Ciência-IUL
Publications
Publication Detailed Description
Journal Title
Intelligent Data Analysis
Year (definitive publication)
2009
Language
English
Country
Netherlands
More Information
--
Web of Science®
Scopus
Google Scholar
This publication is not indexed in Google Scholar
Abstract
Clustering quality or validation indices allow the evaluation of the quality of clustering in order to support the selection of a specific partition or clustering structure in its natural unsupervised environment, where the real solution is unknown or not available. In this paper, we investigate the use of quality indices mostly based on the concepts of clusters' compactness and separation, for the evaluation of clustering results (partitions in particular). This work intends to offer a general perspective regarding the appropriate use of quality indices for the purpose of clustering evaluation. After presenting some commonly used indices, as well as indices recently proposed in the literature, key issues regarding the practical use of quality indices are addressed. A general methodological approach is presented which considers the identification of appropriate indices thresholds. This general approach is compared with the simple use of quality indices for evaluating a clustering solution.
Acknowledgements
--
Keywords
Cluster validation; Validation indices; Quality indices; Clustering
Fields of Science and Technology Classification
- Computer and Information Sciences - Natural Sciences