Sealbook

szilard/benchm-ml

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 algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

data-sciencedeep-learninggradient-boosting-machineh2omachine-learningpythonrrandom-forestsparkxgboost

License & maintenance

MIT is a permissive license: free to use commercially with attribution.

Last code push 4 years ago.