OpenML
Supervised Classification on hepatitis

Supervised Classification on hepatitis

Task 284 Supervised Classification hepatitis 375 runs submitted
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6134, f_measure: 0.6944, kappa: 0.148, kb_relative_information_score: 6.3812, mean_absolute_error: 0.2873, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.685, predictive_accuracy: 0.7255, prior_entropy: 0.7418, recall: 0.7255, relative_absolute_error: 0.8027, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4901, root_relative_squared_error: 1.1187, scimark_benchmark: 906.0979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6731, f_measure: 0.7236, kappa: 0.2234, kb_relative_information_score: 10.168, mean_absolute_error: 0.2712, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7361, predictive_accuracy: 0.7647, prior_entropy: 0.7418, recall: 0.7647, relative_absolute_error: 0.7576, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4344, root_relative_squared_error: 0.9915, scimark_benchmark: 972.587, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6852, f_measure: 0.6373, kappa: -0.0046, kb_relative_information_score: -3.136, mean_absolute_error: 0.3317, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.6182, predictive_accuracy: 0.6667, prior_entropy: 0.7418, recall: 0.6667, relative_absolute_error: 0.9267, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.5035, root_relative_squared_error: 1.1492, scimark_benchmark: 851.2074, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6363, kb_relative_information_score: 11.4722, mean_absolute_error: 0.2549, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.5552, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.7121, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.5049, root_relative_squared_error: 1.1524, scimark_benchmark: 916.0735, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6363, kb_relative_information_score: 11.4722, mean_absolute_error: 0.2549, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.5552, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.7121, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.5049, root_relative_squared_error: 1.1524, scimark_benchmark: 941.6675, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7895, f_measure: 0.8039, kappa: 0.4838, kb_relative_information_score: 20.1376, mean_absolute_error: 0.2152, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8039, predictive_accuracy: 0.8039, prior_entropy: 0.7418, recall: 0.8039, relative_absolute_error: 0.6013, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.411, root_relative_squared_error: 0.9381, scimark_benchmark: 934.695,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7895, f_measure: 0.8039, kappa: 0.4838, kb_relative_information_score: 20.1376, mean_absolute_error: 0.2152, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8039, predictive_accuracy: 0.8039, prior_entropy: 0.7418, recall: 0.8039, relative_absolute_error: 0.6013, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.411, root_relative_squared_error: 0.9381, scimark_benchmark: 938.191,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7257, f_measure: 0.6677, kappa: 0.0701, kb_relative_information_score: 5.1475, mean_absolute_error: 0.3057, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.6901, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.8542, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4167, root_relative_squared_error: 0.9511, scimark_benchmark: 941.6675,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7895, f_measure: 0.8039, kappa: 0.4838, kb_relative_information_score: 20.1376, mean_absolute_error: 0.2152, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8039, predictive_accuracy: 0.8039, prior_entropy: 0.7418, recall: 0.8039, relative_absolute_error: 0.6013, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.411, root_relative_squared_error: 0.9381, scimark_benchmark: 905.2959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8735, f_measure: 0.8506, kappa: 0.5863, kb_relative_information_score: 23.0151, mean_absolute_error: 0.2028, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8642, predictive_accuracy: 0.8627, prior_entropy: 0.7418, recall: 0.8627, relative_absolute_error: 0.5665, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3353, root_relative_squared_error: 0.7654, scimark_benchmark: 927.2917, usercpu_time_millis: 400, usercpu_time_millis_training: 400,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7773, f_measure: 0.6944, kappa: 0.148, kb_relative_information_score: 10.7739, mean_absolute_error: 0.2746, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.685, predictive_accuracy: 0.7255, prior_entropy: 0.7418, recall: 0.7255, relative_absolute_error: 0.7671, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.391, root_relative_squared_error: 0.8925, scimark_benchmark: 931.771, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6363, kb_relative_information_score: 11.4722, mean_absolute_error: 0.2549, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.5552, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.7121, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.5049, root_relative_squared_error: 1.1524, scimark_benchmark: 937.5117, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6363, kb_relative_information_score: 11.4722, mean_absolute_error: 0.2549, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.5552, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.7121, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.5049, root_relative_squared_error: 1.1524, scimark_benchmark: 974.2014, usercpu_time_millis: 40, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8036, f_measure: 0.8039, kappa: 0.4838, kb_relative_information_score: 21.0655, mean_absolute_error: 0.204, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8039, predictive_accuracy: 0.8039, prior_entropy: 0.7418, recall: 0.8039, relative_absolute_error: 0.5701, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4184, root_relative_squared_error: 0.955, scimark_benchmark: 941.3847,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7895, f_measure: 0.8039, kappa: 0.4838, kb_relative_information_score: 20.1376, mean_absolute_error: 