Gaussian bandwidth selection for manifold learning and classification.
Ofir LindenbaumMoshe SalhovArie YeredorAmir AverbuchPublished in: Data Min. Knowl. Discov. (2020)
Keyphrases
- manifold learning
- feature extraction
- dimension reduction
- low dimensional
- dimensionality reduction
- high dimensional
- feature space
- diffusion maps
- subspace learning
- locality preserving
- locality preserving projections
- pattern recognition
- semi supervised
- high dimensional data
- feature mapping
- nonlinear dimensionality reduction
- feature selection
- manifold embedding
- decision trees
- feature vectors
- support vector
- unsupervised learning
- face recognition
- sparse representation
- support vector machine
- text classification
- laplacian eigenmaps
- geodesic distance
- machine learning
- data analysis
- preprocessing
- training set
- pattern classification
- supervised learning
- support vector machine svm
- maximum likelihood