STUDY ENSEMBLE METHODS AND PREDICT KIDNEY DISEASE FOR DIEN BIEN GENERAL HOSPITAL

Abstract

Machine learning has now been widely applied in the modern life, ranging from medical diagnostics to counterfeit credit cards, stock market analysis, DNA sequencing, speech and writing recognition, auto translate, play games and robot locomotion. Every year, the research community and the industrial community have conducted health care seminars using the knowledge of Machine Learning, Artificial Intelligence [7]. Vic Gundotra, a former director at Google and Microsoft, said that within next five years, Machine Learning would be a powerful assistant to doctors. In this paper, we use Decision Trees model to predict kidney disease for the general hospital Dien Bien. In order to improve the accuracy, we study and install two models of ensembles which commonly used and are the most effective models in machine learning: Random Forests and Gradient Boosted Trees.