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Research Article | Open Access |

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

Author 1: Mohammed H. Afif Author 2: Abdel-Rahman Hedar Author 3: Taysir H. Abdel Hamid Author 4: Yousef B. Mahdy
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 4, No. 2 · Published 2013 · Cited by 16

DOI: https://doi.org/10.14569/IJACSA.2013.040208

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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%.

Keywords

Support Vector Machine Scatter Search Classification Parameter tuning

How to Cite this Article

Afif, M. H., Hedar, A., Hamid, T. H. A., & Mahdy, Y. B. (2013). SS-SVM (3SVM): A New Classification Method for Hepatitis Disease Diagnosis. International Journal of Advanced Computer Science and Applications, 4(2). https://doi.org/10.14569/IJACSA.2013.040208

Afif, Mohammed H., et al.. "SS-SVM (3SVM): A New Classification Method for Hepatitis Disease Diagnosis." International Journal of Advanced Computer Science and Applications, vol. 4, no. 2, 2013, https://doi.org/10.14569/IJACSA.2013.040208.

@article{Afif2013,
  title     = {SS-SVM (3SVM): A New Classification Method for Hepatitis Disease Diagnosis},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {4},
  number    = {2},
  year      = {2013},
  publisher = {The Science and Information Organization},
  author    = {Mohammed H. Afif and Abdel-Rahman Hedar and Taysir H. Abdel Hamid and Yousef B. Mahdy},
  doi       = {10.14569/IJACSA.2013.040208},
  url       = {https://doi.org/10.14569/IJACSA.2013.040208}
}

Open Access — licensed under a Creative Commons Attribution 4.0 International License. Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.

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