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.