基于调和平均测地线核的局部线性嵌入算法

J4 ›› 2010, Vol. 45 ›› Issue (7): 55-59.

基于调和平均测地线核的局部线性嵌入算法

曾文赋1,黄添强1,2,李凯1,余养强1,郭躬德1,2

1. 福建师范大学数学与计算机科学学院, 福建福州 350007;
2. 福建师范大学网络安全与密码技术重点实验室, 福建福州 350007

收稿日期:2010-04-02 出版日期:2010-07-16 发布日期:2010-09-06
作者简介:曾文赋(1985-),男,硕士研究生,研究方向为机器学习.Email:zwf0923@126.com
基金资助:
福建省自然科学基金资助项目(2007J0016, 2008J04004);福建省青年人才创新基金资助项目(2006F3045);福建省高校服务海西建设重点资助项目(201008)

A local linear emedding agorithm based on harmonicmean geodesic kernel

ZENG Weng-fu1, HUANG Tian-qiang1,2, LI Kai1, YU YANG-qiang1, GUO Gong-de1,2

1.School of Mathematics and Computer Science, Fujian Normal University, Fuzhou 350007, Fujian, China;
2. Key Laboratory of Network Security and Cryptology, Fujian Normal University, Fuzhou 350007,Fujian, China

Received:2010-04-02 Online:2010-07-16 Published:2010-09-06

摘要/Abstract

摘要：

为解决现有局部线性嵌入算法不适合处理非均匀分布数据和未利用距离远点信息的问题,首先引入测地线距离,以便能利用远点信息;然后使用调和平均规范化构造调和平均测地线核矩阵,使算法能更好地处理分布不均匀数据并具有鲁棒性。在UCI数据集上的实验结果表明,改进后的算法能够取得比局部线性嵌入算法更好的降维效果。

关键词: 局部线性嵌入;调和平均;核方法;测地线;流形学习

Abstract:

An improved algorithm was proposed to overcome the shortcomings of the existing local linear embedding algorithm that was not suitable for the nonuniform distribution data and not use the information of distant points. First, to improv the accuracy of the algorithm the geodesic-distance was introduced into the new algorithm in order to take advantage of the information of distant points, and then the harmonic-mean geodesic-kernel matrix was constructed by using the harmonic-mean standardization,which could process robustly non-uniform distribution data. The results of the experiments on UCI data sets showed that the improved algorithm could obtain better performance than the classical local linear embedding algorithm on dimension reduction.

Key words: local linear embedding; harmonic mean; kernel trick; geodesic; manifold learning

曾文赋1,黄添强1,2,李凯1,余养强1,郭躬德1,2. 基于调和平均测地线核的局部线性嵌入算法[J]. J4, 2010, 45(7): 55-59.

ZENG Weng-fu1, HUANG Tian-qiang1,2, LI Kai1, YU YANG-qiang1, GUO Gong-de1,2. A local linear emedding agorithm based on harmonicmean geodesic kernel[J]. J4, 2010, 45(7): 55-59.

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