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RANDOMFOREST

Classification using Random Forest


Description

This function builds a classification model using Random Forest

Usage

RANDOMFOREST(
  train,
  labels,
  ntree = 500,
  nvar = if (!is.null(labels) && !is.factor(labels)) max(floor(ncol(train)/3), 1) else
    floor(sqrt(ncol(train))),
  tune = FALSE,
  ...
)

Arguments

train

The training set (description), as a data.frame.

labels

Class labels of the training set (vector or factor).

ntree

The number of trees in the forest.

nvar

Number of variables randomly sampled as candidates at each split.

tune

If true, the function returns paramters instead of a classification model.

...

Other parameters.

Value

The classification model.

See Also

Examples

## Not run: 
require (datasets)
data (iris)
RANDOMFOREST (iris [, -5], iris [, 5])

## End(Not run)

fdm2id

Data Mining and R Programming for Beginners

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

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