Assessing Machine Learning Methods for Predicting Diabetes among Pregnant Women

Machine Learning has a big impact on a lot of different scientific and technical disciplines, including medical research and Biophysics. Diabetes is a chronic condition marked by abnormally high glucose levels and the body's inefficient utilization of insulin. Diabetes is now becoming a leading cause of death all over the world. The objective of this article was to use multiple. Machine Learning methods are used to create a model with a limited number of dependencies, which could be used to study diabetic patients and diagnose diabetes using the PIMA dataset. Some of the most well-known prediction algorithms employed in this system are SVM (support vector machine), Multinomial Naive Bayes, Random forest, and Decision tree. Use these algorithms to construct a gathering of models by combining multiple combinations into one. This will enhance performance and accuracy.