Feature Space Interpretation of SVMs with Indefinite Kernels.
Bernard HaasdonkPublished in: IEEE Trans. Pattern Anal. Mach. Intell. (2005)
Keyphrases
- feature space
- kernel function
- kernel methods
- support vector
- polynomial kernels
- feature selection
- support vector machine
- input space
- classification accuracy
- hyperplane
- feature vectors
- high dimensional feature space
- feature extraction
- support vectors
- kernel space
- high dimensionality
- decision functions
- rbf kernel
- kernel principal component analysis
- mean shift
- image representation
- low dimensional
- high dimensional
- feature set
- training set
- positive definite
- support vector machine svm
- kernel trick
- principal component analysis
- dot product
- high dimension
- svm classification
- svm classifier
- dimension reduction
- kernel learning
- linear discriminant analysis
- kernel machines
- multiple kernel learning
- kernel matrix
- visual words
- training samples
- image retrieval
- kernel pca
- linear svm
- machine learning
- multiple kernel
- dimensionality reduction
- data points
- training data
- similarity measure
- margin maximization
- mercer kernels