Chronic Kidney Disease is a very dangerous health problem that has been spreading as well as growing due to diversification in life style such as food habits, changes in the atmosphere, etc. The branch of biosciences has progressive to a bigger extent and has bring out huge amounts of data from Electronic Health Records. The primary aim of this paper is to classify using various Classification techniques like Logistic Regression (LR), K-Nearest Neighbor (KNN) Classifier, Decision Tree Classifier Tree, Random Forest Classifier, Support Vector Machine (SVM), and SGD Classifier. According to the health statistics of India 63538 cases has been registered on chronic renal disorder. Average age of men and women susceptible to renal disorders occurs within the range of 48 to 70 years.
CITATION STYLE
Reddy*, M. P., & Devi, Dr. T. U. (2020). Prediction of Diagnosing Chronic Kidney Disease using Machine Learning: Classification Algorithms. International Journal of Innovative Technology and Exploring Engineering, 9(6), 1922–1924. https://doi.org/10.35940/ijitee.f3989.049620
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