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Application of A Radial Basis Function Neural Network for Diagnosis of Diabetes Mellitus

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dc.contributor.author Win, Kay Thi
dc.contributor.author Aye, Zin May
dc.date.accessioned 2019-08-06T10:44:12Z
dc.date.available 2019-08-06T10:44:12Z
dc.date.issued 2009-12-30
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1883
dc.description.abstract In this paper, an attempt is made to study the applicability of a general purpose, supervised feed forward neural network with one hidden layer, namely; Radial Basic Function (RBF) neural network. It uses relatively smaller number of locally tuned units and its adaptive in nature. RBFs are suitable for pattern recognition and classification. An artificial neural network with radial basic function is applied for the diagnosis of diabetes mellitus system This system consists of three phases: preprocessing, training and testing. en_US
dc.language.iso en en_US
dc.publisher Fourth Local Conference on Parallel and Soft Computing en_US
dc.title Application of A Radial Basis Function Neural Network for Diagnosis of Diabetes Mellitus en_US
dc.type Article en_US


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