计算机科学 ›› 2022, Vol. 49 ›› Issue (9): 70-75.doi: 10.11896/jsjkx.210800203
柴慧敏1,2, 张勇2, 方敏1
CHAI Hui-min1,2, ZHANG Yong2, FANG Min1
摘要： 针对采用聚类算法进行目标分群时需要给出聚类个数和对初始中心选择敏感的问题,提出了一种基于目标特征相似度聚类的分群方法。该方法首先计算目标间的相似度值,构建相似度矩阵;然后计算相似度矩阵的连通分支,获取群中心结构和孤立目标点,识别的群中心结构个数为聚类个数;最后将不属于群中心结构和孤立点的目标归类到与其最相近的群中心结构中,使得聚类过程不再过多地依赖于聚类初始中心的选择。实验结果表明,所提方法能够正确识别出多种形态的群中心结构,并能检测出孤立点,且目标聚类正确率均高于其他4种聚类算法。
中图分类号:
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