Support Vector Regression

M. Dziuda, Darius

doi:10.1017/9781009006767.012

Public

Support Vector Regression

Published in Cambridge University Press eBooks • May 30, 2024

Authors:

Darius M. Dziuda

Abstract

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, ...

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Subject

Support vector machine

Generalization

Quadratic programming

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