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OpenML
Task
Supervised Classification on echoMonths

Supervised Classification on echoMonths

Task 3807 Supervised Classification echoMonths 519 runs submitted
0 likes downloaded by 0 people , 0 total downloads 0 issues
Visibility: Public
  • mythbusting_1 study_1 study_107 study_123 study_15 study_20 study_41 under100k under1m
Issue #Downvotes for this reason By


Metric:

519 Runs

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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7744, f_measure: 0.7227, kappa: 0.4455, kb_relative_information_score: 51.3249, mean_absolute_error: 0.3062, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7237, predictive_accuracy: 0.7231, prior_entropy: 0.9998, recall: 0.7231, relative_absolute_error: 0.6126, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4551, root_relative_squared_error: 0.9102, scimark_benchmark: 1324.8395,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7292, f_measure: 0.7276, kappa: 0.4597, kb_relative_information_score: 59.9761, mean_absolute_error: 0.2692, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7396, predictive_accuracy: 0.7308, prior_entropy: 0.9998, recall: 0.7308, relative_absolute_error: 0.5386, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5189, root_relative_squared_error: 1.0379, scimark_benchmark: 1336.3256, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6721, f_measure: 0.6411, kappa: 0.3475, kb_relative_information_score: 45.9715, mean_absolute_error: 0.3231, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7831, predictive_accuracy: 0.6769, prior_entropy: 0.9998, recall: 0.6769, relative_absolute_error: 0.6463, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5684, root_relative_squared_error: 1.1369, scimark_benchmark: 1336.3256, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7973, f_measure: 0.7935, kappa: 0.5978, kb_relative_information_score: 77.9821, mean_absolute_error: 0.2, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.8381, predictive_accuracy: 0.8, prior_entropy: 0.9998, recall: 0.8, relative_absolute_error: 0.4001, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4472, root_relative_squared_error: 0.8945, scimark_benchmark: 1250.8301,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7854, f_measure: 0.7946, kappa: 0.598, kb_relative_information_score: 50.9146, mean_absolute_error: 0.3236, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.8307, predictive_accuracy: 0.8, prior_entropy: 0.9998, recall: 0.8, relative_absolute_error: 0.6473, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3943, root_relative_squared_error: 0.7888, scimark_benchmark: 887.6719, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7595, f_measure: 0.7569, kappa: 0.521, kb_relative_information_score: 67.9788, mean_absolute_error: 0.2385, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7799, predictive_accuracy: 0.7615, prior_entropy: 0.9998, recall: 0.7615, relative_absolute_error: 0.477, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4883, root_relative_squared_error: 0.9768, scimark_benchmark: 942.9708, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7791, f_measure: 0.7809, kappa: 0.5675, kb_relative_information_score: 51.835, mean_absolute_error: 0.3145, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.8023, predictive_accuracy: 0.7846, prior_entropy: 0.9998, recall: 0.7846, relative_absolute_error: 0.6292, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4092, root_relative_squared_error: 0.8186, scimark_benchmark: 1304.6687, usercpu_time_millis: 90, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 80,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6631, f_measure: 0.6581, kappa: 0.3252, kb_relative_information_score: 41.9702, mean_absolute_error: 0.3385, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.6705, predictive_accuracy: 0.6615, prior_entropy: 0.9998, recall: 0.6615, relative_absolute_error: 0.6771, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5818, root_relative_squared_error: 1.1637, scimark_benchmark: 1337.7959, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7594, f_measure: 0.7349, kappa: 0.4751, kb_relative_information_score: 52.457, mean_absolute_error: 0.3088, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7492, predictive_accuracy: 0.7385, prior_entropy: 0.9998, recall: 0.7385, relative_absolute_error: 0.6177, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.431, root_relative_squared_error: 0.8621, scimark_benchmark: 1028.5889,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7357, f_measure: 0.7349, kappa: 0.4751, kb_relative_information_score: 46.4884, mean_absolute_error: 0.3321, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7492, predictive_accuracy: 0.7385, prior_entropy: 0.9998, recall: 0.7385, relative_absolute_error: 0.6643, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4359, root_relative_squared_error: 0.8719, scimark_benchmark: 1368.9272,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7682, f_measure: 0.7579, kappa: 0.5213, kb_relative_information_score: 53.9859, mean_absolute_error: 0.305, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7755, predictive_accuracy: 0.7615, prior_entropy: 0.9998, recall: 0.7615, relative_absolute_error: 0.6101, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4234, root_relative_squared_error: 