An Optimized Clustering Algorithm Using Improved Gene Expression Programming
How to find the better initial center points plays an important role in many clustering applications. In our paper, we propose the novel chromosome representation according to extended traditional gene expression programming used in GEP-ADF. It is aimed at improving the performance of GEP to obtain center points more accurately. Experimental results show that our new algorithm has good performance in clustering and the three real world datasets compared with the other two algorithms.
KeywordsCenter points Novel chromosome representation Gene expression programming GEP-ADF
This work is supported by the National Natural Science Foundation of China with the Grant No. 61573157, the Fund of Natural Science Foundation of Guangdong Province of China with the Grant No. 2014A030313454.
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