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caretSBF

Selection By Filtering (SBF) Helper Functions


Description

Ancillary functions for univariate feature selection

Usage

caretSBF

anovaScores(x, y)

gamScores(x, y)

Arguments

x

a matrix or data frame of numeric predictors

y

a numeric or factor vector of outcomes

Format

An object of class list of length 5.

Details

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.

Author(s)

Max Kuhn

See Also


caret

Classification and Regression Training

v6.0-86
GPL (>= 2)
Authors
Max Kuhn [aut, cre], Jed Wing [ctb], Steve Weston [ctb], Andre Williams [ctb], Chris Keefer [ctb], Allan Engelhardt [ctb], Tony Cooper [ctb], Zachary Mayer [ctb], Brenton Kenkel [ctb], R Core Team [ctb], Michael Benesty [ctb], Reynald Lescarbeau [ctb], Andrew Ziem [ctb], Luca Scrucca [ctb], Yuan Tang [ctb], Can Candan [ctb], Tyler Hunt [ctb]
Initial release

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