Date of Publication :9th August 2023

Abstract: One of the many chronic diseases that affect the elderly globally is diabetes. This condition develops when the blood sugar or glucose level is extremely high. Serious health issues can be avoided with early diabetes testing and treatment. The current methods for measuring blood glucose are intrusive, which makes patients uncomfortable. In this study, a dataset constructed from samples from the PIMA Indian Diabetes dataset is used to predict diabetes using a machine learning technique. Decision Tree utilising K Fold cross validation and Train Test split are the machine learning techniques utilised in this study. Using Decision Tree and Logistic Regression, comparative study of model accuracies and other performance parameters (Precision, Recall, F1 score) is also investigated.

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