getBinaryTargetLevel

<p>For binary classification problems, ensemble
stacks and certain performance measures require an awareness
of which class in a two-factor outcome is the "target" class.
By default, this class will be assumed to be the first level in
an outcome factor but that setting can be overridden using
<code>setBinaryTargetLevel(2L)</code>.</p>

Functions for creating ensembles of caret models: caretList()
and caretStack().  caretList() is a convenience function for fitting multiple
caret::train() models to the same dataset. caretStack() will make linear or
non-linear combinations of these models, using a caret::train() model as a
meta-model, and caretEnsemble() will make a robust linear combination of
models using a GLM.

Zachary A Mayer

getBinaryTargetLevel: Return the configured target binary class level

Description

Usage

Arguments

Value

See Also