Dynamic Partitional Clustering Using Evolution Strategies
C. Lee, and E. Antonsson. In Proceedings of the Third Asia Pacific Conference on Simulated Evolution and Learning, page 25--27. (2000)
Abstract
A novel evolution strategy implementing variable length genomes is developed to address the problem of dynamic partitional clustering. As opposed to static, dynamic partitional clustering does not require the a priori specification of the number of clusters. Results of the algorithm are presented and discussed for 2-D touching and non-touching cluster test cases.
Description
Dynamic Partitional Clustering Using Evolution Strategies
%0 Conference Paper
%1 Lee_dynamicpartitional
%A Lee, C.-Y.
%A Antonsson, E.K.
%B In Proceedings of the Third Asia Pacific Conference on Simulated Evolution and Learning
%D 2000
%K 2009 clustering seminar
%P 25--27
%T Dynamic Partitional Clustering Using Evolution Strategies
%U http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.9974
%X A novel evolution strategy implementing variable length genomes is developed to address the problem of dynamic partitional clustering. As opposed to static, dynamic partitional clustering does not require the a priori specification of the number of clusters. Results of the algorithm are presented and discussed for 2-D touching and non-touching cluster test cases.
@inproceedings{Lee_dynamicpartitional,
abstract = {A novel evolution strategy implementing variable length genomes is developed to address the problem of dynamic partitional clustering. As opposed to static, dynamic partitional clustering does not require the a priori specification of the number of clusters. Results of the algorithm are presented and discussed for 2-D touching and non-touching cluster test cases.},
added-at = {2009-11-12T14:17:17.000+0100},
author = {Lee, C.-Y. and Antonsson, E.K.},
biburl = {https://www.bibsonomy.org/bibtex/21bc03cd61acf1b6d4dd88c1a1799456a/k.e.},
booktitle = {In Proceedings of the Third Asia Pacific Conference on Simulated Evolution and Learning},
description = {Dynamic Partitional Clustering Using Evolution Strategies},
interhash = {e508018227ac13c15b38f85540b51b8a},
intrahash = {1bc03cd61acf1b6d4dd88c1a1799456a},
keywords = {2009 clustering seminar},
pages = {25--27},
timestamp = {2009-11-12T14:17:17.000+0100},
title = {Dynamic Partitional Clustering Using Evolution Strategies},
url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.9974},
year = 2000
}