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

  • Nguyen Van Hau Hung Yen University of Technology and Education
  • Nguyen Thi Hai Nang Hung Yen University of Technology and Education
  • Nguyen Tien Tu Dien Bien General Hospital
  • Nguyen Ngoc Tien Dien Bien General Hospital
Keywords: Decision Trees, Random Forests, Gradient Boosted Trees, Ensemble methods, Machine learning

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.

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Published
2018-01-08
How to Cite
Nguyen Van Hau, Nguyen Thi Hai Nang, Nguyen Tien Tu, & Nguyen Ngoc Tien. (2018). STUDY ENSEMBLE METHODS AND PREDICT KIDNEY DISEASE FOR DIEN BIEN GENERAL HOSPITAL. UTEHY Journal of Science and Technology, 16, 64-70. Retrieved from http://tapchi.utehy.edu.vn/index.php/jst/article/view/146