plot.pprf: Plot a pprf model.

In ppforest2: Projection Pursuit Oblique Decision Trees and Random Forests

Plot a pprf model.

Description

Visualizes a pprf model. By default, shows variable importance with one plot per metric side by side. Use metric to show a single importance metric.

Usage

## S3 method for class 'pprf'
plot(x, type = "importance", metric = NULL, tree_index = 1L, node = 1L, ...)

Arguments

x	A pprf model.
type	Character string specifying the plot type. "importance" (default) shows variable importance, "structure" shows a specific tree with embedded histograms, "projection" shows projected data at a node, "boundaries" shows decision boundaries of a specific tree.
metric	Character string selecting a single importance metric to plot: "projections", "weighted", or "permuted". NULL (default) shows all available metrics side by side in separate panels. Only used when type = "importance".
tree_index	Integer index of the tree to plot (1-based). Only used when type = "structure", type = "projection", or type = "boundaries". Defaults to 1.
node	Integer index of the node for projection plots. Defaults to 1 (root). Only used when type = "projection".
...	Additional arguments passed to the internal plotting function.

Value

A ggplot2-compatible object (invisibly). The importance grid returns a patchwork object that works with ggplot2::ggsave().

Examples

if (requireNamespace("ggplot2", quietly = TRUE) &&
    requireNamespace("patchwork", quietly = TRUE)) {
  forest <- pprf(Species ~ ., data = iris, size = 10)
  plot(forest)                                    # all metrics side by side
  plot(forest, metric = "permuted")               # single metric
  plot(forest, type = "structure", tree_index = 1)
  plot(forest, type = "projection", tree_index = 1)
}

ppforest2 documentation built on July 21, 2026, 9:07 a.m.