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Partial Dependence Plot

Source: R/plot_main_effect.R
plot_pdp.Rd

A version of plot_main_effect with the intercept term (horizontal line) added, resulting in a partial dependence plot.

Usage

plot_pdp(object, predictor, rug_sides = "b", ...)

Arguments

object

Object of class glex.

predictor

(character(1)) predictor names, e.g. "x1" to plot main effect of x1.

rug_sides

(character(1): "b") Sides to plot rug (see ggplot2::geom_rug()) plot on for continuous predictors.. Default is "b" for both sides. Set to "none" to disable rug plot.

...

Used for future expansion.

Value

A ggplot2 object.

See also

plot_main_effect()

Other Visualization functions: autoplot.glex(), autoplot.glex_vi(), glex_explain()

Examples

if (requireNamespace("randomPlantedForest", quietly = TRUE)) {
library(randomPlantedForest)

# introduce factor variables to show categorical feature handling
mtcars$cyl <- factor(mtcars$cyl)
mtcars$vs <- factor(mtcars$vs)

# Fit forest, get components
set.seed(12)
rpfit <- rpf(mpg ~ cyl + wt + hp + drat + vs, data = mtcars, ntrees = 25, max_interaction = 3)
components <- glex(rpfit, mtcars)

plot_pdp(components, "wt")
plot_pdp(components, "cyl")
}