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OpenML
OpenML
Supervised Classification on monks-problems-3

Supervised Classification on monks-problems-3

Task 3494 Supervised Classification monks-problems-3 73042 runs submitted
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Visibility: Public
  • mythbusting_1 OpenML100 study_1 study_107 study_123 study_14 study_15 study_20 study_41 study_50 study_7 study_73 under100k under1m
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9865, f_measure: 0.9801, kappa: 0.9602, kb_relative_information_score: 362.8901, mean_absolute_error: 0.2051, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9802, predictive_accuracy: 0.9801, prior_entropy: 0.9989, recall: 0.9801, relative_absolute_error: 0.4109, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.2356, root_relative_squared_error: 0.4716, scimark_benchmark: 889.3151, usercpu_time_millis: 30, usercpu_time_millis_testing: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9476, f_measure: 0.9477, kappa: 0.8952, kb_relative_information_score: 495.8643, mean_absolute_error: 0.0523, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9477, predictive_accuracy: 0.9477, prior_entropy: 0.9989, recall: 0.9477, relative_absolute_error: 0.1049, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.2288, root_relative_squared_error: 0.4579, scimark_benchmark: 1363.454, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9889, f_measure: 0.9892, kappa: 0.9783, kb_relative_information_score: 541.9683, mean_absolute_error: 0.0108, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9893, predictive_accuracy: 0.9892, prior_entropy: 0.9989, recall: 0.9892, relative_absolute_error: 0.0217, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1041, root_relative_squared_error: 0.2083, scimark_benchmark: 1312.3073, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9646, f_measure: 0.9639, kappa: 0.9278, kb_relative_information_score: 513.905, mean_absolute_error: 0.0361, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9646, predictive_accuracy: 0.9639, prior_entropy: 0.9989, recall: 0.9639, relative_absolute_error: 0.0723, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.19, root_relative_squared_error: 0.3803, scimark_benchmark: 939.5088, usercpu_time_millis: 230, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 180,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.975, f_measure: 0.9747, kappa: 0.9494, kb_relative_information_score: 525.9321, mean_absolute_error: 0.0253, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9748, predictive_accuracy: 0.9747, prior_entropy: 0.9989, recall: 0.9747, relative_absolute_error: 0.0506, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.159, root_relative_squared_error: 0.3182, scimark_benchmark: 932.5646, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9848, f_measure: 0.9783, kappa: 0.9566, kb_relative_information_score: 505.3428, mean_absolute_error: 0.0508, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9784, predictive_accuracy: 0.9783, prior_entropy: 0.9989, recall: 0.9783, relative_absolute_error: 0.1018, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1379, root_relative_squared_error: 0.2761, scimark_benchmark: 923.988, usercpu_time_millis: 140, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9646, f_measure: 0.9639, kappa: 0.9278, kb_relative_information_score: 513.905, mean_absolute_error: 0.0361, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9646, predictive_accuracy: 0.9639, prior_entropy: 0.9989, recall: 0.9639, relative_absolute_error: 0.0723, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.19, root_relative_squared_error: 0.3803, scimark_benchmark: 942.9708,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9902, f_measure: 0.9892, kappa: 0.9783, kb_relative_information_score: 507.7237, mean_absolute_error: 0.0508, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9893, predictive_accuracy: 0.9892, prior_entropy: 0.9989, recall: 0.9892, relative_absolute_error: 0.1017, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1217, root_relative_squared_error: 0.2435, scimark_benchmark: 899.5042, usercpu_time_millis: 3520, usercpu_time_millis_testing: 100, usercpu_time_millis_training: 3420,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9894, f_measure: 0.9819, kappa: 0.9638, kb_relative_information_score: 497.9099, mean_absolute_error: 0.0586, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9823, predictive_accuracy: 0.9819, prior_entropy: 0.9989, recall: 0.9819, relative_absolute_error: 0.1173, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1459, root_relative_squared_error: 0.292, scimark_benchmark: 1355.9413,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9887, f_measure: 0.9892, kappa: 0.9783, kb_relative_information_score: 476.6408, mean_absolute_error: 0.0863, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9893, predictive_accuracy: 0.9892, prior_entropy: 0.9989, recall: 0.9892, relative_absolute_error: 0.1728, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1407, root_relative_squared_error: 0.2816, scimark_benchmark: 1368.9272, usercpu_time_millis: 80, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9904, f_measure: 0.9801, kappa: 