Chronic Kidney Disease Prediction using Machine Learning Algorithms

Kidney diseases are increasing day by among people. It is becoming a major health issue around the world. Not maintaining proper food habits and drinking less amount of water one reasons that contribute this condition. With this, it has become necessary to build up system foresee Chronic Diseases precisely. Here, we have proposed an approach for real time kidney disease prediction. Our aim find best efficient machine learning (ML) application can effectively recognize predict condition chronic disease. We used data from UCI repository. In work, five important classification techniques were considered predicting which KNN, Logistic Regression, Random Forest Classifier, SVM Decision Tree Classifier. process, been divided into two sections. section train dataset got trained another evaluated test dataset. The analysis results show Classifier Regression algorithms achieved highest performance than other classifiers, obtaining accuracy 98.75% followed random Forest, stands at 97.5%.