappa: 0.9748, kb_relative_information_score: 3360.5321, mean_absolute_error: 0.0416, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9894, predictive_accuracy: 0.9893, prior_entropy: 0.8898, recall: 0.9893, relative_absolute_error: 0.0978, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.1019, root_relative_squared_error: 0.2211, scimark_benchmark: 763.3895, usercpu_time_millis: 640, usercpu_time_millis_testing: 70, usercpu_time_millis_training: 570,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 0.9973, kappa: 0.9936, kb_relative_information_score: 3631.045, mean_absolute_error: 0.0026, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9973, predictive_accuracy: 0.9973, prior_entropy: 0.8898, recall: 0.9973, relative_absolute_error: 0.006, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0438, root_relative_squared_error: 0.0949, scimark_benchmark: 944.0133, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9996, f_measure: 0.9935, kappa: 0.9846, kb_relative_information_score: 3589.5402, mean_absolute_error: 0.0073, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9935, predictive_accuracy: 0.9934, prior_entropy: 0.8898, recall: 0.9934, relative_absolute_error: 0.0173, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.074, root_relative_squared_error: 0.1606, scimark_benchmark: 941.3057, usercpu_time_millis: 340, usercpu_time_millis_training: 340,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 0.9984, kappa: 0.9961, kb_relative_information_score: 3385.2396, mean_absolute_error: 0.0396, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9984, predictive_accuracy: 0.9984, prior_entropy: 0.8898, recall: 0.9984, relative_absolute_error: 0.0932, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0862, root_relative_squared_error: 0.187, scimark_benchmark: 938.988, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9999, f_measure: 0.994, kappa: 0.9859, kb_relative_information_score: 3528.7845, mean_absolute_error: 0.0168, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.994, predictive_accuracy: 0.994, prior_entropy: 0.8898, recall: 0.994, relative_absolute_error: 0.0394, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0694, root_relative_squared_error: 0.1506, scimark_benchmark: 936.2574, usercpu_time_millis: 9130, usercpu_time_millis_testing: 4160, usercpu_time_millis_training: 4970,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9999, f_measure: 0.994, kappa: 0.9859, kb_relative_information_score: 3526.1212, mean_absolute_error: 0.017, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.994, predictive_accuracy: 0.994, prior_entropy: 0.8898, recall: 0.994, relative_absolute_error: 0.0401, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0707, root_relative_squared_error: 0.1534, scimark_benchmark: 938.4601, usercpu_time_millis: 5530, usercpu_time_millis_testing: 2730, usercpu_time_millis_training: 2800,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9999, f_measure: 0.9937, kappa: 0.9852, kb_relative_information_score: 3528.073, mean_absolute_error: 0.0168, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9938, predictive_accuracy: 0.9937, prior_entropy: 0.8898, recall: 0.9937, relative_absolute_error: 0.0395, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0697, root_relative_squared_error: 0.1512, scimark_benchmark: 939.8002, usercpu_time_millis: 2410, usercpu_time_millis_testing: 1120, usercpu_time_millis_training: 1290,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9998, f_measure: 0.9932, kappa: 0.984, kb_relative_information_score: 3526.4101, mean_absolute_error: 0.0167, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9932, predictive_accuracy: 0.9932, prior_entropy: 0.8898, recall: 0.9932, relative_absolute_error: 0.0393, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0746, root_relative_squared_error: 0.1618, scimark_benchmark: 922.613, usercpu_time_millis: 1060, usercpu_time_millis_testing: 390, usercpu_time_millis_training: 670,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9999, f_measure: 0.9937, kappa: 0.9852, kb_relative_information_score: 3526.9789, mean_absolute_error: 0.0166, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9937, predictive_accuracy: 0.9937, prior_entropy: 0.8898, recall: 0.9937, relative_absolute_error: 0.0391, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0739, root_relative_squared_error: 0.1603, scimark_benchmark: 921.466, usercpu_time_millis: 470, usercpu_time_millis_testing: 140, usercpu_time_millis_training: 330,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9995, f_measure: 0.997, kappa: 0.9929, kb_relative_information_score: 3628.8971, mean_absolute_error: 0.0028, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.997, predictive_accuracy: 0.997, prior_entropy: 0.8898, recall: 0.997, relative_absolute_error: 0.0066, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0489, root_relative_squared_error: 