Inglis, Alan and Parnell, Andrew and Hurley, Catherine (2023) vivid: An R package for Variable Importance and Variable Interactions Displays for Machine Learning Models. The R Journal, 15 (2). pp. 344-361. ISSN 2073-4859

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Abstract

We present vivid, an R package for visualizing variable importance and variable interactions in machine learning models. The package provides 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 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.

Item Type:	Article
Keywords:	Computer Science, Interdisciplinary Applications; Mathematics; Physical Sciences; Science & Technology;
Academic Unit:	Faculty of Science and Engineering > Mathematics and Statistics Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	19139
Identification Number:	https://doi.org/10.32614/RJ-2023-054
Depositing User:	Dr. Catherine Hurley
Date Deposited:	31 Oct 2024 15:07
Journal or Publication Title:	The R Journal
Publisher:	The R Foundation
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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