CBMAP: Clustering-based manifold approximation and projection for dimensionality reduction.
Berat DoganPublished in: CoRR (2024)
Keyphrases
- dimensionality reduction
- low dimensional
- manifold learning
- high dimensional
- lower dimensional
- nonlinear dimensionality reduction
- linear projection
- diffusion maps
- discriminant projection
- locally linear embedding
- intrinsic manifold
- high dimensional data
- high dimensionality
- feature space
- graph embedding
- dimensionality reduction methods
- principal component analysis
- laplacian eigenmaps
- pattern recognition
- manifold structure
- feature extraction
- underlying manifold
- euclidean distance
- structure preserving
- dimension reduction
- projection operator
- embedding space
- random projections
- data sets
- input space
- singular value decomposition
- closed form
- pattern recognition and machine learning
- nonlinear manifold
- data representation
- null space
- convex sets
- euclidean space
- locality preserving projections
- subspace learning
- principal components
- parameter space
- error bounds
- machine learning
- neural network