Plot the response for newdata of a TreeSurrogate object. Each plot facet is one leaf node and visualizes the distribution of the \(\hat{y}\) from the machine learning model.

# S3 method for TreeSurrogate
plot(object)

Arguments

object

A TreeSurrogate object.

Value

ggplot2 plot object

See also

Examples

library("randomForest")
# Fit a Random Forest on the Boston housing data set
data("Boston", package = "MASS")
rf <- randomForest(medv ~ ., data = Boston, ntree = 50)
# Create a model object
mod <- Predictor$new(rf, data = Boston[-which(names(Boston) == "medv")])

# Fit a decision tree as a surrogate for the whole random forest
dt <- TreeSurrogate$new(mod)

# Plot the resulting leaf nodes
plot(dt)