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OpenML
Task
Supervised Classification on squash-unstored

Supervised Classification on squash-unstored

Task 3848 Supervised Classification squash-unstored 496 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_107 study_15 study_20 study_41 under100k under1m
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Metric:

496 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7143, f_measure: 0.6538, kappa: 0.3118, kb_relative_information_score: 12.0414, mean_absolute_error: 0.3862, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.6616, predictive_accuracy: 0.6538, prior_entropy: 0.996, recall: 0.6538, relative_absolute_error: 0.7769, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4793, root_relative_squared_error: 0.9614, scimark_benchmark: 854.5188,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5893, f_measure: 0.593, kappa: 0.1802, kb_relative_information_score: 9.6497, mean_absolute_error: 0.4038, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.5938, predictive_accuracy: 0.5962, prior_entropy: 0.996, recall: 0.5962, relative_absolute_error: 0.8123, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.6355, root_relative_squared_error: 1.2748, scimark_benchmark: 940.3347, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3769, kb_relative_information_score: 3.6019, mean_absolute_error: 0.4615, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.2899, predictive_accuracy: 0.5385, prior_entropy: 0.996, recall: 0.5385, relative_absolute_error: 0.9284, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.6794, root_relative_squared_error: 1.3628, scimark_benchmark: 869.6028, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7083, f_measure: 0.711, kappa: 0.4179, kb_relative_information_score: 21.7452, mean_absolute_error: 0.2885, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.711, predictive_accuracy: 0.7115, prior_entropy: 0.996, recall: 0.7115, relative_absolute_error: 0.5802, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.5371, root_relative_squared_error: 1.0774, scimark_benchmark: 1337.7959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6875, f_measure: 0.6725, kappa: 0.3403, kb_relative_information_score: 12.6817, mean_absolute_error: 0.3834, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.6724, predictive_accuracy: 0.6731, prior_entropy: 0.996, recall: 0.6731, relative_absolute_error: 0.7712, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4973, root_relative_squared_error: 0.9975, scimark_benchmark: 942.9708, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6548, f_measure: 0.6544, kappa: 0.3077, kb_relative_information_score: 15.6974, mean_absolute_error: 0.3462, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.6568, predictive_accuracy: 0.6538, prior_entropy: 0.996, recall: 0.6538, relative_absolute_error: 0.6963, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.5883, root_relative_squared_error: 1.1802, scimark_benchmark: 942.6843, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8869, f_measure: 0.7503, kappa: 0.4985, kb_relative_information_score: 21.4309, mean_absolute_error: 0.3056, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.7511, predictive_accuracy: 0.75, prior_entropy: 0.996, recall: 0.75, relative_absolute_error: 0.6147, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.3837, root_relative_squared_error: 0.7697, scimark_benchmark: 908.2231, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.3769, kb_relative_information_score: 3.6019, mean_absolute_error: 0.4615, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.2899, predictive_accuracy: 0.5385, prior_entropy: 0.996, recall: 0.5385, relative_absolute_error: 0.9284, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.6794, root_relative_squared_error: 1.3628, scimark_benchmark: 934.0566, usercpu_time_millis: 10, usercpu_time_millis_testing: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.75, f_measure: 0.7503, kappa: 0.5015, kb_relative_information_score: 19.8046, mean_absolute_error: 0.3159, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.7556, predictive_accuracy: 0.75, prior_entropy: 0.996, recall: 0.75, relative_absolute_error: 0.6355, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4731, root_relative_squared_error: 0.949, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7649, f_measure: 0.6523, kappa: 0.3158, kb_relative_information_score: 17.0352, mean_absolute_error: 0.3345, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.6685, predictive_accuracy: 0.6538, prior_entropy: 0.996, recall: 0.6538, relative_absolute_error: 0.6728, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4829, root_relative_squared_error: 0.9687, scimark_benchmark: 918.6491, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7515, f_measure: 0.6523, kappa: 0.3158, kb_relative_information_score: 16.5951, mean_absolute_error: 0.3388, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.6685, predictive_accuracy: 0.6538, prior_entropy: 0.996, recall: 0.6538, relative_absolute_error: 0.6814, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4916, root_relative_squared_error: 0.9861, scimark_benchmark: 930.067,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7537, f_measure: 