An approach to non-linear principal components analysis using radially symmetric kernel functions.
Andrew R. WebbPublished in: Stat. Comput. (1996)
Keyphrases
- principal components analysis
- kernel function
- radially symmetric
- support vector machine
- kernel trick
- support vector
- straight line
- dimensionality reduction methods
- kernel methods
- feature space
- input space
- dimensionality reduction
- linear discriminant analysis
- omni directional
- principal components
- kernel matrix
- covariance matrix
- kernel learning
- support vectors
- feature extraction
- high dimensional feature space
- gaussian kernels
- high dimensional
- multiple kernel learning
- feature selection
- feature vectors
- kernel pca
- reproducing kernel hilbert space
- neural network
- training data
- kernel matrices
- machine learning
- face recognition
- line segments