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基于密度调整的改进自适应谱聚类算法

DOI: 10.13195/j.kzyjc.2013.0660, PP. 1683-1687

Keywords: 谱聚类,密度调整,自适应,尺度参数,多重尺度数据集

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Abstract:

针对谱聚类存在构造相似度矩阵时对尺度参数敏感以及处理多重尺度数据集效果不理想的缺陷,提出一种基于密度调整的改进自适应谱聚类算法.该算法将样本点所处领域的密度引入谱聚类,利用密度差来调整样本点之间的相似度,使其更符合实际簇类中样本点间的内在关系,在一定程度上解决了多尺度聚类问题;同时,通过样本点的近邻距离自适应得到尺度参数,使算法对尺度参数相对不敏感.仿真实验验证了所提出算法的有效性和优越性.

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