0.7119, kappa: 0.4214, kb_relative_information_score: 17.4884, mean_absolute_error: 0.3332, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.7127, predictive_accuracy: 0.7115, prior_entropy: 0.996, recall: 0.7115, relative_absolute_error: 0.6703, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4921, root_relative_squared_error: 0.9872, scimark_benchmark: 910.6151, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8586, f_measure: 0.8077, kappa: 0.6131, kb_relative_information_score: 14.76, mean_absolute_error: 0.3772, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.8077, predictive_accuracy: 0.8077, prior_entropy: 0.996, recall: 0.8077, relative_absolute_error: 0.7587, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4089, root_relative_squared_error: 0.8202, scimark_benchmark: 1307.4861, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5751, f_measure: 0.593, kappa: 0.2041, kb_relative_information_score: 7.8838, mean_absolute_error: 0.4245, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.6121, predictive_accuracy: 0.5962, prior_entropy: 0.996, recall: 0.5962, relative_absolute_error: 0.8538, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.604, root_relative_squared_error: 1.2117, scimark_benchmark: 1346.9602,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4196, f_measure: 0.3769, kb_relative_information_score: -0.1815, mean_absolute_error: 0.4984, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.2899, predictive_accuracy: 0.5385, prior_entropy: 0.996, recall: 0.5385, relative_absolute_error: 1.0024, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4999, root_relative_squared_error: 1.0028, scimark_benchmark: 1361.1055,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6845, f_measure: 0.7296, kappa: 0.4551, kb_relative_information_score: 20.262, mean_absolute_error: 0.3111, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.7305, predictive_accuracy: 0.7308, prior_entropy: 0.996, recall: 0.7308, relative_absolute_error: 0.6258, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.5022, root_relative_squared_error: 1.0074, scimark_benchmark: 1309.3173, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5952, f_measure: 0.5966, kappa: 0.1899, kb_relative_information_score: 9.6497, mean_absolute_error: 0.4038, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.5975, predictive_accuracy: 0.5962, prior_entropy: 0.996, recall: 0.5962, relative_absolute_error: 0.8123, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.6355, root_relative_squared_error: 1.2748, scimark_benchmark: 1292.2426, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, f_measure: 0.2915, kb_relative_information_score: -4.4618, mean_absolute_error: 0.5385, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.213, predictive_accuracy: 0.4615, prior_entropy: 0.996, recall: 0.4615, relative_absolute_error: 1.0831, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.7338, root_relative_squared_error: 1.472, scimark_benchmark: 1280.6952,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7128, f_measure: 0.7296, kappa: 0.4551, kb_relative_information_score: 19.7226, mean_absolute_error: 0.3142, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.7305, predictive_accuracy: 0.7308, prior_entropy: 0.996, recall: 0.7308, relative_absolute_error: 0.6321, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4916, root_relative_squared_error: 0.9862, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5774, f_measure: 0.5776, kappa: 0.1538, kb_relative_information_score: 7.6337, mean_absolute_error: 0.4231, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.5799, predictive_accuracy: 0.5769, prior_entropy: 0.996, recall: 0.5769, relative_absolute_error: 0.851, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.6504, root_relative_squared_error: 1.3047, scimark_benchmark: 1465.2979,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6964, f_measure: 0.6923, kappa: 0.3882, kb_relative_information_score: 19.7293, mean_absolute_error: 0.3077, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.7005, predictive_accuracy: 0.6923, prior_entropy: 0.996, recall: 0.6923, relative_absolute_error: 0.6189, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.5547, root_relative_squared_error: 1.1127, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4196, f_measure: 0.3769, kb_relative_information_score: -0.1942, mean_absolute_error: 0.4984, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.2899, predictive_accuracy: 0.5385, prior_entropy: 0.996, recall: 0.5385, relative_absolute_error: 1.0026, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4999, root_relative_squared_error: 1.0027, scimark_benchmark: 1505.597,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7046, f_measure: 0.748, kappa: 0.4925, kb_relative_information_score: 21.1144, mean_absolute_error: 0.3033, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.7512, predictive_accuracy: 0.75, prior_entropy: 0.996, recall: 0.75, relative_absolute_error: 0.61, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4778, root_relative_squared_error: 0.9584, scimark_benchmark: 1465.2979, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8348, f_measure: 0.7495, kappa: 