extractSubModel

extractSubModel,CombinedModelsPath,character-method

Extract a part of a <code>CombinedModelsPath-class</code> object

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

extractSubModel function

<dl><dt>sol</dt>
<dd>an <code>CombinedModelsPath-class</code> object</dd>
<dt>sub_model_name</dt>
<dd>a string which specify the part of the model to
extract. Note that the name must correspond to the one of the names used in
the list of models during the origin call to <code>greed</code>.</dd></dl>

Arguments

<ul>
<li><code>sol = CombinedModelsPath,sub_model_name = character</code>: CombinedModelsPath method</li>
</ul>

Methods (by class)

Extract a part of a CombinedModelsPath-class object — extractSubModel

<dl>

<dt>sol</dt>
<dd>an <code>CombinedModelsPath-class</code> object</dd>


<dt>sub_model_name</dt>
<dd>a string which specify the part of the model to
extract. Note that the name must correspond to the one of the names used in
the list of models during the origin call to <code>greed</code>.</dd>

</dl>

extractSubModel: Extract a part of a `CombinedModelsPath-class` object

Description

Usage

Value

Arguments

Methods (by class)