A Novel Prediction Model for Diabetes Detection Using Gridsearch and A Voting Classifier between Lightgbm and KNN

Diabetes is also known as diabetes mellitus is one of the world’s most prominent health hazards of the current times. It is a chronic disease in which the pancreas isn’t able to produce the right amounts of insulin for the body to absorb glucose into the body cells for energy and stays in the bloodstream in turn raising the blood glucose levels. If this is not detected and treated on time, it can affect other body organs as well and leads to organ failure thus becoming fatal.Machine learning and data mining are two emerging fields in today’s tech world. With the help of these methods, we can observe the past data behaviors and can then predict the future outcomes to a certain extent. This brings rise to the term ‘prediction models’ that we all know in today’s tech world. Keeping this in mind, we can create predictive models for diabetes prediction. This helps in the early detection of diabetes so that it can be treated at the earliest to avoid complications. By finding out the highest accuracy model, we can accurately predict whether the patient is diabetic beforehand and prevent further health issues. This research paper discusses the techniques that have been used to create a unique predictive model for the prediction of diabetes.