摘要
提出了一种增量式模糊聚类技术的改进算法,该算法仅对新增数据计算相似系数而直接聚类,其结果和动态聚类算法相同;该算法较好地解决了新增数据的聚类及类属问题,提高了模糊聚类算法的收敛速度,实验结果证实改进了算法的高可靠性。
The article puts forward an improved increasable fuzzy clustering algorithm. The algorithm only calculates similar coefficient of increased data. Its result is the same as dynamic clustering algorithm. The clustering and the class attribute problem of the new data are reasonably solved with the improved algorithm, and the convergence speed of fuzzy clustering algorithm is improved. The result of the experiment presented in the paper illustrates that the improved algorithm is reliable.
出处
《黄石理工学院学报》
2006年第4期37-39,共3页
Journal of Huangshi Institute of Technology
关键词
模糊聚类
增量式算法
模糊C-均值算法
fuzzy clustering
increasable algorithm
fuzzy c- means clustering algorithm(FCM)