Orthogonal vs. uncorrelated least squares discriminant analysis for feature extraction

In this paper, a new discriminant analysis for feature extraction is derived from the perspective of least squares regression. To obtain great discriminative power between classes, all the data points in each class are expected to be regressed to a single vector, and the basic task is to find a tran...

全面介紹

Saved in:
書目詳細資料
Main Authors: Nie, Feiping, Xiang, Shiming, Liu, Yun, Hou, Chenping, Zhang, Changshui
其他作者: School of Electrical and Electronic Engineering
格式: Article
語言:English
出版: 2013
主題:
在線閱讀:https://hdl.handle.net/10356/105687
http://hdl.handle.net/10220/17576
http://dx.doi.org/10.1016/j.patrec.2011.11.028
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
機構: Nanyang Technological University
語言: English