Unsupervised Dimension Reduction Using Supervised Orthogonal Discriminant Projection for Clustering.
Leilei YanLi ZhangPublished in: HPCC/SmartCity/DSS (2019)
Keyphrases
- discriminant projection
- dimension reduction
- manifold learning
- dimensionality reduction
- linear discriminant analysis
- high dimensional data
- high dimensional data analysis
- unsupervised learning
- high dimensionality
- cluster analysis
- dimensionality reduction methods
- discriminant analysis
- principal component analysis
- feature extraction
- high dimensional
- low dimensional
- data points
- random projections
- feature space
- partial least squares
- feature selection
- clustering algorithm
- singular value decomposition
- clustering method
- principal components analysis
- data clustering
- k means
- scatter matrices
- face recognition
- nearest neighbor
- knn
- feature subspace
- pattern recognition
- support vector
- supervised learning
- semi supervised
- self organizing maps
- preprocessing
- data sets
- machine learning
- preprocessing step
- principal components
- document clustering
- database