Parameter determination of support vector machine and feature selection using simulated annealing approach.
Shih-Wei LinZne-Jung LeeShih-Chieh ChenTsung-Yuan TsengPublished in: Appl. Soft Comput. (2008)
Keyphrases
- parameter determination
- feature selection
- support vector machine
- simulated annealing
- model selection
- multi class
- support vector
- support vector regression
- simulated annealing algorithm
- small sample
- support vector machine svm
- svm classifier
- kernel methods
- metaheuristic
- text classification
- evolutionary algorithm
- feature space
- genetic algorithm
- text categorization
- machine learning
- knn
- classification accuracy
- feature set
- mutual information
- k nearest neighbor
- feature selection algorithms
- hill climbing
- solution quality
- kernel function
- classification method
- feature extraction
- svm classification
- generalization ability
- stochastic search
- training data
- radial basis function
- input features
- feature ranking
- information gain
- data sets
- microarray data
- high dimensionality
- tabu search
- regression model
- feature vectors
- recursive feature elimination
- feature subset
- dimension reduction
- unsupervised feature selection
- global optimum
- genetic algorithm ga
- data mining
- irrelevant features
- reversible jump mcmc
- gene expression data
- optimization method
- objective function
- decision trees
- neural network