Trace Ratio Criterion for Feature Extraction in Classification | Zendy

Guoqi Li | Zendy; Changyun Wen | Zendy; Wei Wei | Zendy; Yi Xu | Zendy; Jie Ding | Zendy; Guangshe Zhao | Zendy; Luping Shi | Zendy

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Trace Ratio Criterion for Feature Extraction in Classification

Author(s) -

Guoqi Li,

Changyun Wen,

Wei Wei,

Yi Xu,

Jie Ding,

Guangshe Zhao,

Luping Shi

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/725204

Subject(s) - pattern recognition (psychology) , subspace topology , trace (psycholinguistics) , linear discriminant analysis , mathematics , feature (linguistics) , feature extraction , artificial intelligence , set (abstract data type) , computer science , philosophy , linguistics , programming language

A generalized linear discriminant analysis based on trace ratio criterion algorithm (GLDA-TRA) is derived to extract features for classification. With the proposed GLDA-TRA, a set of orthogonal features can be extracted in succession. Each newly extracted feature is the optimal feature that maximizes the trace ratio criterion function in the subspace orthogonal to the space spanned by the previous extracted features

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