# vivid

Variable importance, interaction measures and partial dependence plots are important summaries in the interpretation of statistical and machine learning models. In our R package `vivid`

(variable importance and variable interaction displays) we create new visualisation techniques for exploring these model summaries. We construct heatmap and graph-based displays showing variable importance and interaction jointly, which are carefully designed to highlight important aspects of the fit. We also construct a new matrix-type layout showing all single and bivariate partial dependence plots, and an alternative layout based on graph Eulerians focusing on key subsets. Our new visualisations are model-agnostic and are applicable to regression and classification supervised learning settings. They enhance interpretation even in situations where the number of variables is large and the interaction structure complex.

## Installation

The `zenplots`

package (which is used within `vivid`

) requires the `graph`

package from `BioConductor.`

To install the `graph`

and `zenplots`

packages use:

```
if (!requireNamespace("graph", quietly = TRUE)){
install.packages("BiocManager")
BiocManager::install("graph")
}
install.packages("zenplots")
```

You can install the released version of vivid from CRAN with:

`install.packages("vivid")`

And the development version from GitHub with:

```
# install.packages("devtools")
devtools::install_github("AlanInglis/vivid")
```

You can then load the package with: