# rfe

0th

Percentile

##### Backwards Feature Selection Helper Functions

Ancillary fuctions for backwards selection

Keywords
models
##### Usage
pickSizeTolerance(x, metric, tol = 1.5, maximize)
pickSizeBest(x, metric, maximize) pickVars(y, size) caretFuncs
lmFuncs
rfFuncs
treebagFuncs
ldaFuncs
nbFuncs
##### Arguments
x
a matrix or data frame with the performance metric of interest
metric
a character string with the name of the performance metric that should be used to choose the appropriate number of variables
maximize
a logical; should the metric be maximized?
tol
a scalar to denote the acceptable difference in optimal performance (see Details below)
size
an integer for the number of variables to retain
##### Details

This page describes the functions that are used in backwards selection (aka recursive feature elimination). The funcitons described here are passed to the algorithm via the functions argument of rfeControl.

See rfeControl for details on how these functions should be defined.

rfeControl, rfe

##### Aliases
• caretFuncs
• lmFuncs
• rfFuncs
• treebagFuncs
• ldaFuncs
• nbFuncs
• pickSizeBest
• pickSizeTolerance
• pickVars
Documentation reproduced from package caret, version 4.20, License: GPL-2

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