Alzheimer disease classification using KPCA, LDA, and multi-kernel learning SVM.
Saruar AlamGoo-Rak KwonPublished in: Int. J. Imaging Syst. Technol. (2017)
Keyphrases
- kernel learning
- kernel function
- kernel principal component analysis
- support vector
- kernel methods
- kernel matrix
- support vector machine svm
- feature space
- linear discriminant analysis
- support vector machine
- multiple kernel learning
- svm classification
- feature vectors
- svm classifier
- support vector regression
- support vectors
- feature selection
- feature extraction
- face recognition
- kernel pca
- high dimensional feature space
- classification method
- subspace methods
- training set
- classification accuracy
- feature set
- machine learning
- dimensionality reduction
- principal component analysis
- generalization ability
- pattern classification
- dimension reduction
- cost sensitive
- discriminant analysis
- text classification
- metric learning
- knn
- topic models
- multi class
- image classification
- decision trees
- semi supervised learning
- pattern recognition
- decision boundary
- cross validation
- high dimensional
- hyperplane
- input space
- principal components