A Survey on Machine Learning Methodologies for Predicting The Diabetes Mellitus
Keywords:
Keywords: Classification, Naïve Bayes, K-NN, SVM, Association Rule Mining, Diabetes MellitusAbstract
Machine learning and Data mining play very major role in clinical
sector; in particular, for the design and develop diagnostic model as
an intelligent and expert system. The task of disease prediction and
diagnosis is a part of classification and prediction. The health datasets
Corresponding Author:
RM Gawande, Department of Computer
Engineering, Matoshri College of Engineering
Nashik, Maharashtra, India.
are dynamic and not definite in nature and it is tedious to manipulate
E-mail Id:
and to maintain. Diabetes is very chronic disease Diabetic patients
are normally not identified till a later stage of the disease or the
development of complications. The aim of paper is carry out in details
survey on the algorithmic approaches used in machine learning and
data mining techniques. Once the model build then it is necessary to
carry out validation and testing of the model. So in this paper various
validation techniques were discussed. One of the major objective of
this paper is summarization of various parameters and constraint that
the researchers used in their research work. We need a new expertaware
of daily helpful diagnosis and recommendation systems to avoid the
diabetes.
How to cite this article:
Gawande RM, Patil VH. A Survey on Machine
Learning Methodologies for Predicting The
Diabetes Mellitus. Int J Hum Comp Inter Data
Min 2019; 2(2): 18-24.
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