Selection By Filtering (SBF) Helper Functions
Ancillary functions for univariate feature selection
a matrix or data frame of numeric predictors
a numeric or factor vector of outcomes
More details on these functions can be found at http://topepo.github.io/caret/feature-selection-using-univariate-filters.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 for details on how these functions should be
gamScores are two examples of univariate
anovaScores fits a simple linear model between a
single feature and the outcome, then the p-value for the whole model F-test
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
gam, a p-value of 1 is
An object of class
list of length 5.