Classification of Diabetes using Random Forest with Feature Selection Algorithm | Zendy

K. Koteswara Chari | Zendy; M.Chinna Babu | Zendy; Sarangam Kodati | Zendy

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Classification of Diabetes using Random Forest with Feature Selection Algorithm

Author(s) -

K. Koteswara Chari,

M.Chinna Babu,

Sarangam Kodati

Publication year - 2019

Publication title -

international journal of innovative technology and exploring engineering

Language(s) - English

Resource type - Journals

ISSN - 2278-3075

DOI - 10.35940/ijitee.l3595.119119

Subject(s) - random forest , diabetes mellitus , computer science , feature selection , health records , machine learning , feature (linguistics) , artificial intelligence , data mining , medicine , algorithm , health care , political science , linguistics , philosophy , endocrinology , law

Diabetes has become a serious problem now a day. So there is a need to take serious precautions to eradicate this. To eradicate, we should know the level of occurrence. In this project we predict the level of occurrence of diabetes. We predict the level of occurrence of diabetes using Random Forest, a Machine Learning Algorithm. Using the patient’s Electronic Health Records (EHR) we can build accurate models that predict the presence of diabetes.

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