Abstract
Abstract: Diabetes mellitus is a chronic condition that influences everyday life of the individual having this disease. Diabetes can only be treated to maintain controlled blood glucose levels than to achieve a permanent cure to lead a normal life. As the proverb goes, “prevention is better than cure”, this model aims at “predicting the probability”, of getting this condition, which help early prognosis enough to either avoid it or delay it. Ensemble method is used for prediction of probability of getting diabetes. Classification models in machine learning are used for decision making and enlisted in sequence of accuracy. Hyperparameters are tuned for top five accurate models. Comparison of different classifiers are carried out and then subjected to voting to choose the best possible method of prediction. Voting is carried out in hard voting and soft voting procedures. The results obtained are better compared to general classifiers individually
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal for Research in Applied Science and Engineering Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
