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File: /var/www/openml/index.php
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Function: require_once

OpenML
Task
Supervised Classification on soybean

Supervised Classification on soybean

Task 271 Supervised Classification soybean 321 runs submitted
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321 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9795, f_measure: 0.8855, kappa: 0.8864, kb_relative_information_score: 197.9127, mean_absolute_error: 0.0157, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.9144, predictive_accuracy: 0.8978, prior_entropy: 3.8572, recall: 0.8978, relative_absolute_error: 0.164, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0888, root_relative_squared_error: 0.4064, scimark_benchmark: 882.7843, usercpu_time_millis: 130, usercpu_time_millis_testing: 130,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9699, f_measure: 0.805, kappa: 0.8169, kb_relative_information_score: 37.3793, mean_absolute_error: 0.0945, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.8051, predictive_accuracy: 0.8356, prior_entropy: 3.8572, recall: 0.8356, relative_absolute_error: 0.9858, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.2136, root_relative_squared_error: 0.9776, scimark_benchmark: 912.5006, usercpu_time_millis: 3370, usercpu_time_millis_testing: 2510, usercpu_time_millis_training: 860,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9854, f_measure: 0.9224, kappa: 0.9163, kb_relative_information_score: 39.1825, mean_absolute_error: 0.0942, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.9243, predictive_accuracy: 0.9244, prior_entropy: 3.8572, recall: 0.9244, relative_absolute_error: 0.9834, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.213, root_relative_squared_error: 0.975, scimark_benchmark: 1369.9744, usercpu_time_millis: 820, usercpu_time_millis_testing: 50, usercpu_time_millis_training: 770,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9949, f_measure: 0.9328, kappa: 0.9262, kb_relative_information_score: 208.6289, mean_absolute_error: 0.0083, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.934, predictive_accuracy: 0.9333, prior_entropy: 3.8572, recall: 0.9333, relative_absolute_error: 0.0865, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0706, root_relative_squared_error: 0.3229, scimark_benchmark: 1363.434, usercpu_time_millis: 2370, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 2360,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.959, f_measure: 0.9266, kappa: 0.9212, kb_relative_information_score: 204.603, mean_absolute_error: 0.0075, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.9325, predictive_accuracy: 0.9289, prior_entropy: 3.8572, recall: 0.9289, relative_absolute_error: 0.0781, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0865, root_relative_squared_error: 0.396, scimark_benchmark: 939.449, usercpu_time_millis: 90, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9867, f_measure: 0.9281, kappa: 0.9214, kb_relative_information_score: 205.7326, mean_absolute_error: 0.0082, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.9323, predictive_accuracy: 0.9289, prior_entropy: 3.8572, recall: 0.9289, relative_absolute_error: 0.0854, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0838, root_relative_squared_error: 0.3836, scimark_benchmark: 1319.5177, usercpu_time_millis: 15750, usercpu_time_millis_testing: 1260, usercpu_time_millis_training: 14490,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9952, f_measure: 0.8837, kappa: 0.8815, kb_relative_information_score: 186.9179, mean_absolute_error: 0.0286, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.9044, predictive_accuracy: 0.8933, prior_entropy: 3.8572, recall: 0.8933, relative_absolute_error: 0.2987, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0968, root_relative_squared_error: 0.443, scimark_benchmark: 1346.9602, usercpu_time_millis: 660, usercpu_time_millis_testing: 210, usercpu_time_millis_training: 450,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.854, f_measure: 0.6891, kappa: 0.6663, kb_relative_information_score: 148.7266, mean_absolute_error: 0.0339, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.718, predictive_accuracy: 0.6978, prior_entropy: 3.8572, recall: 0.6978, relative_absolute_error: 0.3538, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.1692, root_relative_squared_error: 0.7745, scimark_benchmark: 1301.9956, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9478, f_measure: 0.7133, kappa: 0.7221, kb_relative_information_score: 164.2191, mean_absolute_error: 0.0363, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.7372, predictive_accuracy: 0.7511, prior_entropy: 3.8572, recall: 0.7511, relative_absolute_error: 0.3787, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.1344, root_relative_squared_error: 0.6151, scimark_benchmark: 1319.9043, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9805, f_measure: 0.9198, kappa: 0.9163, kb_relative_information_score: 202.7977, mean_absolute_error: 0.0125, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.919, predictive_accuracy: 0.9244, prior_entropy: 3.8572, recall: 0.9244, relative_absolute_error: 