TY - JOUR TI - Chronic Kidney Disease Prediction System AU - Ammavajjula Sai Tejaswi AU - Animilla Swapna Deepika AU - Yaragani Sowmya JO - International Journal of Scientific Research in Computer Science, Engineering and Information Technology PB - Technoscience Academy DA - 2020/04/30 PY - 2020 DO - https://doi.org/10.32628/CSEIT206215 UR - https://ijsrcseit.com/CSEIT206215 VL - 6 IS - 2 SP - 43 EP - 47 AB - Chronic Kidney Disease (CKD) is a very dangerous health problem that has been spreading due to globally due to alterations in lifestyle such as food habits, changes in the atmosphere, etc. So, it is essential to decide any remedies to avoid and predict the disease in an early stage. This paper focuses on predictive analytics architecture to analyze the CKD dataset using feature engineering and classification algorithm. The proposed model incorporates techniques to validate the feasibility of data points used for analysis. The main focus of research work is to analyze the dataset of chronic kidney failure and perform the classification of CKD and Non-CKD cases.