A hybrid genetic based clustering algorithm

A hybrid genetic based clustering algorithm, called HGA-clustering, is proposed in this article to explore the proper clustering of data sets. The presented algorithm, with the cooperation of tabu list and aspiration criteria, can achieve harmony between population diversity and convergence speed. Its superiority over K-means algorithm and another genetic algorithm based clustering approach is extensively demonstrated for artificial and real life data sets.

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