0.847, scimark_benchmark: 1250.8301, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8333, f_measure: 0.7505, kappa: 0.5059, kb_relative_information_score: 54.6955, mean_absolute_error: 0.3011, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7654, predictive_accuracy: 0.7538, prior_entropy: 0.9998, recall: 0.7538, relative_absolute_error: 0.6023, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3967, root_relative_squared_error: 0.7934, scimark_benchmark: 1331.6907, usercpu_time_millis: 40, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7711, f_measure: 0.7692, kappa: 0.5384, kb_relative_information_score: 66.5114, mean_absolute_error: 0.2458, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7692, predictive_accuracy: 0.7692, prior_entropy: 0.9998, recall: 0.7692, relative_absolute_error: 0.4917, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4822, root_relative_squared_error: 0.9645, scimark_benchmark: 825.5282,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7952, f_measure: 0.7809, kappa: 0.5675, kb_relative_information_score: 58.9389, mean_absolute_error: 0.2869, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.8023, predictive_accuracy: 0.7846, prior_entropy: 0.9998, recall: 0.7846, relative_absolute_error: 0.574, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3968, root_relative_squared_error: 0.7936, scimark_benchmark: 1372.2145,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7648, f_measure: 0.7862, kappa: 0.5824, kb_relative_information_score: 56.5012, mean_absolute_error: 0.2986, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.8256, predictive_accuracy: 0.7923, prior_entropy: 0.9998, recall: 0.7923, relative_absolute_error: 0.5973, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3942, root_relative_squared_error: 0.7885, scimark_benchmark: 1318.1432, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7005, f_measure: 0.6997, kappa: 0.4006, kb_relative_information_score: 51.9735, mean_absolute_error: 0.3, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7015, predictive_accuracy: 0.7, prior_entropy: 0.9998, recall: 0.7, relative_absolute_error: 0.6001, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5477, root_relative_squared_error: 1.0956, scimark_benchmark: 1291.6995,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4979, f_measure: 0.4165, kappa: -0.0042, kb_relative_information_score: -2.0444, mean_absolute_error: 0.5077, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.4956, predictive_accuracy: 0.4923, prior_entropy: 0.9998, recall: 0.4923, relative_absolute_error: 1.0156, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.7125, root_relative_squared_error: 1.4252, scimark_benchmark: 1337.7959,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.83, f_measure: 0.7676, kappa: 0.5373, kb_relative_information_score: 64.9341, mean_absolute_error: 0.2586, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7752, predictive_accuracy: 0.7692, prior_entropy: 0.9998, recall: 0.7692, relative_absolute_error: 0.5174, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.3967, root_relative_squared_error: 0.7936, scimark_benchmark: 1358.4523,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7973, f_measure: 0.7935, kappa: 0.5978, kb_relative_information_score: 77.9821, mean_absolute_error: 0.2, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.8381, predictive_accuracy: 0.8, prior_entropy: 0.9998, recall: 0.8, relative_absolute_error: 0.4001, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4472, root_relative_squared_error: 0.8945, scimark_benchmark: 1351.788,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7827, f_measure: 0.7809, kappa: 0.5675, kb_relative_information_score: 73.9808, mean_absolute_error: 0.2154, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.8023, predictive_accuracy: 0.7846, prior_entropy: 0.9998, recall: 0.7846, relative_absolute_error: 0.4309, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4641, root_relative_squared_error: 0.9283, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.4631, f_measure: 0.3419, kb_relative_information_score: -0.116, mean_absolute_error: 0.5002, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.2578, predictive_accuracy: 0.5077, prior_entropy: 0.9998, recall: 0.5077, relative_absolute_error: 1.0006, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5003, root_relative_squared_error: 1.0007, scimark_benchmark: 1418.5826,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7789, f_measure: 0.7447, kappa: 0.4911, kb_relative_information_score: 57.0477, mean_absolute_error: 0.2898, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7504, predictive_accuracy: 0.7462, prior_entropy: 0.9998, recall: 0.7462, relative_absolute_error: 0.5796, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4315, root_relative_squared_error: 0.8631, scimark_benchmark: 1353.5686,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.773, f_measure: 0.7595, kappa: 0.5217, kb_relative_information_score: 67.9559, mean_absolute_error: 0.2393, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7687, predictive_accuracy: 0.7615, prior_entropy: 0.9998, recall: 0.7615, relative_absolute_error: 0.4787, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4753, root_relative_squared_error: 0.9507, scimark_benchmark: 