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Visualizing and classifying data using a hybrid intelligent system
In this paper, a hybrid intelligent system that integrates the SOM (Self-Organizing Map) neural network, kMER (kernel-based Maximum Entropy learning Rule), and Probabilistic Neural Network (PNN) for data visualization and classification is proposed. The rationales of this Probabilistic SOM-kMER model are explained, and its applicability is demonstrated using two benchmark data sets. The results are analyzed and compared with those from a number of existing methods. Implication of the proposed hybrid system as a useful and usable data visualization and classification tool is discussed.
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Artificial Intelligence, Knowledge Engineeering and Data Bases. Conference (5th : 2006 : Madrid, Spain)Pagination
13 - 17Publisher
World Scientific and Engineering Academy and Society (WSEAS)Location
Madrid, SpainPlace of publication
Stevens Point, Wis.Start date
2006-02-15End date
2006-02-17Language
engPublication classification
E1.1 Full written paper - refereedEditor/Contributor(s)
P Espi, J Giron-Sierra, A DrigasTitle of proceedings
AIKED '06 : Proceedings of the 5th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering, and DatabasesUsage metrics
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