A new regularized linear discriminant analysis method to solve small sample size problems.
Wen-Sheng ChenPong Chi YuenJian HuangPublished in: Int. J. Pattern Recognit. Artif. Intell. (2005)
Keyphrases
- small sample size
- linear discriminant analysis
- high dimensionality
- dimension reduction
- sample size
- fisher criterion
- support vector machine svm
- discriminant analysis
- face recognition
- discriminant features
- null space
- dimensionality reduction
- principal component analysis
- high dimensional data
- high dimensional
- support vector
- scatter matrices
- subspace methods
- least squares
- linear discriminant
- discriminant information
- neural network
- optimization criterion
- similarity measure
- objective function
- microarray data
- gene expression data
- pattern recognition
- input image
- unsupervised learning