Abstract
In this study, a new approach to Kohonen Self-Organizing Maps fusion is presented: the use of modified cluster validity indexes as a criterion for merging Kohonen Maps. Computational simulations were performed with traditional dataset from the UCI Machine Learning Repository, with variations in map size, number of subsets to be merged and the percentage of dataset bagging. The fusion results were compared with a regular single Kohonen Map. In some selected parameters, the proposed method achieves a better accuracy measure.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Dietterich, T.G.: Ensemble methods in machine learning. In: Kittler, J., Roli, F. (eds.) MCS 2000. LNCS, vol. 1857, pp. 1–15. Springer, Heidelberg (2000)
Hansen, L.K., Salamon, P.: Neural network ensembles. IEEE Transactions on Pattern Analysis and Machine Intelligence 12, 10 (1990)
Perrone, M.P., Cooper, L.N.: When networks disagree: ensemble methods for hybrid neural networks. In: Neural Networks for Speech and Image Processing, pp. 126–142. Chapman and Hall (1993)
Kohonen, T.: Self-organized maps, 2nd edn. Springer, Berlin (1997)
Breiman, L.: Bagging predictors. Machine Learning 24, 123–140 (1996)
Zhou, Z.-H., Wu, J., Tang, W.: Ensembling neural networks: many could be better than all. Artificial Intelligence 137(1-2), 239–263 (2002)
Gonçalves, M.L., De Andrade Netto, M.L., Costa, J.A.F., Zullo, J.: Data clustering using self-organizing maps segmented by mathematic morphology and simplified cluster validity indexes: an application in remotely sensed images. In: International Joint Conference on Neural Networks, IJCNN 2006, pp. 4421–4428 (2006)
Georgakis, A., Li, H., Gordan, M.: An ensemble of SOM networks for document organization and retrieval. In: International Conference on Adaptive Knowledge Representation and Reasoning (2005)
Saavedra, C., Salas, R., Moreno, S., Allende, H.: Fusion of self organizing maps. In: Sandoval, F., Prieto, A.G., Cabestany, J., Graña, M. (eds.) IWANN 2007. LNCS, vol. 4507, pp. 227–234. Springer, Heidelberg (2007)
Corchado, E., Baruque, B.: WeVoS-ViSOM: an ensemble summarization algorithm for enhanced data visualization. Neurocomputing 75, 171–184 (2012)
Borrajo, M.L., Baruque, B., Corchado, E., Bajo, J., Corchado, J.M.: Hybrid neural intelligent system to predict business failure in small-to-medium-size enterprises. International Journal of Neural Systems 21(04), 277–296 (2011)
Jiang, Y., Zhi-Hua, Z.: SOM ensemble-based image segmentation. Neural Processing Letters 20(3), 171–178 (2004)
Low, K.H., Wee, K.L., Marcelo, H.A.: An ensemble of cooperative extended Kohonen maps for complex robot motion tasks. Neural Computation 17, 1411–1445 (2005)
DeLooze, L.L.: Attack characterization and intrusion detection using an ensemble of self-organizing maps. In: 2006 IEEE Information Assurance Workshop, pp. 108–115 (2006)
Fustes, D., Dafonte, C., Arcay, B., Manteiga, M., Smith, K., Vallenari, A., Luri, X.: SOM ensemble for unsupervised outlier analysis. Application to outlier identification in the Gaia astronomical survey. Expert Systems with Applications 40(5), 1530–1541 (2013)
Tsai, C.-F.: Combining cluster analysis with classifier ensembles to predict financial distress. Information Fusion 16, 46–58 (2014)
Halkidi, M., Vazirgiannis, M.: A density-based cluster validity approach using multi-representatives. Pattern Recognition Letters 29, 773–786 (2008)
Milligan, G.W., Cooper, M.C.: An examination of procedures for determining the number of clusters in a data set. Psychometrika 50, 159–179 (1985)
Bezdek, J.C., Pal, N.R.: Some new indexes of cluster validity. IEEE Transactions on Systems, Man and Cybernetic. B 28, 301–315 (1998)
Pakhira, M.K., Bandopadhyay, S., Maulik, U.: Validity index for crisp and fuzzy clusters. Pattern Recognition 37(3), 487–501 (2004)
Davies, D.L., Bouldin, D.W.: A cluster separation measure. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-1(2), 224–227 (1979)
Bache, K., Lichman, M.: Machine Learning Repository. University of California, Irvine, School of Information and Computer Sciences (2013), http://archive.ics.uci.edu/ml
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Pasa, L.A., Costa, J.A.F., de Medeiros, M.G. (2014). Fusion of Kohonen Maps Ranked by Cluster Validity Indexes. In: Polycarpou, M., de Carvalho, A.C.P.L.F., Pan, JS., Woźniak, M., Quintian, H., Corchado, E. (eds) Hybrid Artificial Intelligence Systems. HAIS 2014. Lecture Notes in Computer Science(), vol 8480. Springer, Cham. https://doi.org/10.1007/978-3-319-07617-1_57
Download citation
DOI: https://doi.org/10.1007/978-3-319-07617-1_57
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07616-4
Online ISBN: 978-3-319-07617-1
eBook Packages: Computer ScienceComputer Science (R0)