clusterTrees

Reorders a list of tree structures based on the clustering of variables within each tree.

Investigating and visualising Bayesian Additive Regression Tree (BART) (Chipman, H. A., George, E. I., & McCulloch, R. E. 2010) <doi:10.1214/09-AOAS285> model fits. We construct conventional plots to analyze a model’s performance and stability as well as create new tree-based plots to analyze variable importance, interaction, and tree structure. We employ Value Suppressing Uncertainty Palettes (VSUP) to construct heatmaps that display variable importance and interactions jointly using colour scale to represent posterior uncertainty. Our visualisations are designed to work with the most popular BART R packages available, namely 'BART' Rodney Sparapani and Charles Spanbauer and Robert McCulloch 2021 <doi:10.18637/jss.v097.i01>, 'dbarts' (Vincent Dorie 2023) <https://CRAN.R-project.org/package=dbarts>, and 'bartMachine' (Adam Kapelner and Justin Bleich 2016) <doi:10.18637/jss.v070.i04>.

Alan Inglis

bartMan

Create Visualisations for BART Models

Andrew Parnell

Catherine Hurley

Claus Wilke

clusterTrees function

<dl><dt>tree_list</dt>
<dd>A list of trees, where each tree is expected to have a 'var' column.</dd></dl>

Arguments

Cluster Trees by Variable — clusterTrees

<dl>

<dt>tree_list</dt>
<dd>A list of trees, where each tree is expected to have a 'var' column.</dd>

</dl>

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clusterTrees: Cluster Trees by Variable

Description

Usage

Value

Arguments