Abstract
People should be conscious on good health and hygiene. Diabetes is another epidemic that threatens not only elderly but even youngsters due to sedentary lifestyles. Managing blood sugar level is vital to avoid further health complications, particularly for Type 2 Diabetes. Early prediction will help people to change their eating habits. Dataset containing Age, Gender, Height, Weight, Insulin Level, Fat Level for various age groups were collected for prediction. The JRip technique was employed to generate rules for the above parameters and the data was tested using Multi-Layer Perceptron (MLP) for improved accuracy. MLP model with 10-fold Jrip cross validation predicted the class labels with 99.8% accuracy.
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Sreedevi, B., Karthik, D., Glory Thephoral, J., Jeya Pandian, M., Revathy, G. (2023). A Novel Neural Network Based Model for Diabetes Prediction Using Multilayer Perceptron and Jrip Classifier. In: Ranganathan, G., Bestak, R., Fernando, X. (eds) Pervasive Computing and Social Networking. Lecture Notes in Networks and Systems, vol 475. Springer, Singapore. https://doi.org/10.1007/978-981-19-2840-6_27
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DOI: https://doi.org/10.1007/978-981-19-2840-6_27
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