Statistical classification of diabetes using Bagging algorithm

Diabetes is a disease that is caused by high blood sugar levels. The various traditional methodsavailable for diagnosing diabetes are based on physical and chemical tests. These methods canhave errors due to various uncertainties. For statistical classification of diabetes, we used a dataset that includes ۷۶۸ samples (patients) and ۸ features were examined. And we used the baggingalgorithm to implement. The combining classification algorithm combines several classifications.In fact, these classifiers each build their own model on the data and store this model. Finally, forclassification, a vote is taken among these categories, and the class that gets the most votes is thefinal class. Using this algorithm, we were able to increase the accuracy of diabetes classificationby ۷۵.۳۹۰۶%.