摘要
通过对模糊C-均值聚类算法的研究,用遗传算法的相关知识对其进行优化与改进.并使用著名的IRIS数据集分别对传统的模糊C-均值聚类算法和用遗传算法改进后的模糊C-均值聚类算法进行测试、比较.实验结果表明,用遗传算法改进后的模糊C-均值聚类算法比传统的模糊C-均值聚类算法更加准确、高效.这将为以后的聚类分析研究工作提供一定的帮助.
It is optimized and improved with the related knowledge of genetic algorithm through the research on the c-means clustering algorithm. The famous IRIS data is used to respectively test and compare the traditional c-means clustering algorithm and the c-means clustering algorithm improved by genetic algorithm. The results show that the c-means clustering algorithm improved by genetic algorithm is more accurate and efficient than traditional c-means clustering algorithm. Which provides some help for the future research work of clustering analysis.
出处
《吉林化工学院学报》
CAS
2012年第11期124-126,共3页
Journal of Jilin Institute of Chemical Technology
