Sparse and kernel OPLS feature extraction based on eigenvalue problem solving.
Sergio Muñoz-RomeroJerónimo Arenas-GarcíaVanessa Gómez-VerdejoPublished in: Pattern Recognit. (2015)
Keyphrases
- feature extraction
- sparse kernel
- feature space
- additive models
- kernel function
- kernel principal component analysis
- preprocessing
- kernel matrices
- kernel methods
- knowledge acquisition
- high dimensional
- multiple kernel
- case based reasoning
- sparse data
- support vector
- artificial intelligence
- pattern classification
- feature selection
- sparse representation
- feature vectors
- covariance matrix
- input space
- image classification
- regularized least squares
- explanation based learning
- face recognition
- linear feature extraction
- dimension reduction
- discriminant analysis
- positive semi definite
- manifold learning
- image processing
- random projections
- frequency domain
- component analysis
- kernel pca
- relevance vector machine
- wavelet transform
- principle component analysis
- feature extractors
- feature set
- analogical reasoning
- dimensionality reduction
- kernel machines
- multiple kernel learning
- gaussian processes
- sparse coding
- linear discriminant analysis
- information processing
- support vector machine svm