现代电子技术
現代電子技術
현대전자기술
MODERN ELECTRONICS TECHNIQUE
2007年
2期
152-153,156
,共3页
kernel clustering%maximum entropy%KMEC
With the development of Support Vector Machine (SVM),the "kernel method" has been studied in a general way.In this paper,we present a novel Kernel-based Maximum Entropy Clustering algorithm (KMEC).By using mercer kernel functions,the proposed algorithm is firstly map the data from their original space to high dimensional space where the data are expected to be more separable,then perform MEC clustering in the feature space.The experimental results show that the proposed method has better performance in the non-hyperspherical and complex data structure.
