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...

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Bibliographic Details
Main Authors: Nie, Feiping, Xiang, Shiming, Liu, Yun, Hou, Chenping, Zhang, Changshui
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2013
Subjects:
Online Access:https://hdl.handle.net/10356/105687
http://hdl.handle.net/10220/17576
http://dx.doi.org/10.1016/j.patrec.2011.11.028
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Institution: Nanyang Technological University
Language: English

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