0.1061, scimark_benchmark: 936.1714, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9995, f_measure: 0.997, kappa: 0.9929, kb_relative_information_score: 3628.8971, mean_absolute_error: 0.0028, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.997, predictive_accuracy: 0.997, prior_entropy: 0.8898, recall: 0.997, relative_absolute_error: 0.0066, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0489, root_relative_squared_error: 0.1061, scimark_benchmark: 889.4922, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9998, f_measure: 0.9973, kappa: 0.9936, kb_relative_information_score: 3630.5125, mean_absolute_error: 0.0026, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9973, predictive_accuracy: 0.9973, prior_entropy: 0.8898, recall: 0.9973, relative_absolute_error: 0.0062, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0464, root_relative_squared_error: 0.1007, scimark_benchmark: 936.7184,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9998, f_measure: 0.9973, kappa: 0.9936, kb_relative_information_score: 3630.3881, mean_absolute_error: 0.0027, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9973, predictive_accuracy: 0.9973, prior_entropy: 0.8898, recall: 0.9973, relative_absolute_error: 0.0063, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0464, root_relative_squared_error: 0.1007, scimark_benchmark: 929.0296, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9567, f_measure: 0.9731, kappa: 0.9361, kb_relative_information_score: 3411.5139, mean_absolute_error: 0.0265, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9745, predictive_accuracy: 0.9735, prior_entropy: 0.8898, recall: 0.9735, relative_absolute_error: 0.0623, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.1628, root_relative_squared_error: 0.3533, scimark_benchmark: 1309.0674, usercpu_time_millis: 130, usercpu_time_millis_testing: 60, usercpu_time_millis_training: 70,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9951, f_measure: 0.9858, kappa: 0.9667, kb_relative_information_score: 3483.8147, mean_absolute_error: 0.0205, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.986, predictive_accuracy: 0.9858, prior_entropy: 0.8898, recall: 0.9858, relative_absolute_error: 0.0482, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.1189, root_relative_squared_error: 0.258, scimark_benchmark: 1336.0954,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9997, f_measure: 0.9893, kappa: 0.9748, kb_relative_information_score: 3360.5321, mean_absolute_error: 0.0416, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9894, predictive_accuracy: 0.9893, prior_entropy: 0.8898, recall: 0.9893, relative_absolute_error: 0.0978, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.1019, root_relative_squared_error: 0.2211, scimark_benchmark: 1337.9552, usercpu_time_millis: 330, usercpu_time_millis_testing: 90, usercpu_time_millis_training: 240,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 0.9986, kappa: 0.9968, kb_relative_information_score: 3588.9213, mean_absolute_error: 0.0097, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9986, predictive_accuracy: 0.9986, prior_entropy: 0.8898, recall: 0.9986, relative_absolute_error: 0.0229, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0417, root_relative_squared_error: 0.0905, scimark_benchmark: 1314.2279, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 1, f_measure: 0.9973, kappa: 0.9936, kb_relative_information_score: 3633.5469, mean_absolute_error: 0.0022, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9973, predictive_accuracy: 0.9973, prior_entropy: 0.8898, recall: 0.9973, relative_absolute_error: 0.0053, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.0392, root_relative_squared_error: 0.0851, scimark_benchmark: 1325.8468,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9988, f_measure: 0.9825, kappa: 0.9588, kb_relative_information_score: 3416.978, mean_absolute_error: 0.0292, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9825, predictive_accuracy: 0.9825, prior_entropy: 0.8898, recall: 0.9825, relative_absolute_error: 0.0686, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.1067, root_relative_squared_error: 0.2316, scimark_benchmark: 1337.3324, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9996, f_measure: 0.9935, kappa: 0.9846, kb_relative_information_score: 3589.5402, mean_absolute_error: 0.0073, mean_prior_absolute_error: 0.4251, number_of_instances: 3660, precision: 0.9935, predictive_accuracy: 0.9934, prior_entropy: 0.8898, recall: 0.9934, relative_absolute_error: 0.0173, root_mean_prior_squared_error: 0.4608, root_mean_squared_error: 0.074, root_relative_squared_error: 0.1606, scimark_benchmark: 1358.6198, usercpu_time_millis: 370, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 360,

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