Kernel Canonical Discriminant Analysis Based on Variable Selection.
Seiichi IkedaYoshiharu SatoPublished in: J. Adv. Comput. Intell. Intell. Informatics (2009)
Keyphrases
- variable selection
- discriminant analysis
- kernel discriminant analysis
- discriminant subspace
- kernel fisher discriminant analysis
- linear discriminant analysis
- dimension reduction
- input variables
- class separability
- cross validation
- face recognition
- feature extraction
- high dimensional
- linear models
- principal component analysis
- kernel function
- ls svm
- support vector
- subspace learning
- model selection
- high dimensional data
- fisher discriminant analysis
- graph embedding
- dimensionality reduction methods
- feature selection
- dimensionality reduction
- cluster analysis
- kernel methods
- feature space
- kernel matrix
- kernel trick
- kernel learning
- pattern recognition
- scatter matrices
- learning tasks
- supervised learning
- machine learning