Lecture

Linear SVM derivation

In course

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Description

This lecture covers the derivation of Linear Support Vector Machine (SVM) starting from the classifier margin concept, computing the distance to the separating hyperplane, determining constraints, solving the constrained optimization problem, interpreting the solution, and discussing the dual optimization using the Karush-Kuhn-Tucker (KKT) conditions.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_dlvlmo09

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Ontological neighbourhood

Information engineering

Machine learning: Topics in machine learning

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