Visualizing and classifying data using a hybrid intelligent system

Teh, Chee Siong and Lim, Chee Peng 2006, Visualizing and classifying data using a hybrid intelligent system, in AIKED '06 : Proceedings of the 5th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering, and Databases, World Scientific and Engineering Academy and Society (WSEAS), Stevens Point, Wis., pp. 13-17.

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Title Visualizing and classifying data using a hybrid intelligent system
Author(s) Teh, Chee Siong
Lim, Chee Peng
Conference name Artificial Intelligence, Knowledge Engineeering and Data Bases. Conference (5th : 2006 : Madrid, Spain)
Conference location Madrid, Spain
Conference dates 15-17 Feb. 2006
Title of proceedings AIKED '06 : Proceedings of the 5th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering, and Databases
Editor(s) Espi, Pablo Luis Lopez
Giron-Sierra, Jose M.
Drigas, A. S.
Publication date 2006
Conference series Artificial Intelligence, Knowledge Engineeering and Data Bases. Conference
Start page 13
End page 17
Total pages 5
Publisher World Scientific and Engineering Academy and Society (WSEAS)
Place of publication Stevens Point, Wis.
Keyword(s) hybrid intelligent system
data classification
multi-dimensional data projection
data visualization
Summary 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.
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30048735

Document type: Conference Paper
Collection: Centre for Intelligent Systems Research
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