Unobserved classes and extra variables in high-dimensional discriminant analysis.
Michael FopPierre-Alexandre MatteiCharles BouveyronThomas Brendan MurphyPublished in: Adv. Data Anal. Classif. (2022)
Keyphrases
- discriminant analysis
- high dimensional
- variable selection
- dimensionality reduction methods
- linear discriminant analysis
- kernel principal component analysis
- dimensionality reduction
- face recognition
- discriminant functions
- principal component analysis
- feature extraction
- hidden variables
- factor analysis
- fisher criterion
- low dimensional
- small sample size
- fisher linear discriminant analysis
- generalized linear
- nearest neighbor
- kernel discriminant analysis
- high dimensionality
- class labels
- high dimensional data
- computer vision
- fisher discriminant analysis
- discriminant projection
- discriminant subspace
- manifold learning
- dimension reduction
- cross validation
- data points