International OPEN ACCESS Journal Of Modern Engineering Research (IJMER) | IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 5 | Iss. 7 | July 2015 | 49 | Generating comparative analysis of early stage prediction of Chronic Kidney Disease L.Jerlin Rubini, Dr.P.Eswaran a Research Scholar, Department of Computer Science and Engineering, Alagappa University, Karaikudi b Assistant Professor, Department of Computer Science and Engineering, Alagappa University, Karaikudi I. INTRODUCTION Chronic kidney disease is one of the Kidney disease in medical field. Kidneys are a pair of organs located toward lower back of the body .It can be placed on either side of the spine. Main function of the Kidney act as a filtration system for blood and to remove toxins from body. The kidney shifts the toxins to the bladder then it later removed from the body through urination. Kidney failure occurs when the kidneys unable to filter waste from the blood.If kidneys cannot perform their regular job then body becomes overloaded with toxins. This can lead to kidney failure and can result in death. Kidney failure suffers from one or more of the following causes: Loss of Blood Flow to the Kidneys, Damage to the Kidneys and Urine Elimination Problems. Kidney problems can be either acute or chronic (fig:1). Acute kidney disease is the sudden loss of kidney function that occurs when high levels of waste products of the body's metabolism accumulate in the blood. Fig:1 Types of kidney disease Chronic kidney disease is a gradual development of permanent kidney disease.It is the most common type of kidney disease and occurs when the kidneys are damaged or are not functioning for some months or longer. Some of the leading causes of chronic kidney disease are diabetes, hypertension, lupus and complications from some medications. Medications can control hypertension and diabetes and changes in diet and lifestyle. Complications of chronic kidney disease such as anemia and weak bones leading to fractures.Chronic kidney disease includes a number of conditions affecting function of kidney.Many people may be in the early stages of kidney disease and not have any indication .There are certain symptoms,as follows for chronic kidney disease. Kidney Disease Acute Kidney Disease Chronic Kidney Disease ABSTRACT: Chronic Kidney Disease prediction is one of the most important issues in medical decision making. The discovery of ckd prediction is an important task because it depends on experts of doctor knowledge. Construct effective ckd prediction in time is essential to prevent healthy patients. Chronic kidney disease is one of the leading cause of death and early prediction of chronic kidney disease is important. Prediction is most interesting and challenging tasks in day to life. Data mining play a essential role for prediction of medical dataset. It extract unknown information from hidden knowledge. This paper can proposed a new chronic kidney disease dataset with three classifiers such as radial basis function network, multilayer perceptron, and logistic regression. The obtained result of this experiment shows in terms of prediction accuracy, type I error, type II error, type I error rate, type II error rate, sensitivity, specificity, F-score. Kappa value represents that measure of agreement between the classification made by the experts and classifiers. Accuracy of the three classifiers are evaluated for the new CDK dataset from UCI repository. Thus, the paper discussed the result of comparative study of classifiers in medical ckd dataset. Keywords: CKD, classification, RBF network, MLP, Logistic Regression.