# NOT RUN {
if (require("rpart")) {
# We train a tree on the Boston dataset:
data("Boston", package = "MASS")
tree = rpart(medv ~ ., data = Boston)
y = Boston$medv
X = Boston[-which(names(Boston) == "medv")]
mod = Predictor$new(tree, data = X, y = y)
# Compute feature importances as the performance drop in mean absolute error
imp = FeatureImp$new(mod, loss = "mae")
# Plot the results directly
plot(imp)
}
# }
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