【摘要】 K-means算法是聚类分析中的一种经典算法,但是K-means算法是一种局部搜索技术,受初始聚类中心的影响可能会过早收敛于最优解。而遗传算法具有良好的全局优化的能力,将遗传算法与K-means算法结合起来,能很好解决这一问题。在结合的过程中,又在最传统的遗传算法中改进染色体编码与适应度函数,从而优化k个中心点的选取,最后通过实验说明改进后的遗传算法能较好地提高聚类的质量。更多还原

【Abstract】 K-means algorithm is a local search technique,which is influenced by the original Clustering centers,may have convergence of the best results earlier.Genetic algorithm is able to improve the whole process,so combine the Genetic algorithm with K-means algorithm to solve this problem.During the combing,and improves the Chromosome coding and the fitness function based on the traditional genetic algorithm,optimized the choice of the center.更多还原