Lecture

Support Vector Regression: Principles and Optimization

In course

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Description

This lecture introduces Support Vector Regression (SVR) as an extension of the support vector machine framework for classification to estimate continuous functions. It covers the linear case, the E-tube concept, the ε-margin, optimization problems, and the solution for both linear and non-linear regression. The lecture also delves into the interpretation of SVR solutions, the role of hyperparameters in SVR optimization, and their influence on the fit.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_xrord198

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Ontological neighbourhood

Statistics

Data analysis: Regression analysis

Information engineering

Machine learning: Topics in machine learning

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