fdm2id (version 0.9.6)

selectfeatures: Feature selection for classification

Description

Select a subset of features for a classification task.

Usage

selectfeatures(
  train,
  labels,
  algorithm = c("ranking", "forward", "backward", "exhaustive"),
  unieval = if (algorithm[1] == "ranking") c("fisher", "fstat", "relief",
    "inertiaratio") else NULL,
  uninb = NULL,
  unithreshold = NULL,
  multieval = if (algorithm[1] == "ranking") NULL else c("mrmr", "cfs", "fstat",
    "inertiaratio", "wrapper"),
  wrapmethod = NULL,
  keep = FALSE,
  ...
)

Arguments

train

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

labels

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

algorithm

The feature selection algorithm.

unieval

The (univariate) evaluation criterion. uninb, unithreshold or multieval must be specified.

uninb

The number of selected feature (univariate evaluation).

unithreshold

The threshold for selecting feature (univariate evaluation).

multieval

The (multivariate) evaluation criterion.

wrapmethod

The classification method used for the wrapper evaluation.

keep

If true, the dataset is kept in the returned result.

...

Other parameters.

See Also

FEATURESELECTION, selection-class

Examples

if (FALSE) {
require (datasets)
data (iris)
selectfeatures (iris [, -5], iris [, 5], algorithm = "forward", multieval = "fstat")
selectfeatures (iris [, -5], iris [, 5], algorithm = "ranking", uninb = 2)
selectfeatures (iris [, -5], iris [, 5], algorithm = "ranking",
                multieval = "wrapper", wrapmethod = LDA)
}