0.9602, kb_relative_information_score: 502.1837, mean_absolute_error: 0.056, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9801, predictive_accuracy: 0.9801, prior_entropy: 0.9989, recall: 0.9801, relative_absolute_error: 0.1123, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1297, root_relative_squared_error: 0.2596, scimark_benchmark: 1336.2509, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9737, f_measure: 0.9657, kappa: 0.9313, kb_relative_information_score: 514.2458, mean_absolute_error: 0.0363, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9657, predictive_accuracy: 0.9657, prior_entropy: 0.9989, recall: 0.9657, relative_absolute_error: 0.0727, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1741, root_relative_squared_error: 0.3484, scimark_benchmark: 1316.0472,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9896, f_measure: 0.9892, kappa: 0.9783, kb_relative_information_score: 533.6221, mean_absolute_error: 0.021, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9893, predictive_accuracy: 0.9892, prior_entropy: 0.9989, recall: 0.9892, relative_absolute_error: 0.0421, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1045, root_relative_squared_error: 0.2092, scimark_benchmark: 1325.942,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9819, f_measure: 0.9892, kappa: 0.9783, kb_relative_information_score: 533.5649, mean_absolute_error: 0.0212, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9893, predictive_accuracy: 0.9892, prior_entropy: 0.9989, recall: 0.9892, relative_absolute_error: 0.0426, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1038, root_relative_squared_error: 0.2078, scimark_benchmark: 1306.6379, usercpu_time_millis: 80, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9766, f_measure: 0.9765, kappa: 0.953, kb_relative_information_score: 527.9367, mean_absolute_error: 0.0235, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9765, predictive_accuracy: 0.9765, prior_entropy: 0.9989, recall: 0.9765, relative_absolute_error: 0.047, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1532, root_relative_squared_error: 0.3066, scimark_benchmark: 1306.6379, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4504, f_measure: 0.4434, kappa: -0.1002, kb_relative_information_score: -49.3665, mean_absolute_error: 0.5433, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.4467, predictive_accuracy: 0.4567, prior_entropy: 0.9989, recall: 0.4567, relative_absolute_error: 1.0884, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.7371, root_relative_squared_error: 1.4754, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9876, f_measure: 0.9892, kappa: 0.9783, kb_relative_information_score: 533.4353, mean_absolute_error: 0.0214, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9893, predictive_accuracy: 0.9892, prior_entropy: 0.9989, recall: 0.9892, relative_absolute_error: 0.0428, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1038, root_relative_squared_error: 0.2078, scimark_benchmark: 1384.4418,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9696, f_measure: 0.9693, kappa: 0.9386, kb_relative_information_score: 519.9186, mean_absolute_error: 0.0307, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9695, predictive_accuracy: 0.9693, prior_entropy: 0.9989, recall: 0.9693, relative_absolute_error: 0.0615, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1752, root_relative_squared_error: 0.3506, scimark_benchmark: 1466.6185,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7935, f_measure: 0.794, kappa: 0.5939, kb_relative_information_score: 331.4932, mean_absolute_error: 0.2004, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.8258, predictive_accuracy: 0.7996, prior_entropy: 0.9989, recall: 0.7996, relative_absolute_error: 0.4014, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.4476, root_relative_squared_error: 0.8959, scimark_benchmark: 1466.6185,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9886, f_measure: 0.9856, kappa: 0.9711, kb_relative_information_score: 537.5506, mean_absolute_error: 0.0149, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9856, predictive_accuracy: 0.9856, prior_entropy: 0.9989, recall: 0.9856, relative_absolute_error: 0.0298, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1206, root_relative_squared_error: 0.2413, scimark_benchmark: 917.4321, usercpu_time_millis: 13980, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 13960,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9515, f_measure: 0.9513, kappa: 0.9024, kb_relative_information_score: 499.8733, mean_absolute_error: 0.0487, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9514, predictive_accuracy: 0.9513, prior_entropy: 0.9989, recall: 0.9513, relative_absolute_error: 0.0976, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.2208, root_relative_squared_error: 0.4419, scimark_benchmark: 1363.434, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4927, f_measure: 0.3556, kb_relative_information_score: -0.0183, mean_absolute_error: 0.4992, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.2703, predictive_accuracy: 0.5199, prior_entropy: 0.9989, recall: 0.5199, relative_absolute_error: 1, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.4996, root_relative_squared_error: 