A novel robust kernel for classifying high-dimensional data using Support Vector Machines.
Syed Fawad HussainPublished in: Expert Syst. Appl. (2019)
Keyphrases
- high dimensional data
- dimensionality reduction
- low dimensional
- high dimensional
- nearest neighbor
- data sets
- input space
- subspace clustering
- high dimensions
- high dimensionality
- data analysis
- data points
- data distribution
- dimension reduction
- high dimensional spaces
- low rank
- manifold learning
- clustering high dimensional data
- original data
- similarity search
- linear discriminant analysis
- kernel function
- sparse representation
- dimensional data
- input data
- multi dimensional
- feature space
- text data
- support vector
- underlying manifold
- small sample size
- variable selection
- nonlinear dimensionality reduction
- feature selection
- high dimensional data sets
- clustering algorithm
- similarity measure
- subspace learning