0.2152, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8039, predictive_accuracy: 0.8039, prior_entropy: 0.7418, recall: 0.8039, relative_absolute_error: 0.6013, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.411, root_relative_squared_error: 0.9381, scimark_benchmark: 941.3847,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7895, f_measure: 0.8039, kappa: 0.4838, kb_relative_information_score: 20.1376, mean_absolute_error: 0.2152, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8039, predictive_accuracy: 0.8039, prior_entropy: 0.7418, recall: 0.8039, relative_absolute_error: 0.6013, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.411, root_relative_squared_error: 0.9381, scimark_benchmark: 941.3847,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8735, f_measure: 0.8506, kappa: 0.5863, kb_relative_information_score: 23.0151, mean_absolute_error: 0.2028, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8642, predictive_accuracy: 0.8627, prior_entropy: 0.7418, recall: 0.8627, relative_absolute_error: 0.5665, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3353, root_relative_squared_error: 0.7654, scimark_benchmark: 938.5498, usercpu_time_millis: 270, usercpu_time_millis_training: 270,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7773, f_measure: 0.6944, kappa: 0.148, kb_relative_information_score: 10.7739, mean_absolute_error: 0.2746, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.685, predictive_accuracy: 0.7255, prior_entropy: 0.7418, recall: 0.7255, relative_absolute_error: 0.7671, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.391, root_relative_squared_error: 0.8925, scimark_benchmark: 943.1009, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6134, f_measure: 0.6944, kappa: 0.148, kb_relative_information_score: 6.3812, mean_absolute_error: 0.2873, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.685, predictive_accuracy: 0.7255, prior_entropy: 0.7418, recall: 0.7255, relative_absolute_error: 0.8027, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4901, root_relative_squared_error: 1.1187, scimark_benchmark: 819.5729,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6731, f_measure: 0.7236, kappa: 0.2234, kb_relative_information_score: 10.168, mean_absolute_error: 0.2712, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7361, predictive_accuracy: 0.7647, prior_entropy: 0.7418, recall: 0.7647, relative_absolute_error: 0.7576, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4344, root_relative_squared_error: 0.9915, scimark_benchmark: 935.2002, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6852, f_measure: 0.6373, kappa: -0.0046, kb_relative_information_score: -3.136, mean_absolute_error: 0.3317, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.6182, predictive_accuracy: 0.6667, prior_entropy: 0.7418, recall: 0.6667, relative_absolute_error: 0.9267, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.5035, root_relative_squared_error: 1.1492, scimark_benchmark: 936.2574, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.6363, kb_relative_information_score: 11.4722, mean_absolute_error: 0.2549, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.5552, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.7121, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.5049, root_relative_squared_error: 1.1524, scimark_benchmark: 927.2882, usercpu_time_millis: 40, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7895, f_measure: 0.8039, kappa: 0.4838, kb_relative_information_score: 20.1376, mean_absolute_error: 0.2152, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8039, predictive_accuracy: 0.8039, prior_entropy: 0.7418, recall: 0.8039, relative_absolute_error: 0.6013, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.411, root_relative_squared_error: 0.9381, scimark_benchmark: 938.1282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7895, f_measure: 0.8039, kappa: 0.4838, kb_relative_information_score: 20.1376, mean_absolute_error: 0.2152, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8039, predictive_accuracy: 0.8039, prior_entropy: 0.7418, recall: 0.8039, relative_absolute_error: 0.6013, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.411, root_relative_squared_error: 0.9381, scimark_benchmark: 938.1282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7895, f_measure: 0.8039, kappa: 0.4838, kb_relative_information_score: 20.1376, mean_absolute_error: 0.2152, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8039, predictive_accuracy: 0.8039, prior_entropy: 0.7418, recall: 0.8039, relative_absolute_error: 0.6013, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.411, root_relative_squared_error: 0.9381, scimark_benchmark: 933.3455,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7257, f_measure: 0.6677, kappa: 0.0701, kb_relative_information_score: 5.1475, mean_absolute_error: 0.3057, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.6901, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.8542, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4167, root_relative_squared_error: 0.9511, scimark_benchmark: 941.4991, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7834, f_measure: 0.8211, kappa: 0.5234, kb_relative_information_score: 19.4929, mean_absolute_error: 0.2169, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8195, predictive_accuracy: 0.8235, prior_entropy: 0.7418, recall: 0.8235, relative_absolute_error: 0.6059, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3836, root_relative_squared_error: 0.8756, scimark_benchmark: 730.6551, usercpu_time_millis: 180, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 170,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7895, f_measure: 0.8039, kappa: 0.4838, kb_relative_information_score: 20.1376, mean_absolute_error: 0.2152, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8039, predictive_accuracy: 0.8039, prior_entropy: 0.7418, recall: 0.8039, relative_absolute_error: 0.6013, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.411, root_relative_squared_error: 0.9381, scimark_benchmark: 932.438,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7773, f_measure: 0.6944, kappa: 0.148, kb_relative_information_score: 10.7739, mean_absolute_error: 