A novel formulation of orthogonal polynomial kernel functions for SVM classifiers: The Gegenbauer family.
Luis Carlos PadiernaMartín CarpioAlfonso Rojas DomínguezHéctor PugaHéctor J. Fraire H.Published in: Pattern Recognit. (2018)
Keyphrases
- kernel function
- svm classifier
- support vector machine
- support vector
- representer theorem
- polynomial kernels
- positive semidefinite
- kernel learning
- kernel methods
- input space
- support vectors
- feature space
- high dimensional feature space
- support vector regression
- special case
- kernel matrix
- positive definite
- svm classification
- hyperplane
- semidefinite programming
- high dimensional
- multi class
- data sets
- multiple kernel learning
- support vector machine svm
- reproducing kernel hilbert space
- image classification
- feature set
- training data
- feature selection
- feature vectors
- distance measure
- string kernels
- semi supervised
- gaussian kernels
- computer vision