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Al-Dulaimi, Hiba
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Computer Science & IT Engineering

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A Review on Support Vector Machine Problems and Solutions Al-Dulaimi, Hiba; Ku-Mahamud, Ku Ruhana
Data Science Insights Vol. 4 No. 1 (2026): Journal of Data Science Insights
Publisher : Visi Media Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63017/jdsi.v4i1.217

Abstract

In this paper, a review is presented particularly on Support Vector Machine (SVM) problems, so as to understand these problems and to identify the approaches to solve them. The aim is to organize the main SVM problems in a manner that provides a clear view for the readers. The approaches for solving SVM problems were classified into non-simultaneous and simultaneous approaches based on constraints considered in solving the problems. Algorithms for model selection and feature subset selection are classified into heuristic and non-heuristic approaches. Very promising result can be obtained if the bio-inspired algorithms are simultaneously applied with SVM for classification problem.
Co-Authors Ku-Mahamud, Ku Ruhana