基于免疫克隆算法的LVQ聚类算法权值优化

计算机科学 ›› 2013, Vol. 40 ›› Issue (Z6): 27-28.

基于免疫克隆算法的LVQ聚类算法权值优化

张晓丹,黄海燕

华东理工大学信息科学与工程学院上海200237;华东理工大学信息科学与工程学院上海200237

出版日期:2018-11-16 发布日期:2018-11-16

Optimization of Weights of LVQ Clustering Algorithm Based on Immune Clonal Algorithm

ZHANG Xiao-dan and HUANG Hai-yan

Online:2018-11-16 Published:2018-11-16

摘要/Abstract

摘要： 学习矢量量化(LVQ)聚类算法存在严重的对初值敏感的问题,若初值的选择偏差太大,就不会产生好的聚类效果,致使聚类精准度不够。免疫克隆算法具有很强的群体搜索能力,将免疫克隆算法用于优化LVQ聚类算法的初值,并将改进得到的聚类算法用于对IRIS数据集进行分类。分类结果与标准的LVQ算法的比较表明,改进后的聚类算法在稳定性上有了较大幅度的提高。

关键词: LVQ聚类算法,免疫克隆算法,优化

Abstract: A major problem of learning vector quantization(LVQ) clustering algorithm is its sensitivity to the initialization,affecting the clustering precision．This paper fist introduced the theory of LVQ clustering algorithm,then used immune clonal algorithm to optimize the initial values of LVQ．And the paper used IRIS data to test this new method．Comparing the evolving LVQ with the standard LVQ,the experiment results indicate that the approach of LVQ based on immune clonal algorithm has obvious stability to initial weights．

Key words: LVQ clustering algorithm,Immune clonal algorithm,Optimization

张晓丹,黄海燕. 基于免疫克隆算法的LVQ聚类算法权值优化[J]. 计算机科学, 2013, 40(Z6): 27-28. https://doi.org/

ZHANG Xiao-dan and HUANG Hai-yan. Optimization of Weights of LVQ Clustering Algorithm Based on Immune Clonal Algorithm[J]. Computer Science, 2013, 40(Z6): 27-28. https://doi.org/

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