Machine Learning Application for Diabetes Prediction Using Ensemble Classification

Data mining is a useful method for extracting meaningful information from massive volumes of records. Statistics and machine learning may be utilised to evaluate large-scale patterns in massive databases. Numerous researchers use image processing methods to predict disease, utilising data mining and machine learning approaches. Disease data can be collected from various sources. A bioinformatics technology will be used for keeping, retrieving, and interpreting information with biological molecules. A forecast can be explained as a description of upcoming events based on current conditions. The aim of this study is to create machine learning and data mining algorithms for diabetes prediction. There are various steps in predicting diabetes. In this study, a vote-based classifier is developed to predict diabetes. The proposed algorithm, is used to optimize the diabetes prediction performance up to 2%.