SS-SVM (3SVM): A New Classification Method for Hepatitis Disease Diagnosis | Faculty of Computers and Information

SS-SVM (3SVM): A New Classification Method for Hepatitis Disease Diagnosis

Faculty of Computers and Information

Assiut University

SS-SVM (3SVM): A New Classification Method for Hepatitis Disease Diagnosis

Research Authors
Mohammed H. Afif, Abdel-Rahman Hedar, Taysir H. Abdel Hamid, Yousef B. Mahdy
Research Department
Computer Science Department
Research Journal
International Journal of Advanced Computer Science and Applications
Research Member
Yousef Bassyouni Mahdy Ahmed
Research Rank
1
Research Vol
Vol. 4
Research Year
2013
Research_Pages
No. 2
Research Abstract

Abstract.In this paper, a new classification approach combining support vector machine with scatter
search approach for hepatitis disease diagnosis is presented, called 3SVM. The scatter search approach
is used to find near optimal values of SVM parameters and its kernel parameters. The hepatitis dataset
is obtained from UCI. Experimental results and comparisons prove that the 3SVM gives better
outcomes and has a competitive performance relative to other published methods found in literature,
where the average accuracy rate obtained is 98.75%.