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Bimonthly Since 1986 |
ISSN 1004-9037
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Publication Details |
Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
Distributed by:
China: All Local Post Offices
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Abstract
Diabetes is an ineradicable disease that can be found in most of the people nowadays. Due to hectic schedulespeople are unable to focus on their health. The food we are consuming is fragmented into glucose; thesefragments will be delivered into blood. The pancreas releases a hormone named as insulin when the glucoselevels are high. This insulin plays a vital role in transporting the glucose to cells that can be used as energy. Tomaintain a sustainable life detection of diabetes in early stage will be beneficial. Machine learning algorithmswill be a productive approach as it will be trained & test with vast data and it enhances itself with upcomingfuture predictions. In this article, various algorithms like KNN , Naive Bayes are used, Decision Treeand trained with our collected dataset. Among these three algorithms it was observed that Decision Tree producedaccurateresults.
Keyword
Machine Learning, K-NN, Naïve Bayes, Decision Tree.
PDF Download (click here)
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