By Topic

A Genetic Clustering Technique Using a New Line Symmetry Based Distance Measure

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Saha, S. ; Indian Stat. Inst., Kolkata ; Bandyopadhyay, S.

In this paper, an evolutionary clustering technique is described that uses a new line symmetry based distance measure. Kd-tree based nearest neighbor search is used to reduce the complexity of finding the closest symmetric point. Adaptive mutation and crossover probabilities are used. The proposed GA with line symmetry distance based (GALSD) clustering technique is able to detect any type of clusters, irrespective of their geometrical shape and overlapping nature, as long as they possess the characteristic of line symmetry. GALSD is compared with existing well-known K-means algorithm. Five artificially generated and two real-life data sets are used to demonstrate its superiority.

Published in:

Advanced Computing and Communications, 2007. ADCOM 2007. International Conference on

Date of Conference:

18-21 Dec. 2007