Sparse data-dependent kernel principal component analysis based on least squares support vector machine for feature extraction and recognition.
Jun-Bao LiHuijun GaoPublished in: Neural Comput. Appl. (2012)
Keyphrases
- data dependent
- kernel principal component analysis
- feature extraction
- high dimensional
- discriminant analysis
- ls svm
- preprocessing
- kernel pca
- principal component analysis
- feature space
- feature vectors
- kernel function
- pattern recognition
- principal components
- face recognition
- image processing
- linear discriminant analysis
- image classification
- dimension reduction
- hash functions
- kernel matrix
- dimensionality reduction
- reproducing kernel hilbert space
- kernel methods
- least squares