Representative null space LDA for discriminative dimensionality reduction.
Zaixing HeMengtian WuXinyue ZhaoShuyou ZhangJianrong TanPublished in: Pattern Recognit. (2021)
Keyphrases
- null space
- linear discriminant analysis
- dimensionality reduction
- discriminative information
- discriminant analysis
- feature extraction
- dimension reduction
- data representation
- high dimensional data
- principal component analysis
- unsupervised learning
- discriminant information
- singular value decomposition
- pattern recognition
- high dimensional
- feature selection
- small sample size
- low dimensional
- high dimensionality
- scatter matrices
- data points
- principal components
- random projections
- feature space
- manifold learning
- metric learning
- lower dimensional
- scatter matrix
- discriminative features
- subspace learning
- intrinsic dimensionality
- support vector machine
- machine learning
- data sets