Approximate fuzzy kernel clustering with random feature mapping and dimension reduction.
Lingning KongLong ChenPublished in: ICNC-FSKD (2016)
Keyphrases
- dimension reduction
- feature mapping
- manifold learning
- feature space
- high dimensional data
- cluster analysis
- high dimensionality
- laplacian eigenmaps
- unsupervised learning
- nonlinear dimensionality reduction
- high dimensional
- feature extraction
- low dimensional
- principal component analysis
- k means
- dimensionality reduction
- clustering algorithm
- linear discriminant analysis
- data points
- feature selection
- kernel function
- clustering method
- data clustering
- support vector
- random projections
- kernel matrix
- singular value decomposition
- data sets
- locally linear embedding
- feature vectors
- input space
- machine learning
- multiple instance learning
- document clustering
- similarity search
- latent space
- data mining
- data analysis
- neural network
- spectral clustering
- maximum likelihood
- supervised learning
- nearest neighbor
- semi supervised
- object recognition
- preprocessing