vivid: An R package for Variable Importance and Variable Interactions Displays for Machine Learning Models
Abstract
We present vivid, an R package for visualizing variable importance and variable interactions in machine learning models. The package provides a range of displays including heatmap and graph-based displays for viewing variable importance and interaction jointly and partial dependence plots in both a matrix layout and an alternative layout emphasizing important variable subsets. With the intention of increasing a machine learning models' interpretability and making the work applicable to a wider readership, we discuss the design choices behind our implementation by focusing on the package structure and providing an in-depth look at the package functions and key features. We also provide a practical illustration of the software in use on a data set.
Keywords
Cite
@article{arxiv.2210.11391,
title = {vivid: An R package for Variable Importance and Variable Interactions Displays for Machine Learning Models},
author = {Alan Inglis and Andrew Parnell and Catherine Hurley},
journal= {arXiv preprint arXiv:2210.11391},
year = {2024}
}
Comments
15 pages, 7 figures