Diabetes Disease Prediction System using HNB classifier based on Discretization Method

Bassam Abdo, Al-Hameli and Alsewari, AbdulRahman and Basurra, Shadi and Bhogal, Jagdev and Ali, Mohammed (2023) Diabetes Disease Prediction System using HNB classifier based on Discretization Method. Journal of Integrative Bioinformatics. ISSN 1613-4516

Preview

Text 10.1515_jib-2021-0037.pdf - Published Version Available under License Creative Commons Attribution. Download (1MB)

Abstract

Diagnosing diabetes early is critical as it helps patients live with the disease in a healthy way - through healthy eating, taking appropriate medical doses, and making patients more vigilant in their movements/activities to avoid wounds that are difficult to heal for diabetic patients. Data mining techniques are typically used to detect diabetes with high confidence to avoid misdiagnoses with other chronic diseases whose symptoms are similar to diabetes. Hidden Naïve Bayes is one of the algorithms for classification, which works under a data-mining model based on the assumption of conditional independence of the traditional Naïve Bayes. The results from this research study, which was conducted on the Pima Indian Diabetes (PID) dataset collection, show that the prediction accuracy of the HNB classifier achieved 82%. As a result, the discretization method increases the performance and accuracy of the HNB classifier.

Item Type:	Article
Identification Number:	10.1515/jib-2021-0037
Dates:	Date Event 22 November 2022 Accepted 23 February 2023 Published Online
Uncontrolled Keywords:	classification, data mining, discretization, HNB, Pima dataset
Subjects:	CAH11 - computing > CAH11-01 - computing > CAH11-01-02 - information technology CAH11 - computing > CAH11-01 - computing > CAH11-01-03 - information systems CAH11 - computing > CAH11-01 - computing > CAH11-01-05 - artificial intelligence
Divisions:	Faculty of Computing, Engineering and the Built Environment > College of Computing
Depositing User:	Abdulrahman Alsewari
Date Deposited:	27 Feb 2023 11:17
Last Modified:	27 Feb 2023 11:21
URI:	https://www.open-access.bcu.ac.uk/id/eprint/13989

Actions (login required)

View Item