plot.svmmajcrossval

Shows the results of the cross validation graphically.
Possible graphics are among others the distribution of
the predicted values <code>q</code> per class per lambda value
and the misclassification rate per lambda.

Implements the SVM-Maj algorithm to train data with support vector machine
<doi:10.1007/s11634-008-0020-9>.
This algorithm uses two efficient updates, one for linear kernel and one
for the nonlinear kernel.

Hok San Yip

SVMMaj

Implementation of the SVM-Maj Algorithm

Hoksan Yip

Georgi Nalbantov

plot.svmmajcrossval function

<dl><dt>x</dt>
<dd>the <code>svmmajcrossval</code> object</dd>
<dt>type</dt>
<dd>the type of graph being shown, possible values are
<code>'grid'</code> for the missclassification rate per lambda value,
<code>'profile'</code> the distribution of predicted values
of the classes per lambda value</dd>
<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd></dl>

Arguments

Plot the cross validation output — plot.svmmajcrossval

<dl>

<dt>x</dt>
<dd>the <code>svmmajcrossval</code> object</dd>


<dt>type</dt>
<dd>the type of graph being shown, possible values are
<code>'grid'</code> for the missclassification rate per lambda value,
<code>'profile'</code> the distribution of predicted values
of the classes per lambda value</dd>


<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd>

</dl>

plot.svmmajcrossval: Plot the cross validation output

Description

Usage

Arguments