Canonical kernel dimension reduction.
Chenyang TaoJianfeng FengPublished in: Comput. Stat. Data Anal. (2017)
Keyphrases
- dimension reduction
- feature space
- principle component analysis
- principal component analysis
- feature extraction
- high dimensional
- low dimensional
- data mining and machine learning
- kernel function
- high dimensional problems
- kernel methods
- variable selection
- high dimensionality
- random projections
- linear discriminant analysis
- feature selection
- manifold learning
- partial least squares
- dimensionality reduction
- discriminative information
- singular value decomposition
- unsupervised learning
- high dimensional data
- preprocessing
- kernel pca
- high dimensional data analysis
- cluster analysis
- support vector
- multiple kernel learning
- neural network
- image data
- training data
- dimension reduction methods
- decision trees
- sparse metric learning