Diffusion Maps for dimensionality reduction and visualization of meteorological data.
Ángela FernándezAna M. GonzálezJulia Díaz GarcíaJosé R. DorronsoroPublished in: Neurocomputing (2015)
Keyphrases
- diffusion maps
- dimensionality reduction
- meteorological data
- manifold learning
- nonlinear dimensionality reduction
- wind speed
- high dimensional
- high dimensional data
- low dimensional
- subspace learning
- semi supervised
- feature selection
- pattern recognition
- dimensionality reduction methods
- high dimensionality
- data analysis
- preprocessing step
- euclidean distance
- lower dimensional
- principal component analysis
- data points
- feature extraction
- linear discriminant analysis
- action classification
- weather data
- data visualization
- input space
- data sets
- statistical learning
- principal components
- random projections
- dimension reduction
- singular value decomposition
- feature space
- image processing
- locally linear embedding
- high dimension
- image classification
- supervised learning
- active learning
- computer vision