diceR

diceR-package

<img src="figures/logo.png?package=diceR&version=1.0.3" align="right" alt="logo" width="120">
Performs cluster analysis using an ensemble
 clustering framework, Chiu &amp; Talhouk (2018)
 &lt;doi:10.1186/s12859-017-1996-y&gt;. Results from a diverse set of
 algorithms are pooled together using methods such as majority voting,
 K-Modes, LinkCluE, and CSPA. There are options to compare cluster
 assignments across algorithms using internal and external indices,
 visualizations such as heatmaps, and significance testing for the
 existence of clusters.

internal

Performs cluster analysis using an ensemble
clustering framework, Chiu & Talhouk (2018)
<doi:10.1186/s12859-017-1996-y>. Results from a diverse set of
algorithms are pooled together using methods such as majority voting,
K-Modes, LinkCluE, and CSPA. There are options to compare cluster
assignments across algorithms using internal and external indices,
visualizations such as heatmaps, and significance testing for the
existence of clusters.

Derek Chiu

Diverse Cluster Ensemble in R

Aline Talhouk

Johnson Liu

diceR-package function

<img src='figures/logo.png' align='right' alt='logo' width='120' />
Performs cluster analysis using an ensemble
 clustering framework, Chiu &amp; Talhouk (2018)
 &lt;doi:10.1186/s12859-017-1996-y&gt;. Results from a diverse set of
 algorithms are pooled together using methods such as majority voting,
 K-Modes, LinkCluE, and CSPA. There are options to compare cluster
 assignments across algorithms using internal and external indices,
 visualizations such as heatmaps, and significance testing for the
 existence of clusters.

diceR-package: diceR: Diverse Cluster Ensemble in R

Description

Arguments

See Also