Detection and Evaluation of Chronic Kidney Disease Using Different Regression and Classification Algorithms in Machine Learning

摘要

Nowadays, many people are suffering from chronic kidney disease worldwide. Factors responsible for such conditions are food, living standards, and the environment. Detection and identification of chronic kidney disease are costly, time-consuming, and often risky. Therefore, the early detection of such disease is very important. In this research study, we have tried to reduce the clinical effort by automating the process of detection. We have classified whether the person is suffering from chronic kidney disease or not. We have used different classification algorithms and regression algorithms like KNN, SVM, Naive Bayes, and logistic regression. We have got some good results in all the algorithms but KNN performed very well.