jump_stat

Obtains the jump statistic for a particular kernel for the
specified number of clusters

Implementations several algorithms for kernel k-means. The default
'OTQT' algorithm is a fast alternative to standard implementations of kernel
k-means, particularly in cases with many clusters. For a small number of
clusters, the implemented 'MacQueen' method typically performs the fastest. For
more details and performance evaluations, see Berlinski and Maitra (2025) <doi:10.1002/sam.70032>.

Josh Berlinski

kkmeans

Fast Implementations of Kernel K-Means

jump_stat function

<dl><dt>data</dt>
<dd>Numeric data to cluster. This will be converted to a matrix using <code>as.matrix</code>.</dd>
<dt>kern</dt>
<dd>The kernel to use.</dd>
<dt>param</dt>
<dd>The parameter value to pass to the kernel</dd>
<dt>k_max</dt>
<dd>The maximum number of clusters to consider</dd>
<dt>eta</dt>
<dd>Power for the jump statistic</dd>
<dt>iter_max</dt>
<dd>Maximum number of iterations to use in <code>kkmeans</code> call</dd></dl>

Arguments

Function to get jump statistic for varying values of k — jump_stat

<dl>

<dt>data</dt>
<dd>Numeric data to cluster. This will be converted to a matrix using <code>as.matrix</code>.</dd>


<dt>kern</dt>
<dd>The kernel to use.</dd>


<dt>param</dt>
<dd>The parameter value to pass to the kernel</dd>


<dt>k_max</dt>
<dd>The maximum number of clusters to consider</dd>


<dt>eta</dt>
<dd>Power for the jump statistic</dd>


<dt>iter_max</dt>
<dd>Maximum number of iterations to use in <code>kkmeans</code> call</dd>

</dl>

jump_stat: Function to get jump statistic for varying values of k

Description

Usage

Value

Arguments