A Data Mining Approach for the Diagnosis of Diabetes Mellitus using Random Forest Classifier

Diabetes mellitus is an interminable disease that forces excessively high human, social and financial expenses for a nation. Additionally, minimizing its commonness rate and in addition its excessive and risky confusions requires viable administration. Diabetes administration depends on close partic...

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Bibliographic Details
Published in:International journal of computer applications 2015-01, Vol.120 (8), p.36-39
Main Authors: Butwall, Mani, Kumar, Shraddha
Format: Article
Language:English
Subjects:
Classifiers
Confusion
Data mining
Diabetes
Diabetes mellitus
Forests
Human
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Summary:Diabetes mellitus is an interminable disease that forces excessively high human, social and financial expenses for a nation. Additionally, minimizing its commonness rate and in addition its excessive and risky confusions requires viable administration. Diabetes administration depends on close participation between the patient and health awareness experts. Data mining gives a diversity of methods to investigate large data keeping in mind the end goal to find hidden knowledge. This study is an effort to plan and execute a descriptive data mining approach and to devise association standards to envisage diabetes behaviour in arrangement with particular life style parameters, including physical activity and emotional states, especially in elderly diabetics. Proposed methodology is based on Random Forest Classifier.
ISSN:0975-8887
0975-8887
DOI:10.5120/21249-4065