计算机应用研究2012，Vol.29Issue(6)：2126-2128,2131,4.DOI:10.3969/j.issn.1001-3695.2012.06.032
一种基于p-Laplacian的谱聚类维数约简算法
Dimensionality reduction algorithm based on p-Laplacian in spectral clustering
摘要
Abstract
In recent years, spectral analysis approaches have received much attention in machine learning and data mining areas, due to their rich theoretical foundations. This paper addressed the problem of Laplacian in spectral clustering, which couldn' t get ideally graph cut criterion, by introducing the p-Laplacian operator, this paper proposed a new dimensionality reduction algorithm based on p-Laplacian. The experimental results denote that, the approach can get a approximation of the optimal graph cut, and can accurately get embedding mapped of original data in low dimensionality space.关键词
谱聚类/图切判据/维数约简/p-LaplacianKey words
spectral clustering/graph cut criterion/dimensionality reduction/p-Laplacian分类
信息技术与安全科学引用本文复制引用
石远超,马宏,李海涛..一种基于p-Laplacian的谱聚类维数约简算法[J].计算机应用研究,2012,29(6):2126-2128,2131,4.基金项目
国家"863"计划资助项目(2011AA010603) （2011AA010603）
