Variable Selection for Kernel Classifiers: A Feature-to-Input Space Approach.
Surette OosthuizenSarel SteelPublished in: GfKl (2008)
Keyphrases
- variable selection
- input space
- high dimensional
- high dimensional data
- kernel classifiers
- dimensionality reduction
- low dimensional
- cross validation
- input variables
- feature space
- dimension reduction
- data points
- kernel function
- model selection
- input data
- hyperplane
- training set
- high dimensionality
- class labels
- feature vectors
- ls svm
- machine learning
- multi class
- support vector
- feature selection
- feature set
- principal component analysis
- support vectors
- kernel matrix