Fast Approximation of Support Vector Kernel Expansions, and an Interpretation of Clustering as Approximation in Feature Spaces.
Bernhard SchölkopfAlexander J. SmolaPhil KnirschChris BurgesPublished in: DAGM-Symposium (1998)
Keyphrases
- support vector
- polynomial kernels
- feature space
- kernel function
- kernel methods
- approximation algorithms
- data points
- error bounds
- clustering algorithm
- hyperplane
- linear discriminant analysis
- cluster analysis
- high dimensional data
- feature selection
- closed form
- unsupervised learning
- document clustering
- image classification
- similarity function
- semi supervised
- classification accuracy
- nearest neighbor search