Support Vector Regression

🤖 Plain-English Summary

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.

🔑 Key Findings

• Discussed is ε -insensitive loss used by SVR, the ε -tube concept, as well as algorithms for linear and nonlinear SVRs.

🔗 Related Resources