International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 128

Research Paper | Computer Science & Engineering | Sudan | Volume 6 Issue 10, October 2017


Comparative Study of Diabetic Patient Data Using Classi?cation Algorithm in Weaka

Ahlam A. Sharief | Alaa F. Sheta [3] | Talaat M. Wahbi [4]


Abstract: Diabetes mellitus is now a big growing health problem as it is fourth biggest cause of death world wide particularly in the industrial and developing countries. Early detection of diabetes is of vital importance nowadays. There have been many techniques used in Machine learning that were applied over diabetes diagnosis to help physicians. Diabetes mellitus or simply diabetes is a disease caused due to the increase level of blood glucose. Various available traditional methods for diagnosing diabetes are based on physical and chemical tests. These methods can have errors due to different uncertainties. A number of Data mining algorithms were designed to overcome these uncertainties.


Keywords: diabetes, Classication, Feature Selection, Pima Indians Diabetes Dataset PIDD, Weaka


Edition: Volume 6 Issue 10, October 2017,


Pages: 141 - 146


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How to Cite this Article?

Ahlam A. Sharief, Alaa F. Sheta, Talaat M. Wahbi, "Comparative Study of Diabetic Patient Data Using Classi?cation Algorithm in Weaka", International Journal of Science and Research (IJSR), Volume 6 Issue 10, October 2017, pp. 141-146, https://www.ijsr.net/get_abstract.php?paper_id=25091702

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