计算机工程与应用Issue(2)：65-69,111,6.DOI:10.3778/j.issn.1002-8331.1312-0281
多核模糊聚类
Multiple kernel fuzzy clustering
摘要
Abstract
Because the fuzzy clustering based on single kernel function has some limitation on performance, a new multiple-kernel fuzzy clustering is put forward. The new multiple kernel is constituted by Gaussian kernel, Sigmoid kernel and polynomial kernel. Gaussian kernel is wildly used in KFCM. It can be demonstrated that sigmoid kernel derived from neu-ral network has good global classification performance, as well as polynomial kernel. The new multiple kernel combines the advantage of them. The experimental results prove that the fuzzy clustering with multiple kernel is much better than with single kernel on performance.关键词
多核/模糊核聚类/高斯核/Sigmoid核/多项式核函数Key words
multiple kernel/Kernel Fuzzy Clustering(KFCM)/Gaussian kernel/Sigmoid kernel/polynomial kernel分类
信息技术与安全科学引用本文复制引用
戴思薇,吴小俊,高翠芳..多核模糊聚类[J].计算机工程与应用,2016,(2):65-69,111,6.基金项目
111引智计划基金（No.B12018）。 （）
