Lattice Linear Discriminant Analysis for Shape Constrained Classification.
Geng DengYaoguo XieXindong WangQiang FuPublished in: FSDM (2022)
Keyphrases
- linear discriminant analysis
- small sample size
- discriminant analysis
- support vector machine svm
- discriminant features
- dimension reduction
- feature extraction
- support vector
- feature space
- class separability
- class discrimination
- face recognition
- discriminative information
- fisher criterion
- principal component analysis
- principal components analysis
- dimensionality reduction
- linear discriminant
- subspace analysis
- classification accuracy
- image classification
- sample size
- feature selection
- kernel discriminant analysis
- subspace methods
- null space
- machine learning
- high dimensionality
- training samples
- pattern recognition
- high dimensional data
- similarity measure
- locality preserving projections
- supervised dimensionality reduction
- kernel function
- feature vectors
- linear transformation
- feature set
- multi class
- support vector machine
- decision trees
- computer vision