caretSBF {caret} | R Documentation |
Ancillary functions for univariate feature selection
anovaFilter(x, y, cut = 0.05) gamFilter(x, y, cut = 0.05) caretSBF lmSBF rfSBF treebagSBF ldaSBF nbSBF
x |
a matrix or data frame of numeric predictors |
y |
a numeric or factor vector of outcomes |
cut |
a p-value cut-off |
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.
anovaFilter
and gamFilter
are two examples of univariate filtering functions. anovaFilter
fits a simple linear model between a single feature and the outcome, then the p-value for the whole model F-test is generated. If the p-values is greater than 0.05, the feature is retained for the model. gamFilter
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 p-values greater than 0.05 indicate that a predictor will be excluded.
If a particular model fails for lm
or gam
, the predictor is not used in the model.
Max Kuhn