AndrewjSage/RFLOWESS: A robust approach to random forest regression
Version 1.0.1

This package implements the LOWESS-RF method described by Sage, Genschel, and Nettleton. Random forest prediction weights are iteratively adjusted so that outlying cases are downweighted, resulting in a more robust prediction. Outlying cases are identified using a residual analysis. This approach is motivated by Cleveland's (1979) locally weighted regression and scatterplot smoothing technique.

Getting started

Package details

AuthorAndrew Sage
MaintainerAndrew Sage <[email protected]>
LicenseWhat license is it under?
Version1.0.1
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("AndrewjSage/RFLOWESS")
AndrewjSage/RFLOWESS documentation built on June 13, 2018, 4:58 a.m.