ClusterAlgoPredict

ClusterAlgoPredict-class

This class encapsulates the parameters of prediction methods.

Algorithms and methods for model-based clustering and classification.
It supports various types of data: continuous, categorical and counting
and can handle mixed data of these types. It can fit Gaussian (with diagonal
covariance structure), gamma, categorical and Poisson models. The algorithms
also support missing values.

Serge Iovleff

MixAll

Clustering and Classification using Model-Based Mixture Models

Parmeet Bathia

ClusterAlgoPredict function

<dl>
<dt><code>algo</code></dt>
<dd>A character string with the algorithm.
Possible values: "EM", "SemiSEM". Default value: "SemiSEM".</dd></dl>
<dt><code>nbIterBurn</code></dt>
<dd>Integer defining the number of burning iterations. Default value is 50.</dd>
<dt><code>nbIterLong</code></dt>
<dd>Integer defining the number of iterations. Default value is 100.</dd>
<dt><code>epsilon</code></dt>
<dd>real defining the epsilon value for the long algorithm. epsilon is
note used if <code>algo</code> is "SemiSEM". Default value: 1e-07.</dd>

Slots

[ClusterAlgoPredict] class for predict algorithm. — ClusterAlgoPredict

<dl>
<dt><code>algo</code></dt>
<dd>A character string with the algorithm.
Possible values: "EM", "SemiSEM". Default value: "SemiSEM".</dd>


<dt><code>nbIterBurn</code></dt>
<dd>Integer defining the number of burning iterations. Default value is 50.</dd>


<dt><code>nbIterLong</code></dt>
<dd>Integer defining the number of iterations. Default value is 100.</dd>


<dt><code>epsilon</code></dt>
<dd>real defining the epsilon value for the long algorithm. epsilon is
note used if <code>algo</code> is "SemiSEM". Default value: 1e-07.</dd>


</dl>

ClusterAlgoPredict: [`ClusterAlgoPredict`] class for predict algorithm.

Description

Arguments

Slots

Examples