spectral_igraph_communities

This function invoke <code>spectral_igraph_membership</code> to calculate
clustering and convert it into <code><a href="/link/communities?package=rSpectral&version=1.0.0.14" data-mini-rdoc="rSpectral::communities">communities</a></code> object for
seamless work with native <code><a href="/link/igraph?package=rSpectral&version=1.0.0.14" data-mini-rdoc="rSpectral::igraph">igraph</a></code> clustering functions.

Implements the network clustering algorithm described in
Newman (2006) <doi:10.1103/PhysRevE.74.036104>. The complete
iterative algorithm comprises of two steps. In the first step, the
network is expressed in terms of its leading eigenvalue and
eigenvector and recursively partition into two communities.
Partitioning occurs if the maximum positive
eigenvalue is greater than the tolerance (10e-5) for the current
partition, and if it results in a positive contribution to the
Modularity.
Given an initial separation using the leading eigen step, 'rSpectral'
then continues to maximise for the change in Modularity using a
fine-tuning step - or variate thereof. The first stage here is to
find the node which, when moved from one community to another,
gives the maximum change in Modularity. This node’s community is
then fixed and we repeat the process until all nodes have been moved.
The whole process is repeated from this new state until the change
in the Modularity, between the new and old state, is less than the
predefined tolerance.
A slight variant of the fine-tuning step, which can improve speed
of the calculation, is also provided. Instead of moving each node
into each community in turn, we only consider moves of neighbouring
nodes, found in different communities, to the community of the
current node of interest. The two steps process is repeatedly
applied to each new community found, subdivided each community
into two new communities, until we are unable to find any division
that results in a positive change in Modularity.

Anatoly Sorokin

rSpectral

Spectral Modularity Clustering

Colin Mclean

spectral_igraph_communities function

<dl><dt>g</dt>
<dd><code>igraph</code> object</dd>
<dt>Cn_min</dt>
<dd>minimum cluster size</dd>
<dt>tol</dt>
<dd>tolerance</dd>
<dt>names</dt>
<dd>are we dealing with alphaNumeric (1) or numeric (!1) ids</dd>
<dt>fix_neig</dt>
<dd>whether to fix neighbouring nodes found in same community</dd></dl>

Arguments

This function invoke <code>spectral_igraph_membership</code> to calculate
clustering and convert it into <code><a href='https://rdrr.io/pkg/igraph/man/communities.html'>communities</a></code> object for
seamless work with native <code><a href='https://rdrr.io/pkg/igraph/man/aaa-igraph-package.html'>igraph</a></code> clustering functions.

Spectral clustering for igraph objects — spectral_igraph_communities

<dl>

<dt>g</dt>
<dd><code>igraph</code> object</dd>


<dt>Cn_min</dt>
<dd>minimum cluster size</dd>


<dt>tol</dt>
<dd>tolerance</dd>


<dt>names</dt>
<dd>are we dealing with alphaNumeric (1) or numeric (!1) ids</dd>


<dt>fix_neig</dt>
<dd>whether to fix neighbouring nodes found in same community</dd>

</dl>

spectral_igraph_communities: Spectral clustering for `igraph` objects

Description

Usage

Value

Arguments

Examples