Related papers: An alternative to SVM Method for Data Classification

An alternative to SVM Method for Data Classification

URL: http://arxiv.org/abs/2308.11579v1
Date: Sun, 20 Aug 2023 14:09:01 GMT
Title: An alternative to SVM Method for Data Classification
Authors: Lakhdar Remaki
Abstract summary: Support vector machine (SVM) is a popular kernel method for data classification. The method suffers from some weaknesses including; time processing, risk of failure of the optimization process for high dimension cases. In this paper an alternative method is proposed having a similar performance, with a sensitive improvement of the aforementioned shortcomings.
Score: 0.0
License: http://creativecommons.org/licenses/by/4.0/
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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