931.2336, usercpu_time_millis: 20, usercpu_time_millis_testing: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7634, f_measure: 0.775, kappa: 0.5526, kb_relative_information_score: 51.2089, mean_absolute_error: 0.3184, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7845, predictive_accuracy: 0.7769, prior_entropy: 0.9998, recall: 0.7769, relative_absolute_error: 0.6369, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4298, root_relative_squared_error: 0.8597, scimark_benchmark: 941.7954,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7634, f_measure: 0.775, kappa: 0.5526, kb_relative_information_score: 51.2089, mean_absolute_error: 0.3184, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7845, predictive_accuracy: 0.7769, prior_entropy: 0.9998, recall: 0.7769, relative_absolute_error: 0.6369, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4298, root_relative_squared_error: 0.8597, scimark_benchmark: 923.7642,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7634, f_measure: 0.775, kappa: 0.5526, kb_relative_information_score: 51.2089, mean_absolute_error: 0.3184, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7845, predictive_accuracy: 0.7769, prior_entropy: 0.9998, recall: 0.7769, relative_absolute_error: 0.6369, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4298, root_relative_squared_error: 0.8597, scimark_benchmark: 894.7455, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8024, f_measure: 0.7358, kappa: 0.4753, kb_relative_information_score: 61.5428, mean_absolute_error: 0.2635, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7462, predictive_accuracy: 0.7385, prior_entropy: 0.9998, recall: 0.7385, relative_absolute_error: 0.5272, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4862, root_relative_squared_error: 0.9726, scimark_benchmark: 911.3823, usercpu_time_millis: 50, usercpu_time_millis_training: 50,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8107, f_measure: 0.7194, kappa: 0.4442, kb_relative_information_score: 57.908, mean_absolute_error: 0.277, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.733, predictive_accuracy: 0.7231, prior_entropy: 0.9998, recall: 0.7231, relative_absolute_error: 0.5542, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4987, root_relative_squared_error: 0.9976, scimark_benchmark: 943.2817, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8247, f_measure: 0.7558, kappa: 0.5208, kb_relative_information_score: 66.8024, mean_absolute_error: 0.2444, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.785, predictive_accuracy: 0.7615, prior_entropy: 0.9998, recall: 0.7615, relative_absolute_error: 0.4888, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.461, root_relative_squared_error: 0.9222, scimark_benchmark: 911.3823, usercpu_time_millis: 20, usercpu_time_millis_training: 20,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8262, f_measure: 0.7339, kappa: 0.4748, kb_relative_information_score: 65.505, mean_absolute_error: 0.2471, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7529, predictive_accuracy: 0.7385, prior_entropy: 0.9998, recall: 0.7385, relative_absolute_error: 0.4944, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4628, root_relative_squared_error: 0.9256, scimark_benchmark: 934.5243, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8372, f_measure: 0.7935, kappa: 0.5978, kb_relative_information_score: 73.686, mean_absolute_error: 0.2194, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.8381, predictive_accuracy: 0.8, prior_entropy: 0.9998, recall: 0.8, relative_absolute_error: 0.439, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4341, root_relative_squared_error: 0.8683, scimark_benchmark: 938.4285, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7351, f_measure: 0.6769, kappa: 0.3537, kb_relative_information_score: 45.4621, mean_absolute_error: 0.326, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.6769, predictive_accuracy: 0.6769, prior_entropy: 0.9998, recall: 0.6769, relative_absolute_error: 0.6521, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.5194, root_relative_squared_error: 1.0389, scimark_benchmark: 936.6206, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7474, f_measure: 0.6846, kappa: 0.3695, kb_relative_information_score: 45.8928, mean_absolute_error: 0.3268, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.6852, predictive_accuracy: 0.6846, prior_entropy: 0.9998, recall: 0.6846, relative_absolute_error: 0.6538, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4985, root_relative_squared_error: 0.9972, scimark_benchmark: 924.6116, usercpu_time_millis: 30, usercpu_time_millis_training: 30,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7699, f_measure: 0.7076, kappa: 0.415, kb_relative_information_score: 48.7869, mean_absolute_error: 0.3177, mean_prior_absolute_error: 0.4999, number_of_instances: 130, precision: 0.7078, predictive_accuracy: 0.7077, prior_entropy: 0.9998, recall: 0.7077, relative_absolute_error: 0.6355, root_mean_prior_squared_error: 0.4999, root_mean_squared_error: 0.4699, root_relative_squared_error: 0.9399, scimark_benchmark: 945.6434, usercpu_time_millis: 10, usercpu_time_millis_training: 10,
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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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