ReForeSt is a distributed, scalable implementation of the Random Forest learning algorithm which target fast and memory efficient processing.

ReForeSt and its documentation have been designed for developers and data scientists which are familiar with the Spark Enviroment and the MLlib library. Consequently please refer first to those documentation before starting with ReForeSt