Evolutionary Algorithms for Robust Density-Based Data Clustering. (17th January 2013)

• Record Type: Journal Article
• Authors: Banerjee, Amit
• Other Names: Krohling R. A. Academic Editor.; Pandey R. Academic Editor.
• Is Part Of: ISRN computational mathematics. Volume 2013(2013)
• Publication Date: 2013-01-17
• Subjects: Numerical analysis -- Periodicals; Mathematics -- Data processing -- Periodicals; Mathematics -- Data processing; Numerical analysis; Electronic journals; Periodicals; 510
• DOI: 10.1155/2013/931019
• Languages: English
• ISSNs: 2090-7842

Abstract

Abstract : Density-based clustering methods are known to be robust against outliers in data; however, they are sensitive to user-specified parameters, the selection of which is not trivial. Moreover, relational data clustering is an area that has received considerably less attention than object data clustering. In this paper, two approaches to robust density-based clustering for relational data using evolutionary computation are investigated.