Lecture

Support Vector Machines: Soft Margin SVM

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In course

EE-311: Fundamentals of machine learning

Ce cours présente une vue générale des techniques d'apprentissage automatique, passant en revue les algorithmes, le formalisme théorique et les protocoles expérimentaux. ...

Description

This lecture covers the concept of Soft Margin SVM, which aims to find a compromise between classification errors and the margin width in cases where data are not linearly separable. It introduces the idea of minimizing the inverse of the square of the margin to provide flexibility to the margin. The lecture also discusses the dual formulation of the Soft Margin SVM problem and the decision function derived from it.

Instructors (2)

Michael Stefan Daniel Liebling

Teaching & PhD Past EPFL PhD Students as codirector Christian Jaques, Olivia Mariani, Adrian Shajkofci, François Thierry M Marelli Courses Fundamentals of machine learning EE-311 This course provides a general overview of machine learning, covering the main algorithms, theoretical formalisms, and experimental protocols.

François Fleuret

Official source

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