Combining PCA and multiset CCA for dimension reduction when group ICA is applied to decompose naturalistic fMRI data.
Valeri TsatsishviliFengyu CongPetri ToiviainenTapani RistaniemiPublished in: IJCNN (2015)
Keyphrases
- dimension reduction
- principal component analysis
- independent component analysis
- principle component analysis
- feature extraction
- partial least squares
- dimensionality reduction
- high dimensional problems
- feature space
- face recognition
- high dimensional
- low dimensional
- linear discriminant analysis
- preprocessing
- dimension reduction methods
- random projections
- discriminant analysis
- singular value decomposition
- principal components
- manifold learning
- discriminative information
- canonical correlation analysis
- independent components
- feature selection
- high dimensional data analysis
- high dimensional data
- preprocessing step
- cluster analysis
- feature subspace
- unsupervised learning
- text mining
- image processing