A manifold learning approach to dimensionality reduction for modeling data.
Claudio TurchettiLaura FalaschettiPublished in: Inf. Sci. (2019)
Keyphrases
- dimensionality reduction
- manifold learning
- high dimensional data
- low dimensional
- data points
- manifold structure
- high dimensional
- training data
- principal component analysis
- input space
- dimensionality reduction methods
- data representation
- nonlinear dimensionality reduction
- semi supervised
- diffusion maps
- support vector
- feature extraction
- data sets
- feature selection
- feature space
- subspace learning
- embedding space
- underlying manifold
- dimension reduction
- high dimensionality
- singular value decomposition
- labeled data
- data mining techniques
- data analysis
- decision trees