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: 0.7328, f_measure: 0.7983, kappa: 0.4563, kb_relative_information_score: 16.3338, mean_absolute_error: 0.224, 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: 0.6258, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4007, root_relative_squared_error: 0.9147, scimark_benchmark: 854.5188, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6387, f_measure: 0.7255, kappa: 0.2773, kb_relative_information_score: 7.98, mean_absolute_error: 0.2745, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7255, 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: 0.5239, root_relative_squared_error: 1.1959, scimark_benchmark: 1318.1432, 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: 938.343, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7419, f_measure: 0.8039, kappa: 0.4838, kb_relative_information_score: 21.9487, mean_absolute_error: 0.1961, 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: 0.5478, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4428, root_relative_squared_error: 1.0108, scimark_benchmark: 916.5955, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.753, f_measure: 0.8039, kappa: 0.4838, kb_relative_information_score: 17.3029, mean_absolute_error: 0.2254, 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: 0.6298, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4199, root_relative_squared_error: 0.9586, scimark_benchmark: 1318.1432, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5769, f_measure: 0.7189, kappa: 0.2132, kb_relative_information_score: 18.4565, mean_absolute_error: 0.2157, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.8327, predictive_accuracy: 0.7843, prior_entropy: 0.7418, recall: 0.7843, relative_absolute_error: 0.6026, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4644, root_relative_squared_error: 1.0601, scimark_benchmark: 939.449, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
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: 1330.0694, usercpu_time_millis: 130, usercpu_time_millis_training: 130,
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: 1072.3689, usercpu_time_millis: 250, usercpu_time_millis_training: 250,
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: 1280.6952, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7034, f_measure: 0.7814, kappa: 0.4174, kb_relative_information_score: 18.6791, mean_absolute_error: 0.2111, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7792, predictive_accuracy: 0.7843, prior_entropy: 0.7418, recall: 0.7843, relative_absolute_error: 0.5898, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4408, root_relative_squared_error: 1.0062, scimark_benchmark: 1315.3881,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5506, f_measure: 0.6315, kappa: -0.0355, kb_relative_information_score: 1.9554, mean_absolute_error: 0.3042, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.6017, predictive_accuracy: 0.6863, prior_entropy: 0.7418, recall: 0.6863, relative_absolute_error: 0.8498, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4928, root_relative_squared_error: 1.1248, scimark_benchmark: 1319.6463,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5931, f_measure: 0.6557, kappa: 0.0325, kb_relative_information_score: 4.8147, mean_absolute_error: 0.3054, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.6438, predictive_accuracy: 0.7255, prior_entropy: 0.7418, recall: 0.7255, relative_absolute_error: 0.8532, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.48, root_relative_squared_error: 1.0957, scimark_benchmark: 1073.494, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6913, f_measure: 0.791, kappa: 0.4257, kb_relative_information_score: 21.9487, mean_absolute_error: 0.1961, 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: 0.5478, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4428, root_relative_squared_error: 1.0108, scimark_benchmark: 1442.7264,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.501, f_measure: 0.2084, kappa: 0.0011, kb_relative_information_score: -68.8475, mean_absolute_error: 0.7059, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.6239, predictive_accuracy: 0.2941, prior_entropy: 0.7418, recall: 0.2941, relative_absolute_error: 1.9721, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.8402, root_relative_squared_error: 1.9178, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6549, f_measure: 0.7333, kappa: 0.2738, kb_relative_information_score: 8.5316, mean_absolute_error: 0.2802, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7272, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.7827, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4789, root_relative_squared_error: 1.0931, scimark_benchmark: 1466.6185,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6134, f_measure: 0.7176, kappa: 0.2388, kb_relative_information_score: 7.98, mean_absolute_error: 0.2745, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7119, 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: 0.5239, root_relative_squared_error: 1.1959, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5638, f_measure: 0.7049, kappa: 0.1707, kb_relative_information_score: 14.9643, mean_absolute_error: 0.2353, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7443, 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: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, 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: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6245, 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: 1054.3694,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7176, build_cpu_time: 0.22, build_memory: 499634264, f_measure: 0.7417, kappa: 0.3115, kb_relative_information_score: 11.8723, mean_absolute_error: 0.2512, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7388, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.7017, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4972, root_relative_squared_error: 1.1349, scimark_benchmark: 941.9296,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7176, build_cpu_time: 0.187, build_memory: 1302531160, f_measure: 0.7417, kappa: 0.3115, kb_relative_information_score: 11.8723, mean_absolute_error: 0.2512, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7388, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.7017, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4972, root_relative_squared_error: 1.1349, scimark_benchmark: 940.9906,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7176, build_cpu_time: 0.197, build_memory: 851594240, f_measure: 0.7417, kappa: 0.3115, kb_relative_information_score: 11.8723, mean_absolute_error: 0.2512, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7388, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.7017, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4972, root_relative_squared_error: 1.1349, scimark_benchmark: 920.993,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7186, build_cpu_time: 0.109, build_memory: 456906304, f_measure: 0.7417, kappa: 0.3115, kb_relative_information_score: 12.4319, mean_absolute_error: 0.2458, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7388, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.6867, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4869, root_relative_squared_error: 1.1114, scimark_benchmark: 943.678,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7358, build_cpu_time: 0.054, build_memory: 927627968, f_measure: 0.7417, kappa: 0.3115, kb_relative_information_score: 16.1827, mean_absolute_error: 0.224, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.7388, predictive_accuracy: 0.7451, prior_entropy: 0.7418, recall: 0.7451, relative_absolute_error: 0.6257, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4529, root_relative_squared_error: 1.0338, scimark_benchmark: 940.9906,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6842, build_cpu_time: 0.007, build_memory: 531849304, f_measure: 0.6373, kappa: -0.0046, kb_relative_information_score: 2.4248, mean_absolute_error: 0.3089, 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: 0.863, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.5198, root_relative_squared_error: 1.1864, scimark_benchmark: 942.573,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5931, build_cpu_time: 0.003, build_memory: 108717608, f_measure: 0.7089, kappa: 0.1845, kb_relative_information_score: 12.0751, mean_absolute_error: 0.2532, 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: 0.7073, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4959, root_relative_squared_error: 1.132, scimark_benchmark: 907.1899,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7257, build_cpu_time: 0.007, build_memory: 1224879464, 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: 945.1122,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7257, build_cpu_time: 0.008, build_memory: 636010144, 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: 933.4176,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6984, build_cpu_time: 0.008, build_memory: 10002880, f_measure: 0.6799, kappa: 0.1136, kb_relative_information_score: 5.3833, mean_absolute_error: 0.2896, mean_prior_absolute_error: 0.3579, number_of_instances: 51, precision: 0.6674, predictive_accuracy: 0.7059, prior_entropy: 0.7418, recall: 0.7059, relative_absolute_error: 0.8092, root_mean_prior_squared_error: 0.4381, root_mean_squared_error: 0.4754, root_relative_squared_error: 1.0852, scimark_benchmark: 940.7816,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6245, build_cpu_time: 0.001, build_memory: 615883064, 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: 940.3415,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, build_memory: 109148592, 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: 949.9767,
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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