plot.rda_high_dim_cv

<p>Uses <code><a rd-options="ggplot2:ggplot2-package" href="/link/ggplot2%3A%3Aggplot2()?package=sparsediscrim&version=0.3.0&to=ggplot2%3Aggplot2-package" data-mini-rdoc="ggplot2:ggplot2-package::ggplot2::ggplot2()">ggplot2::ggplot2()</a></code> to plot a heatmap of the training error
grid.</p>

A collection of sparse and regularized discriminant analysis
methods intended for small-sample, high-dimensional data sets. The package
features the High-Dimensional Regularized Discriminant Analysis classifier
from Ramey et al. (2017) <arXiv:1602.01182>. Other classifiers include
those from Dudoit et al. (2002) <doi:10.1198/016214502753479248>, Pang et
al. (2009) <doi:10.1111/j.1541-0420.2009.01200.x>, and Tong et al. (2012)
<doi:10.1093/bioinformatics/btr690>.

Max Kuhn

sparsediscrim

Sparse and Regularized Discriminant Analysis

John Ramey

plot.rda_high_dim_cv function

<p>Uses <code><a rd-options='ggplot2:ggplot2-package' href='ggplot2::ggplot2()'>ggplot2::ggplot2()</a></code> to plot a heatmap of the training error
grid.</p>

plot.rda_high_dim_cv: Plots a heatmap of cross-validation error grid for a HDRDA classifier object.

Description

Usage

Arguments

Value