An alternative to SVM Method for Data Classification

Lakhdar Remaki

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arXiv · 2308.11579

An alternative to SVM Method for Data Classification

Lakhdar Remaki

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Abstract

Support vector machine (SVM), is a popular kernel method for data classification that demonstrated its efficiency for a large range of practical applications. The method suffers, however, from some weaknesses including; time processing, risk of failure of the optimization process for high dimension cases, generalization to multi-classes, unbalanced classes, and dynamic classification. In this paper an alternative method is proposed having a similar performance, with a sensitive improvement of the aforementioned shortcomings. The new method is based on a minimum distance to optimal subspaces containing the mapped original classes.

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Lakhdar Remaki. 2023-08-20. An alternative to SVM Method for Data Classification. https://arxiv.org/abs/2308.11579

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