get_cluster_tightness_vector

Compute dispersion measures of a list of clusters

Topological data analysis (TDA) is a method of data analysis that
uses techniques from topology to analyze high-dimensional data. Here we
implement Mapper, an algorithm from this area developed by Singh, Mémoli and
Carlsson (2007) which generalizes the concept of a
Reeb graph <https://en.wikipedia.org/wiki/Reeb_graph>.

George Clare Kennedy

mappeR

Construct and Visualize TDA Mapper Graphs

get_cluster_tightness_vector function

<dl><dt>dists</dt>
<dd>A distance matrix for the data points inside all the input clusters</dd>
<dt>binclust_data</dt>
<dd>A list of named vectors whose names are those of data points and whose values are cluster ids</dd></dl>

Arguments

Compute dispersion measures of a list of clusters — get_cluster_tightness_vector

<dl>

<dt>dists</dt>
<dd>A distance matrix for the data points inside all the input clusters</dd>


<dt>binclust_data</dt>
<dd>A list of named vectors whose names are those of data points and whose values are cluster ids</dd>

</dl>

get_cluster_tightness_vector: Compute dispersion measures of a list of clusters

Description

Usage

Value

Arguments