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Function: require_once

OpenML
OpenML
Supervised Classification on sleuth_ex2016

Supervised Classification on sleuth_ex2016

Task 3726 Supervised Classification sleuth_ex2016 506 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_107 study_41 under100k under1m
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506 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.719, build_cpu_time: 0.0138, build_memory: 1360104441.2874, f_measure: 0.677, kappa: 0.3535, kb_relative_information_score: 29.8606, mean_absolute_error: 0.331, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6787, predictive_accuracy: 0.6782, prior_entropy: 0.9992, recall: 0.6782, relative_absolute_error: 0.6627, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5119, root_relative_squared_error: 1.0245, scimark_benchmark: 923.9118,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7111, build_cpu_time: 0.0097, build_memory: 820935044.2299, f_measure: 0.6649, kappa: 0.3299, kb_relative_information_score: 27.6425, mean_absolute_error: 0.3412, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6676, predictive_accuracy: 0.6667, prior_entropy: 0.9992, recall: 0.6667, relative_absolute_error: 0.6833, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5642, root_relative_squared_error: 1.129, scimark_benchmark: 934.2858,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6897, build_cpu_time: 0.0186, build_memory: 313521545.0115, f_measure: 0.6547, kappa: 0.3084, kb_relative_information_score: 24.1783, mean_absolute_error: 0.3615, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.655, predictive_accuracy: 0.6552, prior_entropy: 0.9992, recall: 0.6552, relative_absolute_error: 0.7239, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5908, root_relative_squared_error: 1.1824, scimark_benchmark: 943.7751,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6685, build_cpu_time: 0.0598, build_memory: 428819782.8046, f_measure: 0.6539, kappa: 0.3073, kb_relative_information_score: 27.2342, mean_absolute_error: 0.3425, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6554, predictive_accuracy: 0.6552, prior_entropy: 0.9992, recall: 0.6552, relative_absolute_error: 0.6859, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5807, root_relative_squared_error: 1.1621, scimark_benchmark: 936.1433,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6331, build_cpu_time: 0.0751, build_memory: 1733587001.3793, f_measure: 0.6205, kappa: 0.2399, kb_relative_information_score: 21.4566, mean_absolute_error: 0.3755, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6205, predictive_accuracy: 0.6207, prior_entropy: 0.9992, recall: 0.6207, relative_absolute_error: 0.7518, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.6105, root_relative_squared_error: 1.2217, scimark_benchmark: 931.9671,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6175, build_cpu_time: 0.1482, build_memory: 1717641901.7012, f_measure: 0.6092, kappa: 0.2175, kb_relative_information_score: 18.916, mean_absolute_error: 0.3906, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6092, predictive_accuracy: 0.6092, prior_entropy: 0.9992, recall: 0.6092, relative_absolute_error: 0.782, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.6248, root_relative_squared_error: 1.2503, scimark_benchmark: 916.8516,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6405, build_cpu_time: 0.0119, build_memory: 342489617.6552, f_measure: 0.6424, kappa: 0.2905, kb_relative_information_score: 24.4423, mean_absolute_error: 0.3599, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6495, predictive_accuracy: 0.6437, prior_entropy: 0.9992, recall: 0.6437, relative_absolute_error: 0.7206, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5896, root_relative_squared_error: 1.1799, scimark_benchmark: 937.6343,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6405, build_cpu_time: 0.0554, build_memory: 646961048, f_measure: 0.6424, kappa: 0.2905, kb_relative_information_score: 24.4423, mean_absolute_error: 0.3599, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6495, predictive_accuracy: 0.6437, prior_entropy: 0.9992, recall: 0.6437, relative_absolute_error: 0.7206, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5896, root_relative_squared_error: 1.1799, scimark_benchmark: 907.4175,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7429, build_cpu_time: 0.0324, build_memory: 130944900.9655, f_measure: 0.6428, kappa: 0.2848, kb_relative_information_score: 25.4812, mean_absolute_error: 0.3524, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6435, predictive_accuracy: 0.6437, prior_entropy: 0.9992, recall: 0.6437, relative_absolute_error: 0.7057, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5444, root_relative_squared_error: 1.0895, scimark_benchmark: 942.3919,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6926, build_cpu_time: 0.3056, build_memory: 1655371105.4713, f_measure: 0.6428, kappa: 0.2848, kb_relative_information_score: 25.2775, mean_absolute_error: 0.3534, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6435, predictive_accuracy: 0.6437, prior_entropy: 0.9992, recall: 0.6437, relative_absolute_error: 0.7077, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5913, root_relative_squared_error: 1.1833, scimark_benchmark: 933.4498,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7291, build_cpu_time: 0.19, build_memory: 871910730.7586, f_measure: 0.712, kappa: 0.4232, kb_relative_information_score: 35.1794, mean_absolute_error: 0.2978, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.713, predictive_accuracy: 