On the effect of dimensionality reduction by Manifold Learning for Evolutionary Learning.
Hisashi HandaPublished in: Evol. Syst. (2011)
Keyphrases
- manifold learning
- dimensionality reduction
- evolutionary learning
- nonlinear dimensionality reduction
- low dimensional
- diffusion maps
- high dimensional data
- subspace learning
- high dimensional
- feature extraction
- principal component analysis
- evolutionary computation
- manifold learning algorithm
- high dimensionality
- feature space
- locally linear embedding
- dimension reduction
- data representation
- feature selection
- pattern recognition
- input space
- manifold structure
- locality preserving projections
- laplacian eigenmaps
- sparse representation
- data points
- discriminant projection
- principal components
- singular value decomposition
- unsupervised learning
- metric learning
- lower dimensional
- semi supervised
- principal components analysis
- dimensionality reduction methods
- data sets
- neighborhood preserving embedding
- embedding space
- linear discriminant analysis
- fitness function
- computational intelligence
- reinforcement learning
- image processing
- neural network