A Nonlinear Dimensionality Reduction Using Combined Approach to Feature Space Decomposition.
Evgeny MyasnikovPublished in: AIST (Supplement) (2015)
Keyphrases
- nonlinear dimensionality reduction
- feature space
- dimensionality reduction
- low dimensional
- manifold learning
- riemannian manifolds
- high dimensional
- feature mapping
- high dimensional data
- locally linear embedding
- principal component analysis
- feature selection
- high dimensionality
- input space
- dimensionality reduction methods
- data points
- laplacian eigenmaps
- maximum variance unfolding
- dimension reduction
- mean shift
- subspace learning
- geodesic distance
- kernel function
- feature set
- nearest neighbor
- neural network
- linear discriminant analysis
- vector space
- data sets
- preprocessing step
- image representation
- training set
- machine learning