基于链接的模糊聚类集成方法

针对多数聚类集成方法忽视潜在信息或获取潜在信息方法复杂这一缺点,提出一种基于链接的模糊聚类集成方法。该算法首先利用模糊聚类算法建立集成信息矩阵,然后使用相应的链接方法将集成信息矩阵转化为反映数据相关性的权重图,最后运用图划分技术得到最终结果。实验结果表明,新提出的算法可以有效地获取潜在信息,同时提高聚类质量。

A Link-Based Fuzzy Clustering Ensemble

A link-based fuzzy cluster ensemble (LBFCE) is proposed to solve the problem that many clustering ensemble methods ignore the underlying information or acquire the underlying information by complex approaches. In the LBFCE, an ensemble information matrix is first built by primarily exploiting the results of fuzzy clustering, this matrix is then transformed into a weighted graph with data relations by appropriate link analysis, and at last a graph partitioning algorithm is employed to get the final clustering results. Experimental results show that the LBFCE algorithm may obtain the underlying information effectively and improve clustering performance.