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 class '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)
