IClusterPredict

IClusterPredict-class

Interface base class for predicting clusters

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

IClusterPredict function

<dl class="dl-horizontal">
<dt><code>nbSample</code></dt><dd>Integer with the number of samples</dd></dl><dt><code>nbCluster</code></dt><dd>Integer with the number of cluster</dd><dt><code>pk</code></dt><dd>Vector of size K with the proportions of each mixture.</dd><dt><code>tik</code></dt><dd>Matrix of size \(n \times K\) with the posterior probability of
the ith individual to belong to kth cluster.</dd><dt><code>lnFi</code></dt><dd>Vector of size n with the log-likelihood of the ith individuals.</dd><dt><code>zi</code></dt><dd>Vector of integer of size n with the attributed class label of the individuals</dd><dt><code>algo</code></dt><dd>an instance of [<code><a href="/link/?package=MixAll&version=1.4.2" clusteralgopredict'="" data-mini-rdoc="MixAll::"></a>'>ClusterAlgoPredict</code>]</dd>

Slots

Interface class [<code><a href='<a href='IClusterPredict'></a>'>IClusterPredict</a></code>] for predicting — IClusterPredict

Interface class [<code><a href='<a href='IClusterPredict'></a>'>IClusterPredict</a></code>] for predicting

Interface class [<code><a href="/link/?package=MixAll&version=1.4.2" iclusterpredict'="" data-mini-rdoc="MixAll::"></a>'>IClusterPredict</code>] for predicting

IClusterPredict: Interface class [`'>IClusterPredict`] for predicting

Description

Arguments

Slots

Examples