Support vector machines and linear regression coincide with very high-dimensional features.
Navid ArdeshirClayton SanfordDaniel HsuPublished in: CoRR (2021)
Keyphrases
- linear regression
- high dimensional
- support vector
- least squares
- regression problems
- feature space
- classification accuracy
- learning machines
- generalized linear models
- svm classifier
- linear models
- nonlinear regression
- feature vectors
- feature extraction
- linear predictors
- linear regression model
- locally weighted
- kernel function
- high dimensionality
- low dimensional
- input space
- binary classification
- regression trees
- ridge regression
- machine learning