Locally fitting hyperplanes to high-dimensional data.
M. HouC. KambhampatiPublished in: Neural Comput. Appl. (2022)
Keyphrases
- high dimensional data
- data points
- dimensionality reduction
- nearest neighbor
- hyperplane
- low dimensional
- high dimensional
- similarity search
- high dimensionality
- high dimensions
- data analysis
- subspace clustering
- input space
- original data
- data sets
- data distribution
- sparse representation
- high dimensional spaces
- manifold learning
- nonlinear dimensionality reduction
- lower dimensional
- linear discriminant analysis
- dimension reduction
- principal component analysis
- small sample size
- least squares
- high dimensional data sets
- clustering high dimensional data
- high dimensional feature space
- dimensional data
- variable selection
- neural network
- subspace learning
- text data
- real world