A Review on Support Vector Machine Problems and Solutions

Hiba Al-Dulaimi; Ku Ruhana Ku-Mahamud

doi:10.63017/jdsi.v4i1.217

Authors

Hiba Al-Dulaimi University of Technology - Iraq, College of Computer Science, Department of Artificial Intelligence
Ku Ruhana Ku-Mahamud Universiti Utara Malaysia

DOI:

https://doi.org/10.63017/jdsi.v4i1.217

Keywords:

Support Vector Machine, Model Selection, Feature Subset Selection, Non-Simultaneous Approach, Simultaneous Approach

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.

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