An Application to Predict the Risk Level of Chronic Kidney Disease

dc.contributor.author	Vajiramali, G.H.Pamoda
dc.contributor.author	Premachandra, Kaushalya
dc.date.accessioned	2020-01-16T10:23:15Z
dc.date.available	2020-01-16T10:23:15Z
dc.date.issued	2019
dc.identifier.citation	RIRC - 2019 , Rajarata International Research Conference, Faculty of Applied Sciences	en_US
dc.identifier.issn	2235-9710
dc.identifier.uri	http://repository.rjt.ac.lk/handle/123456789/2572
dc.language.iso	en	en_US
dc.publisher	Rajarata University of Sri Lanka, Faculty of Applied Sciences	en_US
dc.subject	Machine Learning	en_US
dc.subject	Chronic kidney disease	en_US
dc.subject	Disease Prediction	en_US
dc.subject	Support Vector machine	en_US
dc.subject	Two Class Logistic Regression	en_US
dc.title	An Application to Predict the Risk Level of Chronic Kidney Disease	en_US
dc.type	Article	en_US