Proceedings of the 2013 International Conference on Advances in Intelligent Systems in Bioinformatics

Verifying the Accuracy of GDAM algorithm on Multiple Classification Problems

Authors
Nazri Mohd Nawi, M.Z Rehman, Abdullah Khan
Corresponding Author
Nazri Mohd Nawi
Available Online January 2014.
Keywords
neural networks, gradient descent, adaptive momentum, adaptive gain
Abstract
Back-Propagation Neural Network (BPNN) algorithm is a widely used technique implemented in many engineering disciplines. Despite solving several practical problems around the globe, BPNN still faces problems like slow convergence, network stagnancy and convergence to local minima. Many alternative ways of improving the convergence rate in BPNN are suggested by previous researchers such as the careful selection of input weights and biases, learning rate, momentum, network topology, activation function and value for ‘gain’ in the activation function. This research propose an algorithm for improving the working performance of back-propagation algorithm which is ‘Gradient Descent with Adaptive Momentum (GDAM)’ by keeping the gain value fixed during all network trials. The performance of GDAM is compared with ‘Gradient Descent with fixed Momentum (GDM)’ and ‘Gradient Descent Method with Adaptive Gain (GDM-AG)’. The results show that GDAM is a better approach than previous methods and shows better accuracy on selected classification problems like Wine Quality, Mushroom, Thyroid disease Breast Cancer, IRIS, Australian Credit Card Approval, Pima Indian Diabetes, and Heart Disease.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 2013 International Conference on Advances in Intelligent Systems in Bioinformatics
Series
Advances in Intelligent Systems Research
Publication Date
January 2014
ISBN
978-94-6252-000-4
ISSN
1951-6851
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Nazri Mohd Nawi
AU  - M.Z Rehman
AU  - Abdullah Khan
PY  - 2014/01
DA  - 2014/01
TI  - Verifying the Accuracy of GDAM algorithm on Multiple Classification Problems
BT  - Proceedings of the 2013 International Conference on Advances in Intelligent Systems in Bioinformatics
PB  - Atlantis Press
SP  - 51
EP  - 57
SN  - 1951-6851
UR  - https://www.atlantis-press.com/article/11357
ID  - Nawi2014/01
ER  -