doi: 10.7763/IJMLC.2012.V2.236
Genetic Algorithm Based Split-Fusion Clustering
- Department of Computer Science and Software Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China.
Abstract
We introduce a new clustering algorithm which is based on the combination of GA and a new technique called split-and-fusion. GA is used to find the initial cluster while split and fusion refines the cluster by continuously breaking apart and merging patterns existing in the cluster. The whole process is repeated until all patterns have been clustered. The algorithm then merges the smallest-sized cluster with other clusters until termination condition is met. In the last step, a heuristic equation is used to evaluate the termination criteria. Experimental results show that the algorithm is accurate in clustering real-world datasets such as Iris and Wine datasets.
Keywords
- Genetic algorithm
- clustering
- hybrid learning
- high-dimensional space;
How to Cite
BarryJuans and Sheng-Uei Guan, "Genetic Algorithm Based Split-Fusion Clustering," International Journal of Machine Learning, vol. 2, no. 6, pp. 782-785, 2012. https://doi.org/10.7763/IJMLC.2012.V2.236
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).