*Assistant Professor, Computer Science, Muthurangam Government Arts College (Autonomous), Vellore – 632 002, Vellore District, Tamil Nadu, India
**Assistant Professor, Computer Science, Arignar Anna Government Arts College For Women, Walajapet – 632 513, Vellore District, Tamil Nadu, India
***Associate Professor, Computer Science & Head, Presidency College (Autonomous), Chennai – 600005, Tamil Nadu, India
Online published on 20 June, 2013.
The devastating disease HIV is well known as being the cause for development of Acquired Immunodeficiency Syndrome (AIDS). In the last 2 decades, over 60 million people have been infected with HIV, most of the people are identified and infected by HIV in the developing countries. In this paper Neural Networks are used as pattern recognition tools in data mining and social-economic characteristics. The data consists of surveillance information and contains the Demographic variables such as age, education, race, location and gravidity. Dempster Shafer (DS) theory is used to select the features from the data set and Bayesian method of training used was checked with the evidence framework. The design involves classification of HIV status and accuracy of prediction using Reference Model.
Demographic, Bayesian, Neural Network, Dempster-Shafer, Multilayer, Classification, Reference Model, Activation function
