期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2012
卷号：2
期号：10
出版社：S.S. Mishra
摘要：In clustering technique, the hard clustering membership values and o verlapping concept could not be identified along with non-convex problem. The proposed algorithm uses soft clustering to combine both Laplacians and multi ple kernels for clustering analysis. The algorithm is formulated on a Rayleigh quotient objective function. The bi-level optimization is an alternating minimization procedure; it is used to co nvert the hard clustering to soft clustering. The kernels and Laplacians co-efficient can be optimized automatically by using the methods semi-infinite programming and quadratic constraint quadratic programming .The kernel Laplacians algorithm uses to control the overlapping
关键词：Clustering; k-means; Data fusion; Data clustering; Soft clustering; hard clustering
