RerF (aka Randomer Forest or Random Projection Forests) is an algorithm developed by Tomita et al. (2016) which is similar to Random Forest-Random Combination (Forest-RC) developed by Breiman (2001).
The difference between the two algorithms is where the random linear combinations occur: Forest-RC combines features at the tree level whereas RerF combines features at the node level.
- Memory optimized C++ implementation of RandomForest and RerF.
- Python bindings to packedForest.
- The R and C++ implemetation of RerF.