This paper is published in Volume-3, Issue-3, 2017
Area
Machine Learning
Author
Sannia, Shehnaz, Abhishek Bhardwaj
Org/Univ
CT Group of Institute, Jalandar, Punjab, India
Keywords
Detection, Machine Learning, Hypoglycemia
Citations
IEEE
Sannia, Shehnaz, Abhishek Bhardwaj. Review on Detection of Hypoglycaemia by Machine Learning Approach, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Sannia, Shehnaz, Abhishek Bhardwaj (2017). Review on Detection of Hypoglycaemia by Machine Learning Approach. International Journal of Advance Research, Ideas and Innovations in Technology, 3(3) www.IJARIIT.com.
MLA
Sannia, Shehnaz, Abhishek Bhardwaj. "Review on Detection of Hypoglycaemia by Machine Learning Approach." International Journal of Advance Research, Ideas and Innovations in Technology 3.3 (2017). www.IJARIIT.com.
Sannia, Shehnaz, Abhishek Bhardwaj. Review on Detection of Hypoglycaemia by Machine Learning Approach, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Sannia, Shehnaz, Abhishek Bhardwaj (2017). Review on Detection of Hypoglycaemia by Machine Learning Approach. International Journal of Advance Research, Ideas and Innovations in Technology, 3(3) www.IJARIIT.com.
MLA
Sannia, Shehnaz, Abhishek Bhardwaj. "Review on Detection of Hypoglycaemia by Machine Learning Approach." International Journal of Advance Research, Ideas and Innovations in Technology 3.3 (2017). www.IJARIIT.com.
Abstract
The doctor concluded related to an indication that someone has the potential against diabetes mellitus (DM) the architecture of the proposed method is designed. With the data obtained from the authorities in the laboratory, the model has been adjusted. Split points and using the Gina index the best split points are identified in this paper. By identifying false split points to minimize the calculation of Gini indices a method is proposed and Gaussian fuzzy function is used because the clinical data sets are not crisp,In this paper review the different method of diabetes classification