REVIEW ON CLASSIFICATION BASED ON ARTIFICIAL NEURAL NETWORKS

Saravanan K1 and S. Sasithra2 1Assistant Professor/Department of Computer Engineering, Erode Sengunthar Engineering College, Erode, India 2 Department of Computer Engineering, Erode Sengunthar Engineering College, Erode, India 

ABSTRACT 

Artificial neural networks (ANN) consider classification as one of the most dynamic research and application areas. ANN is the branch of Artificial Intelligence (AI). The neural network was trained by back propagation algorithm. The different combinations of functions and its effect while using ANN as a classifier is studied and the correctness of these functions are analyzed for various kinds of datasets. The back propagation neural network (BPNN) can be used as a highly successful tool for dataset classification with suitable combination of training, learning and transfer functions. When the maximum likelihood method was compared with backpropagation neural network method, the BPNN was more accurate than maximum likelihood method. A high predictive ability with stable and well functioning BPNN is possible. Multilayer feed-forward neural network algorithm is also used for classification. However BPNN proves to be more effective than other classification algorithms. 

KEYWORDS 

Back propagation algorithm, Maximum Likelihood method, Multilayer feed-forward neural network. 

More Details : http://airccse.org/journal/ijasa/papers/2414asa02.pdf