edarf: Exploratory Data Analysis using Random Forests

Functions useful for exploratory data analysis using random forests which can be used to compute multivariate partial dependence, observation, class, and variable-wise marginal and joint permutation importance as well as observation-specific measures of distance (supervised or unsupervised). All of the aforementioned functions are accompanied by 'ggplot2' plotting functions.

Package details

AuthorZachary M. Jones <[email protected]> and Fridolin Linder <[email protected]>
MaintainerZachary M. Jones <[email protected]>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
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edarf documentation built on May 29, 2017, 3:51 p.m.