International Journal of Computational Intelligence Systems

Volume 4, Issue 1, February 2011, Pages 12 - 28

Experimental Comparison of Iterative Versus Evolutionary Crisp and Rough Clustering

Authors
Pawan Lingras, Manish Joshi
Corresponding Author
Pawan Lingras
Received 19 November 2009, Accepted 20 September 2010, Available Online 1 February 2011.
DOI
https://doi.org/10.2991/ijcis.2011.4.1.2How to use a DOI?
Keywords
Keywords: Rough Clustering, Crisp Clustering, GA based Clustering, Cluster Quality.
Abstract
Researchers have proposed several Genetic Algorithm (GA) based crisp clustering algorithms. Rough clustering based on Genetic Algorithms, Kohonen Self-Organizing Maps, K-means algorithm are also reported in literature. Recently, researchers have combined GAs with iterative rough clustering algorithms such as K-means and K-Medoids. Use of GAs makes it possible to specify explicit optimization of cluster validity measures. However, it can result in additional computing time. In this paper we compare results obtained using K-means, GA K-means, rough K-means, GA rough K-means and GA rough K-medoid algorithms. We experimented with a synthetic data set, a real world data set, and a standard dataset using a total within cluster variation, average precision, and execution time required as the criteria for comparison.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
4 - 1
Pages
12 - 28
Publication Date
2011/02
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
https://doi.org/10.2991/ijcis.2011.4.1.2How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Pawan Lingras
AU  - Manish Joshi
PY  - 2011
DA  - 2011/02
TI  - Experimental Comparison of Iterative Versus Evolutionary Crisp and Rough Clustering
JO  - International Journal of Computational Intelligence Systems
SP  - 12
EP  - 28
VL  - 4
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2011.4.1.2
DO  - https://doi.org/10.2991/ijcis.2011.4.1.2
ID  - Lingras2011
ER  -