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Inglis, Alan, 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: | 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 |
| Related URLs: | |
| URI: | https://mural.maynoothuniversity.ie/id/eprint/19139 |
| 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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