Many pattern recognition applications involve the treatment of high-dimensional data and the small sample size problem. Principal component analysis (PCA) is a common used dimension reduction technique. Linear discriminate analysis (LDA) is often employed for classification. PCA plus LDA is a famous
A direct LDA algorithm for high-dimensional data — with application to face recognition
✍ Scribed by Hua Yu; Jie Yang
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 80 KB
- Volume
- 34
- Category
- Article
- ISSN
- 0031-3203
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