Applying inverse stereographic projection to manifold learning and clustering.
Kajal EybpooshMansoor RezghiAbbas HeydariPublished in: Appl. Intell. (2022)
Keyphrases
- manifold learning
- intrinsic manifold
- high dimensional data
- locality preserving
- discriminant projection
- dimensionality reduction
- nonlinear dimensionality reduction
- semi supervised
- low dimensional
- diffusion maps
- subspace learning
- feature extraction
- high dimensional
- dimension reduction
- clustering algorithm
- sparse representation
- manifold structure
- cluster analysis
- clustering method
- unsupervised learning
- feature space
- locally linear embedding
- high dimensionality
- linear discriminant analysis
- data points
- k means
- head pose estimation
- geodesic distance
- pattern recognition
- locality preserving projections
- machine learning
- discriminant embedding
- learning algorithm
- manifold embedding
- data analysis
- laplacian eigenmaps
- self organizing maps
- pairwise
- data sets
- low rank
- facial expressions
- data clustering