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

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.