0.4955, kb_relative_information_score: 24.6798, mean_absolute_error: 0.2624, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.7496, predictive_accuracy: 0.75, prior_entropy: 0.996, recall: 0.75, relative_absolute_error: 0.5279, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4616, root_relative_squared_error: 0.926, scimark_benchmark: 927.0753, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8438, f_measure: 0.7495, kappa: 0.4955, kb_relative_information_score: 25.5639, mean_absolute_error: 0.2527, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.7496, predictive_accuracy: 0.75, prior_entropy: 0.996, recall: 0.75, relative_absolute_error: 0.5083, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4776, root_relative_squared_error: 0.9581, scimark_benchmark: 941.7954, usercpu_time_millis: 90, usercpu_time_millis_testing: 30, usercpu_time_millis_training: 60,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8266, f_measure: 0.8068, kappa: 0.6108, kb_relative_information_score: 30.1544, mean_absolute_error: 0.2111, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.8084, predictive_accuracy: 0.8077, prior_entropy: 0.996, recall: 0.8077, relative_absolute_error: 0.4246, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4336, root_relative_squared_error: 0.8698, scimark_benchmark: 945.6434, usercpu_time_millis: 120, usercpu_time_millis_testing: 40, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7961, f_measure: 0.7495, kappa: 0.4955, kb_relative_information_score: 26.5042, mean_absolute_error: 0.2423, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.7496, predictive_accuracy: 0.75, prior_entropy: 0.996, recall: 0.75, relative_absolute_error: 0.4874, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4743, root_relative_squared_error: 0.9514, scimark_benchmark: 894.7455, usercpu_time_millis: 340, usercpu_time_millis_testing: 100, usercpu_time_millis_training: 240,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8698, f_measure: 0.8068, kappa: 0.6108, kb_relative_information_score: 32.0002, mean_absolute_error: 0.19, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.8084, predictive_accuracy: 0.8077, prior_entropy: 0.996, recall: 0.8077, relative_absolute_error: 0.3823, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4334, root_relative_squared_error: 0.8694, scimark_benchmark: 936.7115, usercpu_time_millis: 70, usercpu_time_millis_training: 70,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8765, f_measure: 0.8068, kappa: 0.6108, kb_relative_information_score: 31.8746, mean_absolute_error: 0.1917, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.8084, predictive_accuracy: 0.8077, prior_entropy: 0.996, recall: 0.8077, relative_absolute_error: 0.3855, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4365, root_relative_squared_error: 0.8756, scimark_benchmark: 938.2848, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8579, f_measure: 0.7881, kappa: 0.5731, kb_relative_information_score: 29.8095, mean_absolute_error: 0.2104, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.7883, predictive_accuracy: 0.7885, prior_entropy: 0.996, recall: 0.7885, relative_absolute_error: 0.4233, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4446, root_relative_squared_error: 0.8918, scimark_benchmark: 942.1229, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8065, f_measure: 0.7881, kappa: 0.5731, kb_relative_information_score: 29.0784, mean_absolute_error: 0.2205, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.7883, predictive_accuracy: 0.7885, prior_entropy: 0.996, recall: 0.7885, relative_absolute_error: 0.4435, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4467, root_relative_squared_error: 0.896, scimark_benchmark: 922.9039, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7522, f_measure: 0.7308, kappa: 0.4647, kb_relative_information_score: 21.9045, mean_absolute_error: 0.2904, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.7395, predictive_accuracy: 0.7308, prior_entropy: 0.996, recall: 0.7308, relative_absolute_error: 0.5841, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.5009, root_relative_squared_error: 1.0049, scimark_benchmark: 938.9865,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8735, f_measure: 0.8455, kappa: 0.6886, kb_relative_information_score: 34.6928, mean_absolute_error: 0.1672, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.8473, predictive_accuracy: 0.8462, prior_entropy: 0.996, recall: 0.8462, relative_absolute_error: 0.3364, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.3894, root_relative_squared_error: 0.781, scimark_benchmark: 938.4285, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8542, f_measure: 0.8077, kappa: 0.6131, kb_relative_information_score: 29.9604, mean_absolute_error: 0.2147, mean_prior_absolute_error: 0.4972, number_of_instances: 52, precision: 0.8077, predictive_accuracy: 0.8077, prior_entropy: 0.996, recall: 0.8077, relative_absolute_error: 0.4319, root_mean_prior_squared_error: 0.4985, root_mean_squared_error: 0.4015, root_relative_squared_error: 0.8054, scimark_benchmark: 932.3943,
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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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