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. This package can be used as an independent alternative to the
(not free) 'mixtcomp' software available at <https://massiccc.lille.inria.fr/>.

Serge Iovleff

MixAll

Clustering and Classification using Model-Based Mixture Models

Parmeet Bathia

ClusterPredictMixedData function

<dl class="dl-horizontal">
<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

Class [<code><a href='<a href='ClusterPredictMixedData'></a>'>ClusterPredictMixedData</a></code>] for predicting — ClusterPredictMixedData

Class [<code><a href='<a href='ClusterPredictMixedData'></a>'>ClusterPredictMixedData</a></code>] for predicting

Class [<code><a href="/link/?package=MixAll&version=1.4.2" clusterpredictmixeddata'="" data-mini-rdoc="MixAll::"></a>'>ClusterPredictMixedData</code>] for predicting

ClusterPredictMixedData: Class [`'>ClusterPredictMixedData`] for predicting

Description

Arguments

Slots

See Also

Examples