A non-linear dimension reduction methodology for generating data-driven stochastic input models.
Baskar GanapathysubramanianNicholas ZabarasPublished in: J. Comput. Phys. (2008)
Keyphrases
- dimension reduction
- data driven
- feature extraction
- manifold learning
- principal component analysis
- linear discriminant analysis
- feature selection
- high dimensional
- high dimensional data
- high dimensional problems
- feature space
- probabilistic model
- partial least squares
- dimensionality reduction
- variable selection
- low dimensional
- manifold embedding
- finite state transducers
- intrinsic dimension
- database
- cluster analysis
- singular value decomposition
- model selection
- input data
- reinforcement learning
- data mining
- data sets