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Visualizing and classifying data using a hybrid intelligent system

conference contribution
posted on 2006-01-01, 00:00 authored by C Teh, Chee Peng LimChee Peng Lim
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.

History

Event

Artificial Intelligence, Knowledge Engineeering and Data Bases. Conference (5th : 2006 : Madrid, Spain)

Pagination

13 - 17

Publisher

World Scientific and Engineering Academy and Society (WSEAS)

Location

Madrid, Spain

Place of publication

Stevens Point, Wis.

Start date

2006-02-15

End date

2006-02-17

Language

eng

Publication classification

E1.1 Full written paper - refereed

Editor/Contributor(s)

P Espi, J Giron-Sierra, A Drigas

Title of proceedings

AIKED '06 : Proceedings of the 5th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering, and Databases

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