Download the white paper: Big Data Decision Trees with R
by Richard Calaway, Lee Edlefsen, and Lixin Gong, Revolution Analytics
Revolution Analytics’ RevoScaleR package provides full-featured, fast, scalable, distributable predictive data analytics. The included rxDTree function provides the ability to estimate decision trees efficiently on very large data sets. Decision trees (Breiman, Friedman, Olshen, & Stone, 1984) provide relatively easy-to-interpret models, and are widely used in a variety of disciplines. For example,
The rxDTree function fits tree models using a binning-based recursive partitioning algorithm. The resulting model is similar to that produced by the recommended R package rpart (Therneau & Atkinson, 1997). Both classification-type trees and regression-type trees are supported.