Abstract
This paper analyzes the use of ARTMAP-based in structures of ensembles designed by three variants of boosting (Aggressive, Conservative and Inverse). In this investigation, it is aimed to analyze the influence of the RePART (Reward and Punishment ARTmap) neural network in ARTMAP-based ensembles, intending to define whether the use of this model is positive for ARTMAP-based ensembles. In addition, it aims to define which boosting strategy is the most suitable to be used in ARTMAP-based ensembles.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Canuto, A., Howells, G., Fairhurst, M.: An investigation of the effects of variable vigilance within the repart neuro-fuzzy network. J. of Int. and Robotics Systems 29(4), 317–334 (2000)
Canuto, A., Fairhurst, M., Howells, G.: Improving artmap learning through variable vigilance. International Journal of Neural Systems 11(6), 509–522 (2001)
Canuto, A.: Combining neural networks and fuzzy logic for applications in character recognition. PhD thesis, University of Kent (2001)
Canuto, A., Santos, A.: A Comparative Investigation of the RePART Neural Network in Pattern Recognition Tasks. In: Proceedings of IEEE IJCNN 2004 (2004)
Kuncheva, L.I.: Combining Pattern Classifiers. Methods and Algorithms. Wiley, Chichester (2004)
Sharkey, A.J.C.: Multi-net System. In: Sharkey, A.J.C. (ed.) Combining Artificial Neural Nets: Ensemble and Modular Multi-net Systems, pp. 1–30. Springer, Heidelberg (1999)
Santos, A., Canuto, A.M.: Investigating the Influence of RePART in Ensemble Systems Designed by Boosting. In: IJCNN 2008 (accepted, 2008)
Carpenter, G., Grossberg, S., Reynolds, J.H.: Artmap: Supervised real-time learning and classification of nonstationary data by a self-organizing neural network. Neural Networks 4, 565–588 (1991)
Carpenter, G., Grossberg, S., Markunzo, M., Reynolds, J.H., Rosen, D.B.: Fuzzy artmap: A neural network architecture for incremental supervised learning of analog multidimensional maps. IEEE Transactions on Neural Networks 3, 698–713 (1992)
Carpenter, G., Markuzon, N.: Artmap-IC and medical diagnosis: instance counting and inconsistent cases. Neural Networks 11, 323–336 (1998)
Kuncheva, L., Whitaker, C.J.: Using diversity with three variants of boosting: Aggressive, conservative, and inverse. Multiple Classifier Systems (2002)
Blake, C.L., Merz, C.J.: UCI Repository of machine learning databases. University of California, Dep. of Inf. and Computer Science (1998), http://www.ics.uci.edu/~mlearn/MLRepository.html
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
de Medeiros Santos, A., de Paula Canuto, A.M. (2008). Using ARTMAP-Based Ensemble Systems Designed by Three Variants of Boosting. In: Kůrková, V., Neruda, R., KoutnÃk, J. (eds) Artificial Neural Networks - ICANN 2008. ICANN 2008. Lecture Notes in Computer Science, vol 5163. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87536-9_58
Download citation
DOI: https://doi.org/10.1007/978-3-540-87536-9_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87535-2
Online ISBN: 978-3-540-87536-9
eBook Packages: Computer ScienceComputer Science (R0)