Regularized Nonlinear Discriminant Analysis - An Approach to Robust Dimensionality Reduction for Data Visualization.
Martin BeckerJens LippelAndré StuhlsatzPublished in: VISIGRAPP (3: IVAPP) (2017)
Keyphrases
- discriminant analysis
- data visualization
- kernel discriminant analysis
- dimensionality reduction
- linear discriminant analysis
- discriminant subspace
- linear dimensionality reduction
- dimensionality reduction methods
- subspace learning
- feature extraction
- principal component analysis
- graph embedding
- generalized linear
- nonlinear dimensionality reduction
- face recognition
- data analysis
- kernel principal component analysis
- generalized discriminant analysis
- knowledge discovery
- discriminant projection
- high dimensional data
- visual data mining
- class separability
- dimension reduction
- fisher criterion
- kernel pca
- low dimensional
- principal components analysis
- big data
- pattern recognition
- fisher discriminant analysis
- high dimensional
- input space
- kernel trick
- data representation
- manifold learning
- least squares
- database
- original data
- data processing
- nearest neighbor
- computer vision
- nearest feature line
- real world