SVM for Non-separable Datasets

In course

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Description

This lecture covers the application of Support Vector Machine (SVM) for non-separable datasets, introducing slack variables to relax constraints and optimize the margin. It explains the optimization problem, tradeoff between margin and slack, and the three cases for classification. The dual form of SVM is also presented.

Instructor

ex sit

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Official source

https://mediaspace.epfl.ch/media/0_bdn6wlwp

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Ontological neighbourhood

Theoretical computer science

Algorithms and data structures: Combinatorial optimization

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