kmodesD

K-modes function to accept any categorical distance based on
the function found in `klaR:kmodes`.

The gap statistic approach is extended to estimate the number of clusters for categorical response format data. This approach and accompanying software is designed to be used with the output of any clustering algorithm and with distances specifically designed for categorical (i.e. multiple choice) or ordinal survey response data.

Eduardo Cortes

DiscreteGapStatistic

An Extension of the Gap Statistic for Ordinal/Categorical Data

Jeffrey Miecznikowski

kmodesD function

<dl><dt>data</dt>
<dd>A matrix or data frame of categorical data. Objects have to be in rows, variables in columns.</dd>
<dt>modes</dt>
<dd>The number of modes</dd>
<dt>distFun</dt>
<dd>Pairwise categorical distance function. A function accepting two categorical vectors.</dd>
<dt>iter.max</dt>
<dd>The maximum number of iterations allowed.</dd></dl>

Arguments

Adapted k-modes algorithm — kmodesD

<dl>

<dt>data</dt>
<dd>A matrix or data frame of categorical data. Objects have to be in rows, variables in columns.</dd>


<dt>modes</dt>
<dd>The number of modes</dd>


<dt>distFun</dt>
<dd>Pairwise categorical distance function. A function accepting two categorical vectors.</dd>


<dt>iter.max</dt>
<dd>The maximum number of iterations allowed.</dd>

</dl>

kmodesD: Adapted k-modes algorithm

Description

Usage

Value

Arguments