Kidney Failure Due to Diabetics – Detection using Classification Algorithm in Data Mining

Abstract

In order to analyse the chosen data from various points of view, data mining is used as the effective process. This process is also used to sum up all those views into useful information. There are several types of algorithms in data mining such as Classification algorithms, Regression, Segmentation algorithms, association algorithms, sequence analysis algorithms, etc.,. The classification algorithm can be used to bifurcate the data set from the given data set and foretell one or more discrete variables, based on the other attributes in the dataset. The ID3 (Iterative Dichotomiser 3) algorithm is an original data set S as the root node. An unutilised attribute of the data set S calculates the entropy H(S) (or Information gain IG (A)) of the attribute. Upon its selection, the attribute should have the smallest entropy (or largest information gain) value. The prime objective of this paper is to analyze the data from a Kidney disorder due to diabetics by using classification technique to predict class accurately.