0.2746, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.685, predictive_accuracy: 0.7255, prior_entropy: 0.7418, recall: 0.7255, relative_absolute_error: 0.7671, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.391, root_relative_squared_error: 0.8925, scimark_benchmark: 901.4991, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7854, f_measure: 0.7653, kappa: 0.3499, kb_relative_information_score: 10.288, mean_absolute_error: 0.2686, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7658, predictive_accuracy: 0.7843, prior_entropy: 0.7418, recall: 0.7843, relative_absolute_error: 0.7504, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3882, root_relative_squared_error: 0.8861, scimark_benchmark: 763.3895, usercpu_time_millis: 2320, usercpu_time_millis_testing: 1010, usercpu_time_millis_training: 1310,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7976, f_measure: 0.808, kappa: 0.4681, kb_relative_information_score: 10.4456, mean_absolute_error: 0.268, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.815, predictive_accuracy: 0.8235, prior_entropy: 0.7418, recall: 0.8235, relative_absolute_error: 0.7488, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.383, root_relative_squared_error: 0.8742, scimark_benchmark: 859.5223, usercpu_time_millis: 900, usercpu_time_millis_testing: 260, usercpu_time_millis_training: 640,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7611, f_measure: 0.8154, kappa: 0.4973, kb_relative_information_score: 12.4776, mean_absolute_error: 0.2614, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8145, predictive_accuracy: 0.8235, prior_entropy: 0.7418, recall: 0.8235, relative_absolute_error: 0.7304, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3813, root_relative_squared_error: 0.8704, scimark_benchmark: 941.589, usercpu_time_millis: 550, usercpu_time_millis_testing: 300, usercpu_time_millis_training: 250,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8188, f_measure: 0.7743, kappa: 0.3855, kb_relative_information_score: 12.9358, mean_absolute_error: 0.2563, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7708, predictive_accuracy: 0.7843, prior_entropy: 0.7418, recall: 0.7843, relative_absolute_error: 0.7159, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3716, root_relative_squared_error: 0.8483, scimark_benchmark: 911.2316, usercpu_time_millis: 160, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 110,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8198, f_measure: 0.7537, kappa: 0.31, kb_relative_information_score: 11.8223, mean_absolute_error: 0.2589, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.766, predictive_accuracy: 0.7843, prior_entropy: 0.7418, recall: 0.7843, relative_absolute_error: 0.7233, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3753, root_relative_squared_error: 0.8567, scimark_benchmark: 889.4922, usercpu_time_millis: 90, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7753, f_measure: 0.6776, kappa: 0.0939, kb_relative_information_score: 12.8296, mean_absolute_error: 0.2574, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.6689, predictive_accuracy: 0.7255, prior_entropy: 0.7418, recall: 0.7255, relative_absolute_error: 0.719, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4475, root_relative_squared_error: 1.0214, scimark_benchmark: 926.5859, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7753, f_measure: 0.6776, kappa: 0.0939, kb_relative_information_score: 12.8296, mean_absolute_error: 0.2574, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.6689, predictive_accuracy: 0.7255, prior_entropy: 0.7418, recall: 0.7255, relative_absolute_error: 0.719, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4475, root_relative_squared_error: 1.0214, scimark_benchmark: 926.5859,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7753, f_measure: 0.6776, kappa: 0.0939, kb_relative_information_score: 12.8296, mean_absolute_error: 0.2574, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.6689, predictive_accuracy: 0.7255, prior_entropy: 0.7418, recall: 0.7255, relative_absolute_error: 0.719, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4475, root_relative_squared_error: 1.0214, scimark_benchmark: 894.7131, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7773, f_measure: 0.6944, kappa: 0.148, kb_relative_information_score: 10.7739, mean_absolute_error: 0.2746, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.685, predictive_accuracy: 0.7255, prior_entropy: 0.7418, recall: 0.7255, relative_absolute_error: 0.7671, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.391, root_relative_squared_error: 0.8925, scimark_benchmark: 1374.9737, usercpu_time_millis: 50, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 40,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7834, f_measure: 0.8211, kappa: 0.5234, kb_relative_information_score: 19.4929, mean_absolute_error: 0.2169, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8195, predictive_accuracy: 0.8235, prior_entropy: 0.7418, recall: 0.8235, relative_absolute_error: 0.6059, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3836, root_relative_squared_error: 0.8756, scimark_benchmark: 1393.8432, usercpu_time_millis: 140, usercpu_time_millis_training: 140,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6731, f_measure: 0.7236, kappa: 0.2234, kb_relative_information_score: 10.168, mean_absolute_error: 0.2712, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7361, predictive_accuracy: 0.7647, prior_entropy: 0.7418, recall: 0.7647, relative_absolute_error: 0.7576, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4344, root_relative_squared_error: 0.9915, scimark_benchmark: 1345.6844,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7834, f_measure: 0.8211, kappa: 0.5234, kb_relative_information_score: 19.4929, mean_absolute_error: 0.2169, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8195, predictive_accuracy: 0.8235, prior_entropy: 0.7418, recall: 0.8235, relative_absolute_error: 0.6059, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3836, root_relative_squared_error: 0.8756, scimark_benchmark: 1326.2019, usercpu_time_millis: 140, usercpu_time_millis_training: 140,
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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