Dimension Reduction by Maximizing Pairwise Discriminations.
Yanshang GongShiji SongGao HuangPublished in: SMC (2015)
Keyphrases
- dimension reduction
- pairwise
- principal component analysis
- high dimensional
- feature extraction
- variable selection
- high dimensional problems
- high dimensional data
- linear discriminant analysis
- similarity measure
- random projections
- feature space
- high dimensionality
- singular value decomposition
- low dimensional
- dimensionality reduction
- feature selection
- semi supervised
- unsupervised learning
- dimension reduction methods
- manifold learning
- discriminative information
- cluster analysis
- partial least squares
- data mining and machine learning
- neural network
- high dimensional data analysis
- database
- loss function
- preprocessing
- manifold embedding
- data mining
- knn
- metric learning
- probabilistic model
- association rules
- support vector
- image processing
- data sets