sbfFunctions: Selection By Filtering (SBF) Helper Functions
In caret: Classification and Regression Training

Description Usage Arguments Details Author(s) See Also

Ancillary functions for univariate feature selection

anovaScores(x, y)
gamScores(x, y) 

caretSBF
lmSBF
rfSBF
treebagSBF
ldaSBF
nbSBF

`x`	a matrix or data frame of numeric predictors
`y`	a numeric or factor vector of outcomes

More details on these functions can be found at http://caret.r-forge.r-project.org/featureselection.html.

This page documents the functions that are used in selection by filtering (SBF). The functions described here are passed to the algorithm via the functions argument of sbfControl.

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

anovaScores and gamScores are two examples of univariate filtering functions. anovaScores fits a simple linear model between a single feature and the outcome, then the p-value for the whole model F-test is returned. gamScores fits a generalized additive model between a single predictor and the outcome using a smoothing spline basis function. A p-value is generated using the whole model test from summary.gam and is returned.

If a particular model fails for lm or gam, a p-value of 1 is returned.

Max Kuhn

sbfControl, sbf, summary.gam

caret documentation built on May 2, 2019, 5:47 p.m.