Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval.
Mohammed Tahar Habib KaibAbdelmalek KouadriMohamed Faouzi HarkatAbderazak BensmailMajdi MansouriPublished in: IEEE Access (2024)
Keyphrases
- kernel principal component analysis
- data sets
- small number of training samples
- kernel pca
- principal components
- feature extraction
- principal component analysis
- discriminant analysis
- kernel function
- preprocessing
- feature space
- kernel methods
- high dimensional feature space
- classification method
- linear discriminant analysis
- kernel matrix
- high dimensional
- kernel fisher discriminant analysis
- face recognition
- training set
- high dimensional data
- k nearest neighbor
- spectral clustering
- dimensionality reduction
- input space
- feature vectors
- subspace methods