Diabetes diagnosis system using modified Naive Bayes classifier
نویسندگان
چکیده
<span>In today’s world, Diabetes is one of these diseases and now a big growing health problem. The techniques data mining have been widely applied to extract knowledge from medical databases. In this work, Medical Diagnosis system proposed for the diagnosis diabetes in manner that rapid cost-effective. three stages are involved diagnosis (DDS) including: dataset constructing, preprocessing classification algorithm using traditional Naïve Bayesian (TNB) modified (MNB)). MNB Classifier NB that used enhance accuracy diagnosis, by adding modest model help separate the overlapping classes. outcome showed classifier generally higher than TNB classifier all sets features. An about (63%) was achieved TNB model, whereas (100%). experimental results showed better NB both two cases constructed datasets; first case filling missing values experiences second missing K-nearest neighbor (KNN) algorithm.</span>
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ژورنال
عنوان ژورنال: Indonesian Journal of Electrical Engineering and Computer Science
سال: 2022
ISSN: ['2502-4752', '2502-4760']
DOI: https://doi.org/10.11591/ijeecs.v28.i3.pp1766-1774