ClusterPredictMixedData

ClusterPredictMixedData-class

This class encapsulate the parameters for predicted data.

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

ClusterPredictMixedData function

<dl>
<dt><code>ldata</code></dt>
<dd>list of matrix with the data sets</dd></dl>
<dt><code>lmissing</code></dt>
<dd>list of matrix with the indexes of the missing values</dd>

Slots

Author

Class [ClusterPredictMixedData] for predicting — ClusterPredictMixedData

<dl>
<dt><code>ldata</code></dt>
<dd>list of matrix with the data sets</dd>


<dt><code>lmissing</code></dt>
<dd>list of matrix with the indexes of the missing values</dd>


</dl>

ClusterPredictMixedData: Class [`ClusterPredictMixedData`] for predicting

Description

Arguments

Slots

Author

See Also

Examples