Dimension reduction and spatiotemporal regression: applications to neuroimaging.
Kerby SheddenKer-Chau LiPublished in: Comput. Sci. Eng. (2003)
Keyphrases
- dimension reduction
- partial least squares
- principal component analysis
- feature extraction
- high dimensional
- high dimensional data
- data mining and machine learning
- manifold learning
- variable selection
- low dimensional
- dimensionality reduction
- regression model
- high dimensional problems
- random projections
- feature selection
- feature space
- linear discriminant analysis
- unsupervised learning
- discriminative information
- model selection
- singular value decomposition
- high dimensionality
- moving objects
- regression algorithm
- high dimensional data analysis
- nearest neighbor
- pattern recognition
- face recognition
- cluster analysis
- preprocessing
- bayesian networks
- machine learning
- manifold embedding
- dimension reduction methods
- data sets