Generating compact rough cluster descriptions using an evolutionary algorithm

There are no files associated with this record.

Title Generating compact rough cluster descriptions using an evolutionary algorithm
Author Vogts, Kevin; Pope, Nigel Kenneth
Publication Title Genetic and Evolutionary Computation Conference Seattle,WA, USA, June 26-30, 2004 Proceedings, Part II
Year Published 2004
Place of publication USA
Publisher Springer
Abstract Cluster analysis is a technique used to group objects into clusters such that similar objects are grouped together in the same cluster. Early methods were derived from multivariate statistics. Some newer methods are based on rough sets, introduced by Pawlak [3], [4]. An extension of rough sets to rough clusters was introduced in [5]. The lower approximation (LA) of a rough cluster contains objects that only belong to that cluster, and the upper approximation (UA) contains objects that may belong to more than one cluster. An EA can be used to find a set of lower approximations of rough clusters that provide the most comprehensive coverage of the data set with the minimum number of clusters.
Peer Reviewed No
Published Yes
Publisher URI
ISBN 978-3-540-22343-6
Conference name Genetic and Evolutionary Computation – GECCO 2004
Location Seattle
Date From 2004-06-26
Date To 2004-06-30
Date Accessioned 2010-04-09
Language en_AU
Faculty Griffith Business School
Subject Marketing Research Methodology
Publication Type Conference Publications (Extract Paper)
Publication Type Code e3

Show simple item record

Griffith University copyright notice