1, scimark_benchmark: 1505.597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9902, f_measure: 0.9892, kappa: 0.9783, kb_relative_information_score: 533.5552, mean_absolute_error: 0.0211, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9893, predictive_accuracy: 0.9892, prior_entropy: 0.9989, recall: 0.9892, relative_absolute_error: 0.0422, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1051, root_relative_squared_error: 0.2103, scimark_benchmark: 1503.3362,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9812, f_measure: 0.9639, kappa: 0.9278, kb_relative_information_score: 504.396, mean_absolute_error: 0.0471, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9646, predictive_accuracy: 0.9639, prior_entropy: 0.9989, recall: 0.9639, relative_absolute_error: 0.0943, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1895, root_relative_squared_error: 0.3793, scimark_benchmark: 945.7621, usercpu_time_millis: 30, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9821, f_measure: 0.9621, kappa: 0.9241, kb_relative_information_score: 485.7111, mean_absolute_error: 0.0682, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9622, predictive_accuracy: 0.9621, prior_entropy: 0.9989, recall: 0.9621, relative_absolute_error: 0.1365, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1805, root_relative_squared_error: 0.3614, scimark_benchmark: 943.2817, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.983, f_measure: 0.9621, kappa: 0.9241, kb_relative_information_score: 483.4393, mean_absolute_error: 0.0707, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9622, predictive_accuracy: 0.9621, prior_entropy: 0.9989, recall: 0.9621, relative_absolute_error: 0.1416, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1797, root_relative_squared_error: 0.3597, scimark_benchmark: 943.2817, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.983, f_measure: 0.9621, kappa: 0.9241, kb_relative_information_score: 483.4393, mean_absolute_error: 0.0707, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9622, predictive_accuracy: 0.9621, prior_entropy: 0.9989, recall: 0.9621, relative_absolute_error: 0.1416, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1797, root_relative_squared_error: 0.3597, scimark_benchmark: 943.2817, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9831, f_measure: 0.9585, kappa: 0.9168, kb_relative_information_score: 503.1742, mean_absolute_error: 0.0464, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9587, predictive_accuracy: 0.9585, prior_entropy: 0.9989, recall: 0.9585, relative_absolute_error: 0.093, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.194, root_relative_squared_error: 0.3882, scimark_benchmark: 911.3823, usercpu_time_millis: 80, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9838, f_measure: 0.9603, kappa: 0.9204, kb_relative_information_score: 508.2981, mean_absolute_error: 0.0415, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9604, predictive_accuracy: 0.9603, prior_entropy: 0.9989, recall: 0.9603, relative_absolute_error: 0.0832, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1816, root_relative_squared_error: 0.3635, scimark_benchmark: 936.6206, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9833, f_measure: 0.9567, kappa: 0.9132, kb_relative_information_score: 506.3219, mean_absolute_error: 0.0435, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9567, predictive_accuracy: 0.9567, prior_entropy: 0.9989, recall: 0.9567, relative_absolute_error: 0.0871, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1791, root_relative_squared_error: 0.3584, scimark_benchmark: 945.6434, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9808, f_measure: 0.9513, kappa: 0.9024, kb_relative_information_score: 494.959, mean_absolute_error: 0.0551, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9513, predictive_accuracy: 0.9513, prior_entropy: 0.9989, recall: 0.9513, relative_absolute_error: 0.1103, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1913, root_relative_squared_error: 0.3829, scimark_benchmark: 938.2848,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9576, f_measure: 0.9639, kappa: 0.9278, kb_relative_information_score: 493.1263, mean_absolute_error: 0.06, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9646, predictive_accuracy: 0.9639, prior_entropy: 0.9989, recall: 0.9639, relative_absolute_error: 0.1202, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1954, root_relative_squared_error: 0.391, scimark_benchmark: 938.4285, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9849, f_measure: 0.9838, kappa: 0.9675, kb_relative_information_score: 509.4081, mean_absolute_error: 0.0467, mean_prior_absolute_error: 0.4992, number_of_instances: 554, precision: 0.9838, predictive_accuracy: 0.9838, prior_entropy: 0.9989, recall: 0.9838, relative_absolute_error: 0.0934, root_mean_prior_squared_error: 0.4996, root_mean_squared_error: 0.1337, root_relative_squared_error: 0.2675, scimark_benchmark: 945.7621, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
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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

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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