Deep learning in R

Szilard's machine learning benchmark

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.).

Are categorical variables getting lost in your random forests?

Benchmark of categorical encoding schemes and the effect on tree based models (Scikit-learn vs H2O). Oct 28, 2016