Improved Singular Value Decomposition for Supervised Learning in a High Dimensional Dataset.
Ricco RakotomalalaFaouzi MhamdiPublished in: PRIS (2006)
Keyphrases
- singular value decomposition
- high dimensional
- supervised learning
- dimensionality reduction
- dimension reduction
- singular values
- low rank
- least squares
- unsupervised learning
- latent semantic indexing
- low dimensional
- principal component analysis
- high dimensional data
- high dimensionality
- similarity search
- training set
- semi supervised
- data matrix
- manifold learning
- training data
- singular vectors
- null space
- low rank approximation
- training samples
- nearest neighbor
- data points
- active learning
- feature space
- pattern recognition