High-dimensional data clustering by using local affine/convex hulls.
Hakan CevikalpPublished in: Pattern Recognit. Lett. (2019)
Keyphrases
- high dimensional data
- convex hull
- data points
- high dimensional
- high dimensionality
- dimensionality reduction
- nearest neighbor
- subspace clustering
- low dimensional
- data sets
- clustering high dimensional data
- high dimensions
- similarity search
- high dimensional datasets
- data analysis
- high dimensional data sets
- manifold learning
- linear discriminant analysis
- hyperplane
- extreme points
- training samples
- dimension reduction
- high dimensional spaces
- dimensional data
- nonlinear dimensionality reduction
- input space
- neural network
- closest points
- principal component analysis
- pattern recognition
- feature extraction
- euclidean space
- document clustering
- point sets
- pairwise
- image processing