Feature selection and fast training of subspace based support vector machines.
Takuya KitamuraSyogo TakeuchiShigeo AbePublished in: IJCNN (2010)
Keyphrases
- support vector
- learning machines
- feature selection
- feature space
- training examples
- large margin classifiers
- linear svm
- support vector machine
- classification performances
- feature extraction
- logistic regression
- model selection
- classification accuracy
- dimensionality reduction
- svm classifier
- low dimensional
- kernel function
- ensemble learning
- kernel methods
- text categorization
- training set
- feature selection algorithms
- cross validation
- subspace learning
- training algorithm
- training process
- subspace clustering
- discriminative features
- machine learning
- feature set
- mutual information
- loss function
- knn
- decision function
- ls svm
- support vector classification
- generalization ability
- hyperplane
- feature subset
- supervised learning
- support vector regression
- multi class
- selected features
- maximum margin
- information gain
- linear subspace
- irrelevant features
- radial basis function
- feature subspace
- high dimensional
- high dimensional data
- text classification