-hyperplane clustering problem.
Edoardo AmaldiKanika DhyaniLeo LibertiPublished in: Comput. Optim. Appl. (2013)
Keyphrases
- hyperplane
- data points
- high dimensional data sets
- training samples
- feature space
- support vector
- kernel function
- high dimensional data
- incremental learning algorithm
- kernel space
- linearly separable
- support vector machine
- decision boundary
- linear classifiers
- input space
- maximal margin
- convex hull
- principal components
- low dimensional
- support vectors
- locality sensitive
- classification procedure
- machine learning
- average distance
- high dimensional
- nearest neighbor
- feature extraction
- neural network
- linear separability