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STUMP

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

Examples

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

fdm2id

Data Mining and R Programming for Beginners

v0.9.5
GPL-3
Authors
Alexandre Blansché [aut, cre]
Initial release

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