Data mining using Artificial Neural network tree

Proper diagnosis, classification and prediction of diabetes are essential due to the increasing prevalence of the disease and the increasing cost to control it. Appropriate discovery of knowledge from historical data for this disease would be a valuable tool for clinical researchers. The main purpose of data mining is to gain insight of the data, and extract knowledge (inter-relational patterns) from the data. Applying data mining techniques in diabetic data can facilitate systematic analysis. Artificial Neural network (ANN) has already been applied in a variety of domains with remarkable success. However, it has not has been well utilized in data mining because of the “black box” nature. In this paper we present a method of using ANN in data mining and overcoming the “black box” nature using Decision Tree (DT).