ITERATIVE DICHOTOMISER-3 ALGORITHM IN DATA MINING APPLIED TO DIABETES DATABASE

Abstract

In this study, eight major factors playing significant role in the Pima Indian population are analyzed. Real time data is taken from the large dataset of National Institute of Diabetes and Digestive and Kidney Diseases. The data is subjected to an analysis by logistic regression method using SPSS 7.5 statistical software, to isolate the most significant factors among the eight factors taken. Then the significant factors are further applied to decision tree technique called the Iterative Dichotomiser-3 algorithm which leads to significant conclusions about this diabetes disorder which poses to be a greatest threat to mankind in the coming era. Conglomeration of data mining techniques and medical data base research can lead to life saving conclusions for the physicians at critical times to save the mankind.