calculate_stability_measures

Calculate Stability Measures for a Clustering Method

internal

Implementation of the bootstrapping approach for the estimation of clustering stability and its application in estimating the number of clusters, as introduced by Yu et al (2016)<doi:10.1142/9789814749411_0007>. Implementation of the non-parametric bootstrap approach to assessing the stability of module detection in a graph, the extension for the selection of a parameter set that defines a graph from data in a way that optimizes stability and the corresponding visualization functions, as introduced by Tian et al (2021) <doi:10.1002/sam.11495>. Implemented out-of-bag stability estimation function and k-select Smin-based k-selection function as introduced by Liu et al (2022) <doi:10.1002/sam.11593>. Implemented ensemble clustering method based-on k-means clustering method, spectral clustering method and hierarchical clustering method.

Tianmou Liu

bootcluster

Bootstrapping Estimates of Clustering Stability

Han Yu

Mingmei Tian

calculate_stability_measures function

<dl><dt>x</dt>
<dd>Input data matrix</dd>
<dt>k</dt>
<dd>Number of clusters</dd>
<dt>scheme</dt>
<dd>Clustering scheme ("kmeans", "hc", or "spectral")</dd>
<dt>B</dt>
<dd>Number of bootstrap samples</dd>
<dt>n_ref</dt>
<dd>Number of reference distributions</dd>
<dt>hc.method</dt>
<dd>Hierarchical clustering method</dd>
<dt>dist_method</dt>
<dd>Distance method</dd></dl>

Arguments

Calculate Stability Measures for a Clustering Method — calculate_stability_measures

<dl>

<dt>x</dt>
<dd>Input data matrix</dd>


<dt>k</dt>
<dd>Number of clusters</dd>


<dt>scheme</dt>
<dd>Clustering scheme ("kmeans", "hc", or "spectral")</dd>


<dt>B</dt>
<dd>Number of bootstrap samples</dd>


<dt>n_ref</dt>
<dd>Number of reference distributions</dd>


<dt>hc.method</dt>
<dd>Hierarchical clustering method</dd>


<dt>dist_method</dt>
<dd>Distance method</dd>

</dl>

calculate_stability_measures: Calculate Stability Measures for a Clustering Method

Description

Usage

Value

Arguments