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Enhancing the prediction of type 2 diabetes mellitus using sparse balanced SVM |
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| Authors: | Shrestha Bibek Alsadoon Abeer Prasad P. W. C. Al-Naymat Ghazi Al-Dala’in Thair Rashid Tarik A. Alsadoon Omar Hisham |
| Affiliation: | 1.School of Computing Mathematics and Engineering, Charles Sturt University (CSU), Sydney, Australia ;2.School of Computer Data and Mathematical Sciences, Western Sydney University (WSU), Sydney, Australia ;3.Kent Institute Australia, Sydney, Australia ;4.Asia Pacific International College (APIC), Sydney, Australia ;5.College of Engineering and IT, Department of Information Technology, Ajman University, Ajman, UAE ;6.Computer Science and Engineering, University of Kurdistan Hewler, Erbil, KRG, Iraq ;7.Department of Islamic Sciences, Al Iraqia University, Baghdad, Iraq ; |
| Abstract: | Multimedia Tools and Applications - The natural population-based prediction of type 2 diabetes is costly since it needs a high number of resources. Even though much research has used machine... |
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