In spite of the popularity of Fisher discriminant analysis in the realm of feature extraction and pattern classification, it is beyond the capability of Fisher discriminant analysis to extract nonlinear structures from the data. That is where the kernel Fisher discriminant algorithm sets in the scen
β¦ LIBER β¦
Essence of kernel Fisher discriminant: KPCA plus LDA
β Scribed by Jian Yang; Zhong Jin; Jing-yu Yang; David Zhang; Alejandro F Frangi
- Publisher
- Elsevier Science
- Year
- 2004
- Tongue
- English
- Weight
- 143 KB
- Volume
- 37
- Category
- Article
- ISSN
- 0031-3203
No coin nor oath required. For personal study only.
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apply the "kernel trick" to obtain a non-linear variant of Fisher's linear discriminant analysis method, demonstrating state-of-the-art performance on a range of benchmark data sets. We show that leave-one-out cross-validation of kernel Fisher discriminant classiΓΏers can be implemented with a comput