A Predictive Analysis of Chronic Kidney Disease by Exploring Important Features

Abstract

Chronic Kidney Disease is an incurable disease which causes damages to the functions of a kidney gradually. Only proper treatment can prevent the disease from getting worse. Because of proper knowledge about kidney disorders, people had to suffer from this deadly disease. Thus, in this paper, we analyzed certain key features and noticed several interesting relationships with the disease by considering the actual perception of people. We also predict kidney disease by employing various machine learning algorithms including Logistic Regression, Naive Bayes, SVM and KNN. By applying PCA, we observe that there is an improvement in the accuracy for predicting the disease. SVM outperforms other algorithms with 98% accuracy in predicting chronic kidney disease. In future, we will try to find some significant hypothesis that helps us to prevent the disease better.