DlvmCoPrior-class

An S4 class to represent an abstract generative model

An ensemble of algorithms that enable the clustering of networks and data matrices (such as counts, categorical or continuous) with different type of generative models. Model selection and clustering is performed in combination by optimizing the Integrated Classification Likelihood (which is equivalent to minimizing the description length). Several models are available such as: Stochastic Block Model, degree corrected Stochastic Block Model, Mixtures of Multinomial, Latent Block Model. The optimization is performed thanks to a combination of greedy local search and a genetic algorithm (see <arXiv:2002:11577> for more details).

Etienne C<c3><b4>me

greed

Clustering and Model Selection with the Integrated
Classification Likelihood

Etienne Côme

Nicolas Jouvin

DlvmCoPrior-class function

<dl>
<dt><code>alpha</code></dt>
<dd>a numeric vector of length 1 which define the parameters of the Dirichlet over the cluster proportions (default to 1)</dd></dl>

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Abstract class to represent a generative model for co-clustering — DlvmCoPrior-class

<dl>
<dt><code>alpha</code></dt>
<dd>a numeric vector of length 1 which define the parameters of the Dirichlet over the cluster proportions (default to 1)</dd>


</dl>

DlvmCoPrior-class: Abstract class to represent a generative model for co-clustering

Description

Arguments

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