Multiple Kernel-Based Discriminant Analysis via Support Vectors for Dimension Reduction.
Shan ZengChongjun GaoXiuying WangLiang JiangDagan FengPublished in: IEEE Access (2019)
Keyphrases
- discriminant analysis
- dimension reduction
- linear discriminant analysis
- support vector
- support vectors
- principal component analysis
- feature extraction
- partial least squares
- support vector machine
- face recognition
- cluster analysis
- kernel function
- feature space
- kernel methods
- variable selection
- dimensionality reduction
- svm classifier
- high dimensional data
- feature selection
- support vector machine svm
- low dimensional
- scatter matrices
- kernel matrix
- hyperplane
- input space
- manifold learning
- high dimensional
- training examples
- kernel pca
- principal components
- face images
- training samples
- training data
- pattern recognition
- image processing
- singular value decomposition
- null space
- fisher discriminant analysis
- nearest neighbor
- clustering algorithm
- computer vision
- semi supervised learning
- dimensionality reduction methods