2026-07-29T15:36:07Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/6182 2021-12-13T05:26:03Z 1582963342780:1596102355557 user-uit

Comparative Study of Classification Algorithms for Diabetes and Chronic Kidney Disease Diagnosis Aung Nway Oo Khin Thuzar Win Now a day, data mining and machine learning methods are used to analyse the medical dataset. These techniques can reduce the number of tests to be taken by a patient, can save cost and can also save time for both, doctors and patients. Classification is a classic data mining technique based on machine learning. There are many classification algorithms that can be used for medical domain. In this paper, Naïve Bayes, Random Forest, KStar and PART classification algorithms are used to classify Diabetes dataset and Chronic Kidney Disease (CKD) dataset. The main objective of this paper is to compare the classification results of each classifier for Diabetes dataset and Chronic Kidney Disease (CKD) dataset. 2019-08-17 http://hdl.handle.net/20.500.12678/0000006182 https://meral.edu.mm/records/6182