LinkCluE: A MATLAB Package for Link-Based Cluster Ensembles

Natthakan Iam-on and Simon Garrett

Journal of Statistical Software, 2010, vol. 036, issue i09

Abstract: Cluster ensembles have emerged as a powerful meta-learning paradigm that provides improved accuracy and robustness by aggregating several input data clusterings. In particular, link-based similarity methods have recently been introduced with superior performance to the conventional co-association approach. This paper presents a MATLAB package, LinkCluE, that implements the link-based cluster ensemble framework. A variety of functional methods for evaluating clustering results, based on both internal and external criteria, are also provided. Additionally, the underlying algorithms together with the sample uses of the package with interesting real and synthetic datasets are demonstrated herein.

Date: 2010-08-31
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.jstatsoft.org/index.php/jss/article/view/v036i09/v36i09.pdf
https://www.jstatsoft.org/index.php/jss/article/do ... v036i09/LinkCluE.zip
https://www.jstatsoft.org/index.php/jss/article/do ... ile/v036i09/v36i09.m

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:036:i09

DOI: 10.18637/jss.v036.i09

Access Statistics for this article

Journal of Statistical Software is currently edited by Bettina Grün, Edzer Pebesma and Achim Zeileis

More articles in Journal of Statistical Software from Foundation for Open Access Statistics
Bibliographic data for series maintained by Christopher F. Baum ().