Supervised discriminant Isomap with maximum margin graph regularization for dimensionality reduction.
Hongchun QuLin LiZhaoni LiJian ZhengPublished in: Expert Syst. Appl. (2021)
Keyphrases
- maximum margin
- dimensionality reduction
- linear dimensionality reduction
- pattern classification
- principal component analysis
- low dimensional
- kernel trick
- maximum entropy discrimination
- unsupervised learning
- learning algorithm
- graph construction
- feature extraction
- supervised dimensionality reduction
- label information
- hyperplane
- manifold learning
- nonlinear dimensionality reduction
- locality preserving projections
- feature selection
- graph embedding
- high dimensional
- support vector
- input space
- data points
- markov networks
- high dimensional data
- high dimensionality
- support vector machine
- pattern recognition
- feature space
- locally linear embedding
- principal components
- discriminant analysis
- dimensionality reduction methods
- multidimensional scaling
- semi supervised
- multiple kernel learning
- maximum likelihood
- face recognition
- multi task
- kernel pca
- linear discriminant analysis
- generalization error
- active learning
- supervised learning
- input data
- image processing