南京师大学报（自然科学版）2016，Vol.39Issue(1)：14-20,7.DOI:10.3969/j.issn.1001-4616.2016.01.002
一种基于迭代分解的增量流形学习算法
An Incremental Manifold Learning Algorithm Based on Iterative Decomposition
摘要
Abstract
Manifold learning is used to discover intrinsic low-dimensional manifolds of data points embedded in high-dimensional spaces,which is useful in nonlinear dimension reduction. In recent years,new data points come continually, which will change the existing data points' neighborhoods and their local distributions. Tranditional methods cannot discover intrinsic information of high dimensional data streams effectively. To solve this problem,we propose an Incre?mental Manifold Learning Algorithm Based on Iterative Decomposition(IMLID),which can detect the change of mani?fold and improve the classification accuracy of the feature set sampling in the real world. Experiments on real-life datasets validate the effectiveness of the proposed method which has important significance and extensive application value in pattern recognition and so on.关键词
流形学习/迭代分解/增量流形学习Key words
manifold learning/iterative decomposition/incremental learning分类
信息技术与安全科学引用本文复制引用
谈超,吉根林..一种基于迭代分解的增量流形学习算法[J].南京师大学报（自然科学版）,2016,39(1):14-20,7.基金项目
江苏省高校自然科学基金(15KJB520022)、国家自然科学基金(41471371). （15KJB520022）
