Clustering, classification, discriminant analysis, and dimension reduction via generalized hyperbolic mixtures.
Katherine MorrisPaul D. McNicholasPublished in: Comput. Stat. Data Anal. (2016)
Keyphrases
- dimension reduction
- discriminant analysis
- linear discriminant analysis
- feature extraction
- cluster analysis
- principal component analysis
- high dimensional data
- partial least squares
- face recognition
- dimensionality reduction
- discriminative information
- high dimensionality
- principal components analysis
- small sample size
- feature space
- support vector machine svm
- dimension reduction methods
- support vector
- clustering method
- feature subspace
- random projections
- unsupervised learning
- scatter matrices
- feature selection
- clustering algorithm
- fisher discriminant analysis
- singular value decomposition
- pattern recognition
- dimensionality reduction methods
- null space
- preprocessing
- data points
- manifold learning
- feature vectors
- data mining
- k means
- nearest neighbor
- document clustering
- low dimensional
- high dimensional
- independent component analysis
- locality preserving projections
- reinforcement learning
- data mining techniques
- kernel function