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Diagnosis of Tuberculosis (TB) Diseases by Using Naïve Bayesian Classifier

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dc.contributor.author Chit, Nay Chi
dc.contributor.author Oo, May Khaing
dc.date.accessioned 2019-08-03T03:33:07Z
dc.date.available 2019-08-03T03:33:07Z
dc.date.issued 2009-12-30
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1687
dc.description.abstract Computers have become an indispensable tool in the Health Care Industry. As technology grows rapidly, many people take great interest in computer and then computer based methods are used to improve the quality of the medical services. In this paper, Naïve Bayesian classification method is used to classify the Tuberculosis (TB) diseases according to the symptoms. Naïve Bayesian classification has become a successful technique for medical systems. It assumes that attributes are independence of each other. And it is a simple probabilistic classifier based on applying Bayes theorem with strong (naive) independence assumptions. To known the system’s accuracy, holdout method is used and the experimental results shows that this system is reliable. en_US
dc.language.iso en en_US
dc.publisher Fourth Local Conference on Parallel and Soft Computing en_US
dc.title Diagnosis of Tuberculosis (TB) Diseases by Using Naïve Bayesian Classifier en_US
dc.type Article en_US


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