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Generalized version of the support vector machine for binary classification problems: supporting hyperplane machine

2014-04-13 · E. G. Abramov, A. B. Komissarov, D. A. Kornyakov

In this paper there is proposed a generalized version of the SVM for binary classification problems in the case of using an arbitrary transformation x -> y. An approach similar to the classic SVM method is used. The problem is widely explained. Various formulations of primal and dual problems are proposed. For one of the most important cases the formulae are derived in detail. A simple computational example is demonstrated. The algorithm and its implementation is presented in Octave language.

📄 PDF Abstract BibTeX arXiv:1404.3415

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Binary ClassificationGeneral Classification

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SVM A Support Vector Machine, or SVM, is a non-parametric supervised learning model. For non-linear classification and regression, they utilise the kernel trick to map inputs…

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