Task
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: 0.5, build_memory: 698006480, f_measure: 0.6363, kb_relative_information_score: 1.3065, mean_absolute_error: 0.3474, 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: 0.9705, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4408, root_relative_squared_error: 1.0062, scimark_benchmark: 946.9694,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.749, build_cpu_time: 0.001, build_memory: 349214440, f_measure: 0.8115, kappa: 0.5313, kb_relative_information_score: 17.933, mean_absolute_error: 0.2253, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8293, predictive_accuracy: 0.8039, prior_entropy: 0.7418, recall: 0.8039, relative_absolute_error: 0.6295, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4363, root_relative_squared_error: 0.996, scimark_benchmark: 943.2554,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7429, build_cpu_time: 0.092, build_memory: 531260112, f_measure: 0.8211, kappa: 0.5234, kb_relative_information_score: 18.3618, mean_absolute_error: 0.2196, 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: 0.6135, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4063, root_relative_squared_error: 0.9275, scimark_benchmark: 926.0021,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7186, build_cpu_time: 0.048, build_memory: 419226376, f_measure: 0.8211, kappa: 0.5234, kb_relative_information_score: 19.946, mean_absolute_error: 0.2098, 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: 0.5861, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4007, root_relative_squared_error: 0.9147, scimark_benchmark: 928.8874,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7186, build_cpu_time: 0.048, build_memory: 801351584, f_measure: 0.8211, kappa: 0.5234, kb_relative_information_score: 19.946, mean_absolute_error: 0.2098, 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: 0.5861, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4007, root_relative_squared_error: 0.9147, scimark_benchmark: 938.2568,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7439, build_cpu_time: 0.109, build_memory: 218876232, f_measure: 0.8211, kappa: 0.5234, kb_relative_information_score: 19.6162, mean_absolute_error: 0.2127, 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: 0.5944, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4012, root_relative_squared_error: 0.9157, scimark_benchmark: 928.0863,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7551, build_cpu_time: 0.009, build_memory: 836226280, f_measure: 0.7492, kappa: 0.3108, kb_relative_information_score: 7.6651, mean_absolute_error: 0.2849, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7448, predictive_accuracy: 0.7647, prior_entropy: 0.7418, recall: 0.7647, relative_absolute_error: 0.796, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3988, root_relative_squared_error: 0.9103, scimark_benchmark: 919.2952,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8198, build_cpu_time: 1.188, build_memory: 53098152, 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: 937.52,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8198, build_cpu_time: 0.096, build_memory: 85468104, 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: 943.443,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8138, build_cpu_time: 0.038, build_memory: 474687688, f_measure: 0.791, kappa: 0.4722, kb_relative_information_score: 18.5391, mean_absolute_error: 0.2181, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8033, predictive_accuracy: 0.7843, prior_entropy: 0.7418, recall: 0.7843, relative_absolute_error: 0.6092, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3964, root_relative_squared_error: 0.9048, scimark_benchmark: 939.6798,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7166, build_cpu_time: 0.006, build_memory: 832787240, f_measure: 0.7743, kappa: 0.3855, kb_relative_information_score: 16.4759, mean_absolute_error: 0.2269, 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: 0.6338, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4658, root_relative_squared_error: 1.0633, scimark_benchmark: 905.0866,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.665, build_cpu_time: 0.045, build_memory: 47305904, f_measure: 0.7579, kappa: 0.3475, kb_relative_information_score: 14.9643, mean_absolute_error: 0.2353, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7537, predictive_accuracy: 0.7647, prior_entropy: 0.7418, recall: 0.7647, relative_absolute_error: 0.6574, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4851, root_relative_squared_error: 1.1072, scimark_benchmark: 938.6306,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.753, build_cpu_time: 0.003, build_memory: 195055784, f_measure: 0.791, kappa: 0.4722, kb_relative_information_score: 17.825, mean_absolute_error: 0.2266, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8033, predictive_accuracy: 0.7843, prior_entropy: 0.7418, recall: 0.7843, relative_absolute_error: 0.6332, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4269, root_relative_squared_error: 0.9744, scimark_benchmark: 942.5344,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.753, build_cpu_time: 0.003, build_memory: 65310040, f_measure: 0.791, kappa: 0.4722, kb_relative_information_score: 17.825, mean_absolute_error: 0.2266, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8033, predictive_accuracy: 0.7843, prior_entropy: 0.7418, recall: 0.7843, relative_absolute_error: 0.6332, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4269, root_relative_squared_error: 0.9744, scimark_benchmark: 929.8459,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.836, build_cpu_time: 25.279, build_memory: 3477968688, f_measure: 0.8211, kappa: 0.5234, kb_relative_information_score: 15.521, mean_absolute_error: 0.2308, 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: 0.6449, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3799, root_relative_squared_error: 0.8671, scimark_benchmark: 943.4955,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8178, build_cpu_time: 63.968, build_memory: 1469507968, f_measure: 0.8039, kappa: 0.4838, kb_relative_information_score: 15.9299, mean_absolute_error: 0.2294, 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: 0.641, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3828, root_relative_squared_error: 0.8738, scimark_benchmark: 942.9616,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7834, build_cpu_time: 0.028, build_memory: 523442896, f_measure: 0.6641, kappa: 0.059, kb_relative_information_score: 7.7811, mean_absolute_error: 0.2887, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.6479, predictive_accuracy: 0.7059, prior_entropy: 0.7418, recall: 0.7059, relative_absolute_error: 0.8065, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.405, root_relative_squared_error: 0.9245, scimark_benchmark: 941.5509,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7794, build_cpu_time: 0.014, build_memory: 3889226992, f_measure: 0.6776, kappa: 0.0939, kb_relative_information_score: 8.175, mean_absolute_error: 0.2884, 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: 0.8056, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4032, root_relative_squared_error: 0.9204, scimark_benchmark: 941.5509,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7581, build_cpu_time: 