Semi-supervised rough fuzzy Laplacian Eigenmaps for dimensionality reduction.
Minghua MaTingquan DengNing WangYanmei ChenPublished in: Int. J. Mach. Learn. Cybern. (2019)
Keyphrases
- laplacian eigenmaps
- rough fuzzy
- dimensionality reduction
- semi supervised
- manifold learning
- nonlinear dimensionality reduction
- computational theory
- subspace learning
- independent component analysis
- neural network
- kernel pca
- rough set theory
- locally linear embedding
- rough sets
- principal component analysis
- fuzzy sets
- semi supervised learning
- low dimensional
- high dimensional data
- dimensionality reduction methods
- label information
- unlabeled data
- labeled data
- high dimensional
- feature space
- pattern recognition
- feature extraction
- active learning
- pairwise
- input space
- unsupervised learning
- supervised learning
- feature selection
- linear discriminant analysis
- metric learning
- euclidean distance
- data points
- data sets
- spectral clustering
- dimension reduction
- manifold structure
- data mining
- low rank
- object recognition
- labeled and unlabeled data
- signal processing
- support vector machine
- image segmentation