0.7126, prior_entropy: 0.9992, recall: 0.7126, relative_absolute_error: 0.5962, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5306, root_relative_squared_error: 1.0619, scimark_benchmark: 940.9619,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7267, build_cpu_time: 0.1218, build_memory: 1853822573.7012, f_measure: 0.7, kappa: 0.3997, kb_relative_information_score: 31.8579, mean_absolute_error: 0.3196, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.7019, predictive_accuracy: 0.7011, prior_entropy: 0.9992, recall: 0.7011, relative_absolute_error: 0.64, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5371, root_relative_squared_error: 1.0748, scimark_benchmark: 932.084,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6939, build_cpu_time: 0.0416, build_memory: 1216657530.2989, f_measure: 0.6093, kappa: 0.2187, kb_relative_information_score: 19.7709, mean_absolute_error: 0.3844, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.61, predictive_accuracy: 0.6092, prior_entropy: 0.9992, recall: 0.6092, relative_absolute_error: 0.7698, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5816, root_relative_squared_error: 1.1638, scimark_benchmark: 937.4026,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5079, build_cpu_time: 0.0312, build_memory: 77668454.6207, f_measure: 0.4015, kappa: 0.0154, kb_relative_information_score: -1.1477, mean_absolute_error: 0.5057, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.5225, predictive_accuracy: 0.4943, prior_entropy: 0.9992, recall: 0.4943, relative_absolute_error: 1.0127, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.7112, root_relative_squared_error: 1.4232, scimark_benchmark: 924.2934,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7164, build_cpu_time: 0.0483, build_memory: 118583713.2874, f_measure: 0.6539, kappa: 0.3073, kb_relative_information_score: 28.9299, mean_absolute_error: 0.3324, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6554, predictive_accuracy: 0.6552, prior_entropy: 0.9992, recall: 0.6552, relative_absolute_error: 0.6656, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5582, root_relative_squared_error: 1.1171, scimark_benchmark: 902.0906,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7704, build_cpu_time: 0.0011, build_memory: 466014183.3563, f_measure: 0.7012, kappa: 0.4025, kb_relative_information_score: 31.3456, mean_absolute_error: 0.3249, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.702, predictive_accuracy: 0.7011, prior_entropy: 0.9992, recall: 0.7011, relative_absolute_error: 0.6505, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4488, root_relative_squared_error: 0.8982, scimark_benchmark: 913.4921,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7751, build_cpu_time: 0.0257, build_memory: 150298537.8391, f_measure: 0.6308, kappa: 0.2611, kb_relative_information_score: 26.1272, mean_absolute_error: 0.357, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6321, predictive_accuracy: 0.6322, prior_entropy: 0.9992, recall: 0.6322, relative_absolute_error: 0.7149, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4327, root_relative_squared_error: 0.8659, scimark_benchmark: 937.1859,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6791, build_cpu_time: 0.002, build_memory: 1153669980.7816, f_measure: 0.6744, kappa: 0.3514, kb_relative_information_score: 22.671, mean_absolute_error: 0.3795, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6823, predictive_accuracy: 0.6782, prior_entropy: 0.9992, recall: 0.6782, relative_absolute_error: 0.7598, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4852, root_relative_squared_error: 0.9711, scimark_benchmark: 936.8525,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6405, build_cpu_time: 0.0002, build_memory: 198826056.5517, f_measure: 0.6424, kappa: 0.2905, kb_relative_information_score: 24.4423, mean_absolute_error: 0.3599, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6495, predictive_accuracy: 0.6437, prior_entropy: 0.9992, recall: 0.6437, relative_absolute_error: 0.7206, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5896, root_relative_squared_error: 1.1799, scimark_benchmark: 936.8995,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, build_cpu_time: 0.0053, build_memory: 1009577670.3448, f_measure: 0.3527, kb_relative_information_score: 2.8589, mean_absolute_error: 0.4828, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.2675, predictive_accuracy: 0.5172, prior_entropy: 0.9992, recall: 0.5172, relative_absolute_error: 0.9666, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.6948, root_relative_squared_error: 1.3904, scimark_benchmark: 940.4464,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7452, build_cpu_time: 0.004, build_memory: 171307470.069, f_measure: 0.7462, kappa: 0.492, kb_relative_information_score: 42.9245, mean_absolute_error: 0.2529, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.7484, predictive_accuracy: 0.7471, prior_entropy: 0.9992, recall: 0.7471, relative_absolute_error: 0.5063, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5029, root_relative_squared_error: 1.0063, scimark_benchmark: 943.1817,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7016, build_cpu_time: 0.005, build_memory: 967103080, f_measure: 0.7012, kappa: 0.4025, kb_relative_information_score: 34.9114, mean_absolute_error: 0.2989, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.702, predictive_accuracy: 0.7011, prior_entropy: 0.9992, recall: 0.7011, relative_absolute_error: 0.5984, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5467, root_relative_squared_error: 