0.13, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0851, root_relative_squared_error: 0.3895, scimark_benchmark: 1354.2491, usercpu_time_millis: 2380, usercpu_time_millis_training: 2380,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9325, f_measure: 0.8764, kappa: 0.8716, kb_relative_information_score: 194.9429, mean_absolute_error: 0.0122, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.8819, predictive_accuracy: 0.8844, prior_entropy: 3.8572, recall: 0.8844, relative_absolute_error: 0.1269, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.1103, root_relative_squared_error: 0.5049, scimark_benchmark: 1442.7264, usercpu_time_millis: 80, usercpu_time_millis_testing: 20, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6793, f_measure: 0.4559, kappa: 0.3413, kb_relative_information_score: 75.3018, mean_absolute_error: 0.065, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.7605, predictive_accuracy: 0.3822, prior_entropy: 3.8572, recall: 0.3822, relative_absolute_error: 0.6786, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.255, root_relative_squared_error: 1.1673, scimark_benchmark: 1368.9272, usercpu_time_millis: 40, usercpu_time_millis_training: 40,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9837, f_measure: 0.8891, kappa: 0.8817, kb_relative_information_score: 196.3303, mean_absolute_error: 0.0168, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.8985, predictive_accuracy: 0.8933, prior_entropy: 3.8572, recall: 0.8933, relative_absolute_error: 0.175, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0926, root_relative_squared_error: 0.4239, scimark_benchmark: 1341.2341, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6573, f_measure: 0.2948, kappa: 0.3148, kb_relative_information_score: 69.1543, mean_absolute_error: 0.0641, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.283, predictive_accuracy: 0.3911, prior_entropy: 3.8572, recall: 0.3911, relative_absolute_error: 0.6688, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.2532, root_relative_squared_error: 1.1589, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9229, f_measure: 0.8586, kappa: 0.8518, kb_relative_information_score: 190.2257, mean_absolute_error: 0.014, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.8694, predictive_accuracy: 0.8667, prior_entropy: 3.8572, recall: 0.8667, relative_absolute_error: 0.1465, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.1185, root_relative_squared_error: 0.5423, scimark_benchmark: 1028.5889, usercpu_time_millis: 1160, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 1150,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.0257, kb_relative_information_score: 1.5735, mean_absolute_error: 0.0961, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.0144, predictive_accuracy: 0.12, prior_entropy: 3.8572, recall: 0.12, relative_absolute_error: 1.0032, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.2188, root_relative_squared_error: 1.0016, scimark_benchmark: 1054.3694,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.992, f_measure: 0.8595, kappa: 0.8521, kb_relative_information_score: 194.3125, mean_absolute_error: 0.0163, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.8653, predictive_accuracy: 0.8667, prior_entropy: 3.8572, recall: 0.8667, relative_absolute_error: 0.1705, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0974, root_relative_squared_error: 0.4459, scimark_benchmark: 977.6382, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.961, build_cpu_time: 68.72, build_memory: 1549401912, f_measure: 0.9287, kappa: 0.9213, kb_relative_information_score: 204.994, mean_absolute_error: 0.0076, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.9318, predictive_accuracy: 0.9289, prior_entropy: 3.8572, recall: 0.9289, relative_absolute_error: 0.0795, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0866, root_relative_squared_error: 0.3966, scimark_benchmark: 940.9906,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9585, build_cpu_time: 34.251, build_memory: 878141976, f_measure: 0.91, kappa: 0.9015, kb_relative_information_score: 201.2194, mean_absolute_error: 0.0095, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.913, predictive_accuracy: 0.9111, prior_entropy: 3.8572, recall: 0.9111, relative_absolute_error: 0.0991, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0968, root_relative_squared_error: 0.4431, scimark_benchmark: 940.5101,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9632, build_cpu_time: 20.957, build_memory: 257718912, f_measure: 0.9084, kappa: 0.9015, kb_relative_information_score: 202.4128, mean_absolute_error: 0.009, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.9124, predictive_accuracy: 0.9111, prior_entropy: 3.8572, recall: 0.9111, relative_absolute_error: 0.0938, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0932, root_relative_squared_error: 0.4268, scimark_benchmark: 937.3768,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9741, build_cpu_time: 9.255, build_memory: 601198528, f_measure: 0.914, kappa: 0.9064, kb_relative_information_score: 202.3037, mean_absolute_error: 0.0088, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.9167, predictive_accuracy: 0.9156, prior_entropy: 3.8572, recall: 