Abstract: In accordance to the fast developing technology now a days, every field is gaining it’s benefit through machines other than human involvement. Many changes are being made much advancement is possible by this developing technology. Likewise this technology is too gaining its importance in bioinformatics especially to analyse data. As we all know that diabetes is one of the present day deadly diseases prevailing. So in this paper we introduce LS-SVM classification to understand which datasets of blood may have the chance to get diabetes. Further, considering the patient’s details we can predict where he has a chance to get diabetes, if so measures to cure or stop it. In this method, an optimal Tabu search model will be suggested to reduce the chances of getting it in the future.

Fawzi Elias Bekri and Dr. A. Govardhan, “ OFW-ITS-LSSVM: Weighted Classification by LS-SVM for Diabetes diagnosis” International Journal of Advanced Computer Science and Applications(IJACSA), 3(3), 2012. http://dx.doi.org/10.14569/IJACSA.2012.030315

@article{Bekri2012,
title = { OFW-ITS-LSSVM: Weighted Classification by LS-SVM for Diabetes diagnosis},
journal = {International Journal of Advanced Computer Science and Applications}
doi = {10.14569/IJACSA.2012.030315},
url = {http://dx.doi.org/10.14569/IJACSA.2012.030315},
year = {2012},
publisher = {The Science and Information Organization},
volume = {3},
number = {3},
author = {Fawzi Elias Bekri and Dr. A. Govardhan},
}