Support vector machines and linear regression coincide with very high-dimensional features.
Navid ArdeshirClayton SanfordDaniel J. HsuPublished in: NeurIPS (2021)
Keyphrases
- linear regression
- high dimensional
- support vector
- least squares
- regression problems
- feature space
- generalized linear models
- ridge regression
- high dimensionality
- learning machines
- classification accuracy
- training examples
- svm classifier
- regression trees
- feature extraction
- large margin classifiers
- hyperplane
- linear models
- radial basis function
- feature vectors
- cross validation
- high dimensional data
- locally weighted
- kernel function
- nearest neighbor