0.9156, relative_absolute_error: 0.0915, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0923, root_relative_squared_error: 0.4224, scimark_benchmark: 940.572,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9924, build_cpu_time: 0.078, build_memory: 743102016, f_measure: 0.891, kappa: 0.8817, kb_relative_information_score: 196.882, mean_absolute_error: 0.0161, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.8974, predictive_accuracy: 0.8933, prior_entropy: 3.8572, recall: 0.8933, relative_absolute_error: 0.168, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0889, root_relative_squared_error: 0.4067, scimark_benchmark: 940.5101,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9924, build_cpu_time: 0.08, build_memory: 902748504, f_measure: 0.891, kappa: 0.8817, kb_relative_information_score: 196.882, mean_absolute_error: 0.0161, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.8974, predictive_accuracy: 0.8933, prior_entropy: 3.8572, recall: 0.8933, relative_absolute_error: 0.168, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0889, root_relative_squared_error: 0.4067, scimark_benchmark: 926.4124,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9924, build_cpu_time: 0.088, build_memory: 999457336, f_measure: 0.891, kappa: 0.8817, kb_relative_information_score: 196.882, mean_absolute_error: 0.0161, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.8974, predictive_accuracy: 0.8933, prior_entropy: 3.8572, recall: 0.8933, relative_absolute_error: 0.168, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0889, root_relative_squared_error: 0.4067, scimark_benchmark: 932.9956,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9924, build_cpu_time: 0.081, build_memory: 1500338704, f_measure: 0.891, kappa: 0.8817, kb_relative_information_score: 196.882, mean_absolute_error: 0.0161, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.8974, predictive_accuracy: 0.8933, prior_entropy: 3.8572, recall: 0.8933, relative_absolute_error: 0.168, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0889, root_relative_squared_error: 0.4067, scimark_benchmark: 915.3856,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9924, build_cpu_time: 0.169, build_memory: 39593432, f_measure: 0.891, kappa: 0.8817, kb_relative_information_score: 196.882, mean_absolute_error: 0.0161, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.8974, predictive_accuracy: 0.8933, prior_entropy: 3.8572, recall: 0.8933, relative_absolute_error: 0.168, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0889, root_relative_squared_error: 0.4067, scimark_benchmark: 920.993,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9194, build_cpu_time: 0.008, build_memory: 322007824, f_measure: 0.8482, kappa: 0.8234, kb_relative_information_score: 181.9002, mean_absolute_error: 0.0197, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.8724, predictive_accuracy: 0.84, prior_entropy: 3.8572, recall: 0.84, relative_absolute_error: 0.2057, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.1288, root_relative_squared_error: 0.5895, scimark_benchmark: 916.3022,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9194, build_cpu_time: 0.01, build_memory: 2216342040, f_measure: 0.8482, kappa: 0.8234, kb_relative_information_score: 181.9002, mean_absolute_error: 0.0197, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.8724, predictive_accuracy: 0.84, prior_entropy: 3.8572, recall: 0.84, relative_absolute_error: 0.2057, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.1288, root_relative_squared_error: 0.5895, scimark_benchmark: 934.6076,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9955, build_cpu_time: 0.328, build_memory: 1356157984, f_measure: 0.8878, kappa: 0.8817, kb_relative_information_score: 187.6786, mean_absolute_error: 0.0279, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.8958, predictive_accuracy: 0.8933, prior_entropy: 3.8572, recall: 0.8933, relative_absolute_error: 0.2911, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0965, root_relative_squared_error: 0.4416, scimark_benchmark: 939.9709,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.996, build_memory: 739458088, f_measure: 0.9154, kappa: 0.9066, kb_relative_information_score: 205.1039, mean_absolute_error: 0.0101, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.9305, predictive_accuracy: 0.9156, prior_entropy: 3.8572, recall: 0.9156, relative_absolute_error: 0.1052, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.0811, root_relative_squared_error: 0.3714, scimark_benchmark: 940.7816,
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9928, build_cpu_time: 95.114, build_memory: 1398128600, f_measure: 0.8929, kappa: 0.8964, kb_relative_information_score: 38.9696, mean_absolute_error: 0.0943, mean_prior_absolute_error: 0.0958, number_of_instances: 225, precision: 0.9138, predictive_accuracy: 0.9067, prior_entropy: 3.8572, recall: 0.9067, relative_absolute_error: 0.9837, root_mean_prior_squared_error: 0.2185, root_mean_squared_error: 0.213, root_relative_squared_error: 0.9752, scimark_benchmark: 944.9156,
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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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