The Methodology imbibed in this paper is survey of select set
of Data mining methods for predicting immediate or later
incidence of the life threatening disease, the Diabetes Mellitus.
Over the last years several papers have been published on the
problem of analyzing DM data. In 1994, for example, the AAAI
spring symposium on artificial intelligence in medicine
published a BG home monitoring data set as a challenge for
applying machine learning and artificial intelligence methods to
describe and predict BG values. Another well known data set
available is at the University of California. Irvine data
repository, the so called “Pima Indians” Diabetes database,
which is a collection of medical diagnostic reports of 768
samples. There have been many studies applying data mining
techniques to the PIDD.