Variable Selection for Kernel Classification.
S. J. SteelNelmarie LouwSurette BiermanPublished in: Commun. Stat. Simul. Comput. (2011)
Keyphrases
- variable selection
- cross validation
- model selection
- dimension reduction
- support vector
- leave one out cross validation
- high dimensional
- input variables
- pattern recognition
- feature extraction
- linear models
- logistic regression models
- feature space
- classification accuracy
- kernel learning
- image classification
- support vector machine svm
- preprocessing
- text classification
- neural network
- principal component analysis
- high dimensional data
- feature selection
- supervised learning
- image processing
- nearest neighbor
- feature vectors
- decision trees
- machine learning
- group lasso
- high dimensionality
- logistic regression
- unsupervised learning
- feature set