Scaling cut criterion-based discriminant analysis for supervised dimension reduction.
Xiangrong ZhangYudi HeLicheng JiaoRuochen LiuJie FengSisi ZhouPublished in: Knowl. Inf. Syst. (2015)
Keyphrases
- dimension reduction
- discriminant analysis
- linear discriminant analysis
- principal component analysis
- feature extraction
- feature selection
- face recognition
- discriminant projection
- supervised dimensionality reduction
- cluster analysis
- dimensionality reduction
- unsupervised learning
- partial least squares
- random projections
- feature space
- fisher discriminant analysis
- principal components analysis
- discriminative information
- learning algorithm
- high dimensional data
- scatter matrices
- support vector
- manifold learning
- high dimensional
- semi supervised
- low dimensional
- independent component analysis
- null space
- graph embedding
- support vector machine svm
- supervised learning
- locality preserving projections
- dimension reduction methods
- machine learning
- high dimensionality
- pattern recognition
- dimensionality reduction methods
- singular value decomposition
- feature vectors
- preprocessing
- data sets