Performance Analysis of Machine Learning Classifier for Predicting Chronic Kidney Disease

Chronic Kidney Disease (CKD) is a type of chronic disease which means it happens slowly over a period of time and persists for a long time thereafter. It is deadly at its end stage and will only be cured by kidney replacement or regular dialysis which is an artificial filtering mechanism. It is important to identify CKD at the early stage so that necessary treatments can be provided to prevent or cure the disease. The main focus in this paper is on the classification techniques, that is, tree-based decision tree, random forest, and logistic regression has been analyzed. Different measure has been used for comparison between algorithms for the dataset collected from standard UCI repository.