oa A Comparative Study on Various Data Mining Techniques for Early Prediction of Diabetes Mellitus
- Authors: Ovass Shafi1, S. Jahangeer Sidiq2, Tawseef Ahmed Teli3, Majid Zaman4
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View Affiliations Hide AffiliationsAffiliations: 1 School of Computer Applications, Lovely Professional University, Punjab, India 2 School of Computer Applications, Lovely Professional University, Punjab, India 3 Department of Computer Applications, Amar Singh College, J and K, India 4 Directorate of IT and SS, University of Kashmir, Srinagar, India
- Source: Global Emerging Innovation Summit (GEIS-2021) , pp 51-61
- Publication Date: November 2021
- Language: English
A Comparative Study on Various Data Mining Techniques for Early Prediction of Diabetes Mellitus, Page 1 of 1
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Diabetes mellitus is a deadly disease that affects people all over the globe. An early prediction of diabetes is very beneficial as it can be controlled before the onset of the disease. Various data mining classification techniques have proven fruitful in the early detection and prediction of multiple diseases like heart attack, depression, kidney-related diseases, and many more. This paper discusses and compares various data mining techniques for the prediction of Diabetes Mellitus. Also, three widely used data mining techniques via Artificial Neural Networks (ANN), K-nearest neighbor (KNN), and Support Vector Machine (SVM) have been implemented in Matlab and the results are compared based on accuracy, recall, true negative rate, and precision.
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