Call For Paper Volume:4 Issue:8 Aug'2017 |

Design and Development of Hybrid Genetic Classifier Model for Prediction of Diabetes

Publication Date : 26/04/2016



Author(s) :

E.Sreedevi , Prof.M.Padmavathamma.


Volume/Issue :
Volume 3
,
Issue 4
(04 - 2016)



Abstract :

Diabetes is generally a high sugar problem that doesn’t make enough insulin to our body and leads to polygenic disease characterized by abnormal high glucose in the blood. By the statistical survey 95% of the diabetic cases in the world suffering with type 2 diabetes. Genetic algorithm (GA) is considered to be an optimal search algorithm to find the optimal solution by cleaning out the worse gene strings based on a fitness function. GA had established efficiency in solving the problems of unsupervised data classification. This paper proposes a new Hybrid Genetic Classifier Model (HGCM) for the prediction of type 2 diabetes by integrating different distance methods as fitness function in GA Classifier & feature Selection method for getting classification accuracy. By HGCM two rules are generated for the prediction of type 2 diabetes.


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Design and Development of Hybrid Genetic Classifier Model for Prediction of Diabetes

April 8, 2016