I’ve posted a new release of the ggRandomForests: Visually Exploring Random Forests to CRAN at (http://cran.r-project.org/package=ggRandomForests)

The biggest news is the inclusion of some holiday reading – a ggRandomForests package vignette!
ggRandomForests: Visually Exploring a Random Forest for Regression

The vignette is a tutorial for using the ggRandomForests package with the randomForestSRC package for building and post-processing a regression random forest. In this tutorial, we explore a random forest model for the Boston Housing Data, available in the MASS package. We grow a random forest for regression and demonstrate how ggRandomForests can be used to when determining variable associations, interactions and how the response depends on predictive variables within the model.

The tutorial demonstrates the design and usage of many of ggRandomForests functions and features. We also demonstrate how to modify and customize the resulting ggplot2 graphic objects along the way.

Next up in the package development queue is the completion of the Survival in Random Forests vignette (Preliminary draft version is avialable on CRAN also). A time to event analysis of the primary biliary cirrhosis (PBC) of the liver data from Fleming and Harrington (1991) “Counting processes and survival analysis.”

The development version of ggRandomForests is on GitHub at (https://github.com/ehrlinger/ggRandomForests)

Filed under: R Tagged: ggplot2, ggRandomForests, R, randomForestSRC