PCA and PLS with very large data sets.
Nouna KettanehAnders BerglundSvante WoldPublished in: Comput. Stat. Data Anal. (2005)
Keyphrases
- principal component analysis
- partial least squares
- principal components analysis
- dimension reduction
- principal components
- dimensionality reduction
- discriminant analysis
- covariance matrix
- feature extraction
- principle component analysis
- feature space
- appearance based object recognition
- linear discriminant analysis
- canonical correlation analysis
- latent variables
- high dimensional
- face images
- face recognition
- dimension reduction methods
- random projections
- genetic algorithm
- independent component analysis
- computer vision
- singular value decomposition
- kernel pca
- kernel principal component analysis
- lower dimensional
- database
- low dimensional
- least squares
- k means
- feature selection
- real time