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334
1.9k
mit
146
A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algor...
Created 2015-03-28
522 commits to master branch, last one 5 years ago
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
Created 2018-03-14
169 commits to master branch, last one 2 years ago
101
471
mit
16
A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical ...
Created 2019-03-06
404 commits to master branch, last one 4 months ago
28
217
mit
21
Performance of various open source GBM implementations
Created 2017-05-27
504 commits to master branch, last one 8 months ago
69
94
gpl-2.0
11
This repository has no description...
Created 2014-01-13
103 commits to master branch, last one 2 years ago