A U-classifier for high-dimensional data under non-normality.
M. Rauf AhmadTatjana PavlenkoPublished in: J. Multivar. Anal. (2018)
Keyphrases
- high dimensional data
- dimensionality reduction
- low dimensional
- high dimensionality
- nearest neighbor
- high dimensional
- input data
- data sets
- data analysis
- subspace clustering
- similarity search
- high dimensions
- data points
- manifold learning
- linear discriminant analysis
- feature space
- data distribution
- training data
- clustering high dimensional data
- high dimensional data sets
- high dimensional datasets
- original data
- missing values
- classification algorithm
- sparse representation
- decision trees
- dimension reduction
- input space
- support vector
- feature selection
- training set
- lower dimensional
- training samples
- support vector machine
- variable selection
- high dimensional spaces
- feature set
- nonlinear dimensionality reduction
- locally linear embedding
- database
- subspace learning
- neural network
- real world
- pattern recognition