Classification Analysis using Back Propagation Neural Network and Radial Basis Function Neural Network

Abstract

Neural networks are a very popular data mining, classification and image processing tool.The fundamental concept of neural networks is the structure of the information processing system composed of a large number of highly interconnected processing elements or neurons. In this paper, thepropertiesof the two typeof neural networks: back propagation (BP) neural network and radial basis function (RBF) neural network, are analyzed and compared based on mean square error, accuracy and nature of datasets. The four datasets (breast cancer, car, iris, wine) are used from UCI machine learning repository.