plot.ULDA

This function plots the decision boundaries and linear discriminant (LD)
scores for a given ULDA model. If it is a binary classification problem, a
density plot is created. Otherwise, a scatter plot with decision boundaries
is generated.

A novel forward stepwise discriminant analysis framework
that integrates Pillai's trace with Uncorrelated Linear Discriminant Analysis (ULDA),
providing an improvement over traditional stepwise LDA methods that rely on Wilks' Lambda.
A stand-alone ULDA implementation is also provided, offering a more general solution
than the one available in the 'MASS' package. It automatically handles missing values and
provides visualization tools. For more details, see Wang (2024) <doi:10.48550/arXiv.2409.03136>.

Siyu Wang

folda

Forward Stepwise Discriminant Analysis with Pillai's Trace

plot.ULDA function

<dl><dt>x</dt>
<dd>A fitted ULDA model object.</dd>
<dt>datX</dt>
<dd>A data frame containing the predictor variables.</dd>
<dt>response</dt>
<dd>A factor representing the response variable (training labels)
corresponding to <code>datX</code>.</dd>
<dt>...</dt>
<dd>Additional arguments.</dd></dl>

Arguments

Plot Decision Boundaries and Linear Discriminant Scores — plot.ULDA

<dl>

<dt>x</dt>
<dd>A fitted ULDA model object.</dd>


<dt>datX</dt>
<dd>A data frame containing the predictor variables.</dd>


<dt>response</dt>
<dd>A factor representing the response variable (training labels)
corresponding to <code>datX</code>.</dd>


<dt>...</dt>
<dd>Additional arguments.</dd>

</dl>

plot.ULDA: Plot Decision Boundaries and Linear Discriminant Scores

Description

Usage

Value

Arguments

Examples