Support Vector Regression
Darius M. Dziuda · Cambridge University Press eBooks · 2024
Chapter 9 presents support vector regression (SVR), a relatively newer supervised learning algorithm for predictive regression modeling, which – like random forests for regression – also may outperform the least-squares - based methods. Discussed is ε -insensitive loss used by SVR, the ε -tube concept, as well as algorithms for linear and nonlinear SVRs.