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.
Index Terms—Genetic algorithm, clustering, hybrid learning,
high-dimensional space;
Barry Juans and Sheng-Uei Guan are with the Department of Computer
Science and Software Engineering, Xi’an Jiaotong-Liverpool University,
Suzhou, China (e-mail: barry.juans10@student.xjtlu.edu.cn; Steven.Guan@
xjtlu.edu.cn).
Cite:BarryJuans and Sheng-Uei Guan, "Genetic Algorithm Based Split-Fusion Clustering," International Journal of Machine Learning and Computing vol.2, no. 6, pp. 782-785, 2012.