Open Access   Article

A Novel Approach for Heart Disease Classification using Feature Selection

R. UmaDevi1 , Raynuka Azhakarsamy2 , J.G.R. Sathiaseelan3

Section:Research Paper, Product Type: Journal Paper
Volume-06 , Issue-11 , Page no. 44-48, Dec-2018

Online published on Dec 31, 2018

Copyright © R. UmaDevi, Raynuka Azhakarsamy , J.G.R. Sathiaseelan . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Citation

IEEE Style Citation: R. UmaDevi, Raynuka Azhakarsamy , J.G.R. Sathiaseelan, “A Novel Approach for Heart Disease Classification using Feature Selection”, International Journal of Computer Sciences and Engineering, Vol.06, Issue.11, pp.44-48, 2018.

MLA Style Citation: R. UmaDevi, Raynuka Azhakarsamy , J.G.R. Sathiaseelan "A Novel Approach for Heart Disease Classification using Feature Selection." International Journal of Computer Sciences and Engineering 06.11 (2018): 44-48.

APA Style Citation: R. UmaDevi, Raynuka Azhakarsamy , J.G.R. Sathiaseelan, (2018). A Novel Approach for Heart Disease Classification using Feature Selection. International Journal of Computer Sciences and Engineering, 06(11), 44-48.

           

Abstract

Heart disease is predicted by classification technique. The data mining tool WEKA has been utilized for implementing J48 classifier. Proposed work is framed with a specific end goal to enhance the execution of models. For improving the classification accuracy J48 is combined with Bagging and Feature Selection. Trial results demonstrated a critical change over in the current J48 classifier. This approach enhances the classification accuracy and reduces computational time.

Key-Words / Index Term

Data mining, Heart diseases, WEKA, classification, J48, Bagging

References

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