计算机工程与应用2012，Vol.48Issue(3)：189-191,3.DOI:10.3778/j.issn.1002-8331.2012.03.056
一种自适应权值的PCA算法
Adaptively weighted PCA algorithm
摘要
Abstract
Considering the sensitivity of PCA to outliers, a new adaptive weighted PCA is proposed to improve the robustness. Based on PCA, an optimization model by minimizing the weighted reconstruction error is constructed. Information entropy is introduced to adjust the weight of each sample's reconstruction error. An iterative optimization algorithm is used to solve the model. Experiment results on Yale face database and UCI data sets show the robustness and recognition of the method.关键词
特征提取/主成分分析/加权主成分分析/重建误差/鲁棒性Key words
feature extraction/ Principal Component Analysis (PCA)/ Weighted Principal Component Analysis (WPCA)/ reconstruction error/ robustness分类
信息技术与安全科学引用本文复制引用
杨开睿,孟凡荣,梁志贞..一种自适应权值的PCA算法[J].计算机工程与应用,2012,48(3):189-191,3.基金项目
国家自然科学基金(No.50674086,61003169). （No.50674086,61003169）
