grid.arrange

<p>See <code><a href="/link/grid.arrange?package=vip&version=0.3.2" data-mini-rdoc="vip::grid.arrange">grid.arrange</a></code> for more details.</p>

internal

A general framework for constructing variable importance plots from
various types of machine learning models in R. Aside from some standard model-
specific variable importance measures, this package also provides model-
agnostic approaches that can be applied to any supervised learning algorithm.
These include 1) an efficient permutation-based variable importance measure,
2) variable importance based on Shapley values (Strumbelj and Kononenko,
2014) <doi:10.1007/s10115-013-0679-x>, and 3) the variance-based
approach described in Greenwell et al. (2018) <arXiv:1805.04755>. A
variance-based method for quantifying the relative strength of interaction
effects is also included (see the previous reference for details).

Brandon Greenwell

Variable Importance Plots

Brad Boehmke

Bernie Gray

grid.arrange function

<p>See <code><a href='https://rdrr.io/pkg/gridExtra/man/arrangeGrob.html'>grid.arrange</a></code> for more details.</p>

grid.arrange: Arrange multiple grobs on a page

Description

Usage

Arguments