Plot the error graph of the pruned oblique decision tree at different split nodes.
Usage
# S3 method for class 'prune.ODT'
plot(x, position = "topleft", digits = NULL, main = NULL, ...)Arguments
- x
An object of class
prune.ODT.- position
Position of the curve label, including "topleft" (default), "bottomright", "bottom", "bottomleft", "left", "top", "topright", "right" and "center".
- digits
Integer indicating the number of decimal places (round) or significant digits (signif) to be used.
- main
main title
- ...
Arguments to be passed to methods.
Value
The leftmost value of the horizontal axis indicates the tree without pruning, while the rightmost value indicates the data without splitting and using the average value as the predicted value.
Examples
data(body_fat)
set.seed(221212)
train <- sample(1:252, 100)
train_data <- data.frame(body_fat[train, ])
test_data <- data.frame(body_fat[-train, ])
tree <- ODT(Density ~ ., train_data, split = "mse")
prune_tree <- prune(tree, test_data[, -1], test_data[, 1])
# Plot pruned oblique decision tree structure (default)
plot(prune_tree)
# Plot the error graph of the pruned oblique decision tree.
class(prune_tree) <- "prune.ODT"
plot(prune_tree)
