Evaluate Dissimilarity of Samples in Feature Space for Improving KPCA.
Xu YongDavid ZhangJian YangJin ZhongJingyu YangPublished in: Int. J. Inf. Technol. Decis. Mak. (2011)
Keyphrases
- feature space
- training samples
- kernel principal component analysis
- sample set
- training set
- feature vectors
- kernel methods
- sample space
- high dimensional feature space
- kernel function
- kernel pca
- dissimilarity measure
- classification accuracy
- input space
- feature selection
- input data
- high dimensional
- mean shift
- dimensionality reduction
- principal component analysis
- low dimensional
- support vector machine
- linear discriminant analysis
- feature set
- feature extraction
- kernel matrix
- data points
- dimension reduction
- hyperplane
- high dimensionality
- image representation
- support vectors
- lower dimensional
- pattern recognition
- machine learning
- feature subset
- supervised learning
- training examples
- training dataset
- face recognition
- data samples
- computer vision
- data sets