Improved Gradient Descent Back Propagation Neural Networks for Diagnoses of Type II Diabetes Mellitus

The proposed method is a classification problem to diagnose Type II diabetes mellitus using improved Gradient Descent back propagation algorithm. The objective of this research is to increase the performance of the network in terms of accuracy. The accuracy was increased by using three key concepts: missing data replacement, data preprocessing and introducing the Performance Vector (PV) in the search direction. The results of the network have been tested using Pima Indian Diabetes Dataset. This experimental system improves the performance more than 7% than the standard Gradient Descent method