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The tutorial starts with an overview of the concepts of vc dimension and structural risk minimization.We then describe linear support vector machines svms for separable and non-separable data, working through a non-trivial example in detail.We describe a mechanical analogy, and discuss when svm solutions are unique and when they are global.
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