On the equivalence of Kernel Fisher discriminant analysis and Kernel Quadratic Programming Feature Selection.
Irene Rodríguez-LujánCarlos Santa CruzRamón HuertaPublished in: Pattern Recognit. Lett. (2011)
Keyphrases
- quadratic programming
- kernel fisher discriminant analysis
- kernel methods
- feature selection
- support vector machine
- discriminant analysis
- feature space
- kernel principal component analysis
- kernel pca
- optimal kernel
- support vector
- kernel function
- linear programming
- face recognition
- feature extraction
- kernel learning
- kernel matrix
- ls svm
- machine learning
- text classification
- classification accuracy
- multiple kernel learning
- dimensionality reduction
- svm classifier
- feature subset
- dimension reduction
- reproducing kernel hilbert space
- support vector machine svm
- principal component analysis
- data sets
- feature set
- linear discriminant analysis
- graph kernels
- k nearest neighbor
- support vector regression
- multi task
- input space
- principal components
- special case
- spectral clustering
- preprocessing
- multiple kernel
- kernel matrices
- training data
- least squares