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.