Principal subbundles for dimension reduction.
Morten AkhøjJames BennErlend GrongStefan SommerXavier PennecPublished in: CoRR (2023)
Keyphrases
- dimension reduction
- principal component analysis
- feature extraction
- high dimensional
- partial least squares
- singular value decomposition
- low dimensional
- linear discriminant analysis
- feature selection
- manifold learning
- unsupervised learning
- high dimensional data
- random projections
- high dimensional problems
- high dimensionality
- variable selection
- data mining and machine learning
- cluster analysis
- preprocessing
- dimensionality reduction
- feature space
- discriminative information
- dimension reduction methods
- data sets
- discriminant analysis
- semi supervised
- feature subspace
- object recognition
- high dimensional data analysis