Lecture

Support Vector Machines: Definition and Separation Hyperplane

In course

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Description

This lecture introduces support vector machines (SVM) as a method to find a hyperplane that separates two classes with maximum margin. It covers the history of SVM, linear separability, hyperplanes, and the concept of support vectors. The lecture explains the motivation behind SVM, the minimization of empirical risk, and the importance of maximizing the margin of the separating hyperplane. It also discusses the concept of support vectors and the zone of indecision in SVM.

Instructor

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Official source

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

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Ontological neighbourhood

Information engineering

Machine learning: Topics in machine learning

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