Dimensionality reduction by soft-margin support vector machine.
Ruipeng DongHua MengZhiguo LongHailiang ZhaoPublished in: ICA (2017)
Keyphrases
- soft margin
- dimensionality reduction
- support vector machine
- feature selection
- parameter selection
- support vector
- generalization ability
- feature space
- high dimensional data
- low dimensional
- principal component analysis
- feature extraction
- high dimensionality
- multi class
- high dimensional
- principal components
- svm classifier
- dimensionality reduction methods
- boosting algorithms
- input space
- kernel pca
- support vector machine svm
- pattern recognition
- kernel function
- perceptron algorithm
- machine learning
- kernel methods
- generalization error
- learning algorithm
- data points
- feature vectors
- k nearest neighbor
- linearly separable
- class conditional
- linear classifiers
- classification accuracy
- knn
- svm classification
- binary classification
- feature set
- hyperplane
- neural network