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Diabetes Prediction Using Ensemble Classifier

Category: ORIGINAL_ARTICLE
Authors: Shawni Dutta and Bandyopadhyay Kumar Samir
Abstract:Diabetes is one of the impactful diseases that affect humans’ health rigorously. Early diagnosis of diabetes will assist health care systems to decide and act according to counter measures. This paper focuses on obtaining an automated tool that will predict diabetic tendency of a patient. The system proposed by this paper contains two ensemble classifiers- Voting ensemble classifier and Stacking Ensemble classifier. Both of these methods exhibits better results while compared to other classifiers. Stacking ensemble classifier even performs better than voting ensemble classifier with an accuracy of 79.87%.
Year: 2020
Month: April
Volume: 9
Issue: 2
Published on: 30-05-2020