Dimension reduction in functional regression with applications.
Umberto AmatoAnestis AntoniadisItalia De FeisPublished in: Comput. Stat. Data Anal. (2006)
Keyphrases
- dimension reduction
- partial least squares
- feature extraction
- principal component analysis
- high dimensional
- singular value decomposition
- regression model
- high dimensional problems
- high dimensional data
- data mining and machine learning
- low dimensional
- linear discriminant analysis
- feature selection
- high dimensional data analysis
- cluster analysis
- high dimensionality
- random projections
- feature space
- variable selection
- dimensionality reduction
- discriminative information
- unsupervised learning
- dimension reduction methods
- regression algorithm
- manifold learning
- preprocessing
- pairwise
- sparse metric learning
- discriminant analysis
- face recognition
- optical flow
- learning algorithm
- least squares
- maximum likelihood