clustering

clustering,IclFit-method

This method take a <code>IclFit-class</code> object and return an integer vector with the cluster assignments that were found.

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

clustering function

<dl><dt>fit</dt>
<dd>an <code>IclFit</code> solution</dd></dl>

Arguments

<ul>
<li><code>IclFit</code>: IclFit-class method</li>
</ul>

Methods (by class)

Method to extract the clustering results from an IclFit-class object — clustering

<dl>

<dt>fit</dt>
<dd>an <code>IclFit</code> solution</dd>

</dl>

clustering: Method to extract the clustering results from an `IclFit-class` object

Description

Usage

Value

Arguments

Methods (by class)