plot.prune.ODT: to plot pruned oblique decision tree

In ODRF: Oblique Decision Random Forest for Classification and Regression

to plot pruned oblique decision tree

Description

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.

See Also

ODT prune.ODT

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)

ODRF documentation built on May 31, 2023, 8:22 p.m.