Author, Subjects, Keywords

Cited Author

 
 
   » By Author or Editor
 » Browse Author by Alphabet
 » By Journal
 » By Subjects
 » By Affiliations
 » By Type
 » By Year
 » By Latest Additions
 
 
   » By Author
 » Top 20 Authors
 » Top 20 Article
 » Top 20 Journal Cited
 » Top 20 Cited
 » Top 20 Author Cited
 » Usage Since Sept 2007


 
 
 

Login | Create Account

Generalization Performance Analysis Between Fuzzy Artmap And Gaussian Artmap Neural Network

Yaakob Shahrul Nizam, and Saad Puteh , (2007) Generalization Performance Analysis Between Fuzzy Artmap And Gaussian Artmap Neural Network. Malaysian Journal of Computer Science, 20 (1). pp. 13-22. ISSN 0127-9084

Full text not available from this repository.

Official URL: http://mjcs.fsktm.um.edu.my/detail.asp?AID=491

Affiliations

Universiti Malaysia Perlis
Universiti Teknologi Mlaysiai

Abstract

This paper examines the generalization characteristic of Gaussian ARTMAP (GAM) neural network in classification tasks. GAM performance for classification during training and testing is evaluated using the k-folds cross validation technique. A comparison is also done between GAM and Fuzzy ARTMAP (FAM) neural network. It is found that GAM performs better (98-99%) when compared to FAM (79-82%) using two different types of dataset. The difference between GAM and FAM is that input data to be to classified using FAM must be normalized in prior. Hence, three different normalization techniques are examined namely; unit range (UR), improved unit range (IUR) and improve linear scaling (ILS). This paper also proposes an alternative technique to search the best value for gamma ? parameter of GAM neural network, known as gamma threshold. A small number of training required for GAM also shows that its fundamental architecture retain the attractive parallel computing and fast learning properties of FAM.

Item Type:Journal
Keywords:Gaussian ARTMAP (GAM), Fuzzy ARTMAP (FAM), gamma threshold
Subjects:Q Science
ID Code:261

G. C. Anagnostopoulos & M. Georgiopulos, “Hypersphere ART and ARTMAP for unsupervised and supe-rvised, incremental learning”, in Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000, IJCNN 2000, Vol. 6, pp. 59 – 64.

G. C. Anagnostopoulos & M. Georgiopulos, “Ellipsoid ART and ARTMAP for incremental clustering and cla-ssification”, in International Joint Conference on Neural Networks, 2001, Proceedings IJCNN '01, Vol. 2, pp. 1221 – 1226.

G. C. Anagnostopoulos et al. (2002). “Reducing generalization error and category proliferation in ellipsoid ARTMAP via tunable misclassification error tolerance: boosted ellipsoid ARTMAP”, in Proceedings of the 2002 International Joint Conference on Neural Networks, 2002, IJCNN '02, Vol. 3, pp. 2650 – 2655.

A. Baraldi & E. Alpaydin, “Constructive Feedforward ART Clustering Network - Part I”. IEEE Transactions on Neural Networks, Vol. 13 No. 3, 2002, pp. 645-661.

G. A. Carpenter et al., “Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps”, IEEE Transactions on Neural Networks, Vol. 3, Issue. 5, 1992, pp. 698 – 713.

G. A. Carpenter et al., (1992). ”Fuzzy ARTMAP: an adaptive resonance architecture for incremental learning of analog maps” in International Joint Conference on Neural Networks, 1992, IJCNN, Vol. 3, 1992, pp. 309 – 314.

G. A. Carpenter & S. Grossberg, “A self-organizing neural network for supervised learning, recognition and prediction”. IEEE Communications Magazine, Vol. 30, Issue. 9, 1992, pp. 38–49.

M. Georgiopoulos, “Overtraining in fuzzy ARTMAP: Myth or reality?” in International Joint Conference on Neural Networks, 2001. Proceedings. IJCNN '01, Vol. 2, pp. 1186 – 1190.

E. Gomez-Sanchez, Y. A. Dimitriadis, J. Cano-Izquierdo & J.M. Lopez-Coronado, “µARTMAP: use of mut-ual information for category reduction in Fuzzy ARTMAP”. IEEE Transactions on Neural Networks, Vol. 13, Issue. 1, Jan. 2002. pp. 58 – 69.

P. Henniges, E. Granger & R. Sabourin, “Factors of overtraining with fuzzy ARTMAP neural networks”. In Proceedings of the 2005 IEEE International Joint Conference on Neural Networks, 2005. IJCNN '05, Vol. 2, pp. 1075 – 1080.

B.W. Jervis, S. Djebali & L. Smaglo, “Integrated probabilistic simplified fuzzy ARTMAP”. IEE Proceedings on Science, Measurement and Technology, Vol. 151, Issue. 3, 2004, pp. 218 – 228.

M.L.M Lopes, C.R. Minussi & A.D. Lotufo, “Electric load forecasting using a fuzzy ART and ARTMAP neural network”. Applied soft computing. Vol. 5, Issue. 2, 2004, pp. 235-244.

B. S. Puteh et al., “A Comparison of Feature Normalization Technique on Complex Image recognition” in The 2nd Conference on Information Technology in Asia (CITA 01), 2001.

B. S. Puteh et al., “Effect of Normalization on Rice Yield Prediction” in National Postgraduate Colloquium 04, Penang, 8-9 Dec 2004, pp. 330 – 335.

N. Y. Shahrul, Binary Image Classification using Fuzzy and Gaussian ARTMAP neural networks. Msc thesis. School of Computer and Communication. KUKUM 2006.

S. J. Verzi et al., “Boosted ARTMAP” in The 1998 IEEE International Joint Conference on Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence, Vol. 1, pp. 396 – 401.

S. J. Verzi et al., “Hierarchical ARTMAP” in Proceedings of the IEEE-INNS-ENNS International Joint Con-ference on Neural Networks, 2000. IJCNN 2000, Vol. 6, pp. 41 – 46.

J. R. Wiliamson, “Gaussian ARTMAP: A neural network for fast incremental learning of noisy multi-dimensional maps”, Neural Networks, Vol. 9, No.5, 1996, pp. 881-897.

Repository Staff Only: item control page
 
 
 
 
 
   
© Copyright 2007 MyAIS Faculty of Computer Science and Information Technology, University of Malaya – All Rights Reserved. Malaysian Abstracting and Indexing System is powered by EPrints 3 which is developed by the School of Electronics and Computer Science at the University of Southampton. More information and software credits.