STUMP: Classification using one-level decision tree

In fdm2id: Data Mining and R Programming for Beginners

Classification using one-level decision tree

Description

This function builds a classification model using CART with maxdepth = 1.

Usage

STUMP(train, labels, randomvar = TRUE, tune = FALSE, ...)

Arguments

train	The training set (description), as a data.frame.
labels	Class labels of the training set (vector or factor).
randomvar	If true, the model uses a random variable.
tune	If true, the function returns paramters instead of a classification model.
...	Other parameters.

Value

The classification model.

See Also

CART

Examples

require (datasets)
data (iris)
STUMP (iris [, -5], iris [, 5])

fdm2id documentation built on July 9, 2023, 6:05 p.m.