An integrated approach of feature selection and parameter optimisation of kernel to enhance the performance of support vector machine.
Balakrishnan SarojiniPublished in: Int. J. Commun. Networks Distributed Syst. (2015)
Keyphrases
- support vector machine
- feature selection
- kernel parameters
- support vector
- kernel function
- gaussian kernel
- kernel methods
- tuning parameters
- feature space
- multi class
- class separability
- polynomial kernels
- svm classifier
- small sample
- support vector machine svm
- text classification
- svm classification
- optimal parameters
- machine learning
- k nearest neighbor
- text categorization
- kernel machines
- string kernels
- feature vectors
- rbf kernel
- genetic algorithm
- multiple kernel learning
- feature ranking
- recursive feature elimination
- selected features
- feature set
- mutual information
- dimensionality reduction
- classification accuracy
- classification method
- high dimensionality
- radial basis function
- hyperplane
- kernel matrix
- feature selection algorithms
- support vector regression
- generalization ability
- neural network
- parameter values
- feature subset
- dimension reduction
- kernel learning
- ls svm
- high dimensional
- model selection
- decision function
- microarray data
- feature extraction
- kernel pca
- maximum margin
- gene selection
- multi task
- parameter settings