0.354, build_memory: 3039237888, f_measure: 0.8211, kappa: 0.5234, kb_relative_information_score: 24.4896, mean_absolute_error: 0.1841, 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: 0.5142, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4236, root_relative_squared_error: 0.9668, scimark_benchmark: 944.3501,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7085, build_cpu_time: 0.004, build_memory: 1163337832, f_measure: 0.7089, kappa: 0.1845, kb_relative_information_score: 3.5585, mean_absolute_error: 0.3012, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.707, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.8414, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4244, root_relative_squared_error: 0.9687, scimark_benchmark: 938.259,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7348, build_cpu_time: 0.163, build_memory: 1952525792, f_measure: 0.7983, kappa: 0.4563, kb_relative_information_score: 23.6582, mean_absolute_error: 0.1883, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7955, predictive_accuracy: 0.8039, prior_entropy: 0.7418, recall: 0.8039, relative_absolute_error: 0.5261, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4283, root_relative_squared_error: 0.9777, scimark_benchmark: 942.6348,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7267, build_cpu_time: 0.003, build_memory: 2374991744, f_measure: 0.7089, kappa: 0.1845, kb_relative_information_score: 5.5452, mean_absolute_error: 0.2945, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.707, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.8227, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4198, root_relative_squared_error: 0.9582, scimark_benchmark: 941.5509,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7814, build_cpu_time: 1.556, build_memory: 193326872, f_measure: 0.7743, kappa: 0.3855, kb_relative_information_score: 14.6402, mean_absolute_error: 0.2433, 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: 0.6796, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4017, root_relative_squared_error: 0.9169, scimark_benchmark: 742.9293,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7834, build_cpu_time: 2.545, build_memory: 431313400, f_measure: 0.7983, kappa: 0.4563, kb_relative_information_score: 16.8066, mean_absolute_error: 0.2345, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7955, predictive_accuracy: 0.8039, prior_entropy: 0.7418, recall: 0.8039, relative_absolute_error: 0.6553, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3898, root_relative_squared_error: 0.8898, scimark_benchmark: 920.6195,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7834, build_cpu_time: 4.636, build_memory: 3362385296, f_measure: 0.8211, kappa: 0.5234, kb_relative_information_score: 17.9691, mean_absolute_error: 0.2288, 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: 0.6393, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3848, root_relative_squared_error: 0.8784, scimark_benchmark: 942.7014,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6265, build_cpu_time: 0.153, build_memory: 187948344, f_measure: 0.7226, kappa: 0.2318, kb_relative_information_score: 11.5274, mean_absolute_error: 0.2544, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7166, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.7106, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.5032, root_relative_squared_error: 1.1486, scimark_benchmark: 941.4198,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6265, build_cpu_time: 0.124, build_memory: 300008272, f_measure: 0.7226, kappa: 0.2318, kb_relative_information_score: 11.5274, mean_absolute_error: 0.2544, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7166, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.7106, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.5032, root_relative_squared_error: 1.1486, scimark_benchmark: 944.2618,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6356, build_cpu_time: 0.068, build_memory: 1350333568, f_measure: 0.7089, kappa: 0.1845, kb_relative_information_score: 11.7046, mean_absolute_error: 0.2527, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.707, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.706, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.5005, root_relative_squared_error: 1.1424, scimark_benchmark: 942.6202,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.83, build_cpu_time: 0.147, build_memory: 1537093616, f_measure: 0.7236, kappa: 0.2234, kb_relative_information_score: 15.0543, mean_absolute_error: 0.2543, 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: 0.7104, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3757, root_relative_squared_error: 0.8575, scimark_benchmark: 944.3936,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8229, build_cpu_time: 0.308, build_memory: 385571112, f_measure: 0.6911, kappa: 0.1311, kb_relative_information_score: 14.5635, mean_absolute_error: 0.2574, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.6982, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.719, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.384, root_relative_squared_error: 0.8765, scimark_benchmark: 927.4927,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7854, build_cpu_time: 0.133, build_memory: 568996856, f_measure: 0.7653, kappa: 0.3499, kb_relative_information_score: 10.3116, mean_absolute_error: 0.273, 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: 0.7627, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3968, root_relative_squared_error: 0.9058, scimark_benchmark: 936.5167,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7935, build_cpu_time: 0.077, build_memory: 70014304, f_measure: 0.7653, kappa: 0.3499, kb_relative_information_score: 10.2835, mean_absolute_error: 0.2748, 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: 0.7677, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.3968, root_relative_squared_error: 0.9057, scimark_benchmark: 940.4249,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7804, build_cpu_time: 0.033, build_memory: 2414953968, f_measure: 0.791, kappa: 0.4257, kb_relative_information_score: 9.8495, mean_absolute_error: 0.2751, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7909, predictive_accuracy: 0.8039, prior_entropy: 0.7418, recall: 0.8039, relative_absolute_error: 0.7687, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4011, root_relative_squared_error: 0.9156, scimark_benchmark: 943.1552,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7753, build_cpu_time: 0.015, build_memory: 443627120, f_measure: 0.6944, kappa: 0.148, kb_relative_information_score: 10.4508, mean_absolute_error: 0.2745, 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: 0.7669, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4024, root_relative_squared_error: 0.9185, scimark_benchmark: 881.8588,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6245, build_cpu_time: 0.002, build_memory: 1817784280, f_measure: 0.7226, kappa: 0.2318, kb_relative_information_score: 8.9433, mean_absolute_error: 0.2742, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7166, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.7661, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4788, root_relative_squared_error: 1.0929, scimark_benchmark: 944.3283,

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