ANALYSIS OF VARIOUS DATA MINING TECHNIQUES TO PREDICT DIABETES MELLITUS

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DC Field	Value	Language
dc.contributor.author	J, Maria Shyla	-
dc.contributor.author	M, Renuka Devi	-
dc.date.accessioned	2020-12-24T09:19:59Z	-
dc.date.available	2020-12-24T09:19:59Z	-
dc.date.issued	2016-01	-
dc.identifier.issn	0973-4562	-
dc.identifier.uri	https://www.ripublication.com/Volume/ijaerv11n1.htm	-
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/2395	-
dc.description.abstract	Data mining approach helps to diagnose patient’s diseases. Diabetes Mellitus is a chronic disease to affect various organs of the human body. Early prediction can save human life and can take control over the diseases. This paper explores the early prediction of diabetes using various data mining techniques. The dataset has taken 768 instances from PIMA Indian Dataset to determine the accuracy of the data mining techniques in prediction. The analysis proves that Modified J48 Classifier provide the highest accuracy than other techniques.	en_US
dc.language.iso	en	en_US
dc.publisher	Research India Publications	en_US
dc.subject	Data mining	en_US
dc.subject	Diabetes	en_US
dc.subject	Prediction	en_US
dc.subject	accuracy	en_US
dc.subject	classification	en_US
dc.title	ANALYSIS OF VARIOUS DATA MINING TECHNIQUES TO PREDICT DIABETES MELLITUS	en_US
dc.type	Article	en_US
Appears in Collections:	International Journals

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