1.094, scimark_benchmark: 945.1738,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7534, build_cpu_time: 0.0015, build_memory: 132592321.931, f_measure: 0.6897, kappa: 0.3791, kb_relative_information_score: 24.83, mean_absolute_error: 0.3653, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.69, predictive_accuracy: 0.6897, prior_entropy: 0.9992, recall: 0.6897, relative_absolute_error: 0.7315, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4609, root_relative_squared_error: 0.9223, scimark_benchmark: 943.1817,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7778, build_cpu_time: 0.0044, build_memory: 95151880.7356, f_measure: 0.6777, kappa: 0.3545, kb_relative_information_score: 29.8425, mean_absolute_error: 0.3299, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.678, predictive_accuracy: 0.6782, prior_entropy: 0.9992, recall: 0.6782, relative_absolute_error: 0.6606, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4596, root_relative_squared_error: 0.9197, scimark_benchmark: 934.4754,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7778, build_cpu_time: 0.004, build_memory: 78987322.2989, f_measure: 0.6777, kappa: 0.3545, kb_relative_information_score: 29.8425, mean_absolute_error: 0.3299, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.678, predictive_accuracy: 0.6782, prior_entropy: 0.9992, recall: 0.6782, relative_absolute_error: 0.6606, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4596, root_relative_squared_error: 0.9197, scimark_benchmark: 945.1122,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5722, build_cpu_time: 0.0005, build_memory: 505573144, f_measure: 0.5724, kappa: 0.145, kb_relative_information_score: 12.8753, mean_absolute_error: 0.4253, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.574, predictive_accuracy: 0.5747, prior_entropy: 0.9992, recall: 0.5747, relative_absolute_error: 0.8516, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.6521, root_relative_squared_error: 1.3051, scimark_benchmark: 946.8522,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6706, build_cpu_time: 0.0011, build_memory: 364022346.3908, f_measure: 0.6539, kappa: 0.3073, kb_relative_information_score: 24.8191, mean_absolute_error: 0.3593, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6554, predictive_accuracy: 0.6552, prior_entropy: 0.9992, recall: 0.6552, relative_absolute_error: 0.7194, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5512, root_relative_squared_error: 1.103, scimark_benchmark: 922.5645,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7061, build_cpu_time: 0.053, build_memory: 1410865144.8276, f_measure: 0.6774, kappa: 0.3586, kb_relative_information_score: 23.3427, mean_absolute_error: 0.3713, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6831, predictive_accuracy: 0.6782, prior_entropy: 0.9992, recall: 0.6782, relative_absolute_error: 0.7434, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.5062, root_relative_squared_error: 1.0129, scimark_benchmark: 933.5169,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7767, build_cpu_time: 0.2882, build_memory: 1361111019.2184, f_measure: 0.688, kappa: 0.3761, kb_relative_information_score: 25.5366, mean_absolute_error: 0.3637, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.691, predictive_accuracy: 0.6897, prior_entropy: 0.9992, recall: 0.6897, relative_absolute_error: 0.7283, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4313, root_relative_squared_error: 0.8631, scimark_benchmark: 940.5113,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.791, build_cpu_time: 0.0839, build_memory: 268346996.2299, f_measure: 0.6552, kappa: 0.3095, kb_relative_information_score: 26.9629, mean_absolute_error: 0.3512, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6552, predictive_accuracy: 0.6552, prior_entropy: 0.9992, recall: 0.6552, relative_absolute_error: 0.7031, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4337, root_relative_squared_error: 0.8679, scimark_benchmark: 940.204,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7862, build_cpu_time: 0.0698, build_memory: 2882547988.5058, f_measure: 0.6665, kappa: 0.332, kb_relative_information_score: 27.0696, mean_absolute_error: 0.3508, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6665, predictive_accuracy: 0.6667, prior_entropy: 0.9992, recall: 0.6667, relative_absolute_error: 0.7025, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4338, root_relative_squared_error: 0.8682, scimark_benchmark: 943.0533,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7963, build_cpu_time: 0.0341, build_memory: 150162011.8621, f_measure: 0.6665, kappa: 0.332, kb_relative_information_score: 27.9418, mean_absolute_error: 0.3474, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.6665, predictive_accuracy: 0.6667, prior_entropy: 0.9992, recall: 0.6667, relative_absolute_error: 0.6955, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4268, root_relative_squared_error: 0.8541, scimark_benchmark: 947.5139,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8016, build_cpu_time: 0.0117, build_memory: 1630766160.5517, f_measure: 0.7355, kappa: 0.4702, kb_relative_information_score: 29.5097, mean_absolute_error: 0.3397, mean_prior_absolute_error: 0.4994, number_of_instances: 87, precision: 0.7355, predictive_accuracy: 0.7356, prior_entropy: 0.9992, recall: 0.7356, relative_absolute_error: 0.6803, root_mean_prior_squared_error: 0.4997, root_mean_squared_error: 0.4229, root_relative_squared_error: 0.8463, scimark_benchmark: 943.7335,

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