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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.
Getting started
Browse package contents
Package details |
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| Author | Zachary M. Jones <zmj@zmjones.com> and Fridolin Linder <fridolin.linder@gmail.com> |
| Maintainer | Zachary M. Jones <zmj@zmjones.com> |
| License | MIT + file LICENSE |
| Version | 1.1.1 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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Try the edarf package in your browser
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