# rfe

From caret v4.20
by Max Kuhn

##### 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.

##### See Also

*Documentation reproduced from package caret, version 4.20, License: GPL-2*

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