基于改进遗传算法的K-means聚类分析 |
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引用本文: | 王颖,刘建平. 基于改进遗传算法的K-means聚类分析[J]. 工业控制计算机, 2011, 24(8): 78-79 |
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作者姓名: | 王颖 刘建平 |
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作者单位: | 浙江理工大学信息电子学院,浙江杭州,310018 |
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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,...
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关 键 词: | 遗传算法 K-means 聚类分析 数据挖掘 |
Clustering Analysis of K-means Based on Improved Genetic Algorithm |
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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. |
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Keywords: | genetic algorithm K-means clustering analysis data mining |
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