Use of circle-segments as a data visualization technique for feature selection in pattern classification

Wang, Shir Li, Loy, Chen Change, Lim, Chee Peng, Lai, Weng Kin and Tan, Kay Sin 2007, Use of circle-segments as a data visualization technique for feature selection in pattern classification, in Neural Information Processing 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Springer-Verlag, Berlin, Germany, pp.625-634.

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Title Use of circle-segments as a data visualization technique for feature selection in pattern classification
Author(s) Wang, Shir Li
Loy, Chen Change
Lim, Chee Peng
Lai, Weng Kin
Tan, Kay Sin
Title of book Neural Information Processing 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers
Editor(s) Ishikawa, Masumi
Publication date 2007
Series Lecture notes in computer science ; 4984-4985.
Chapter number 65
Total chapters 116
Start page 625
End page 634
Total pages 10
Publisher Springer-Verlag
Place of Publication Berlin, Germany
Keyword(s) feature selection
circle-segments
data visualization
principal component analysis
machine learning techniques
Summary One of the issues associated with pattern classification using data based machine learning systems is the “curse of dimensionality”. In this paper, the circle-segments method is proposed as a feature selection method to identify important input features before the entire data set is provided for learning with machine learning systems. Specifically, four machine learning systems are deployed for classification, viz. Multilayer Perceptron (MLP), Support Vector Machine (SVM), Fuzzy ARTMAP (FAM), and k-Nearest Neighbour (kNN). The integration between the circle-segments method and the machine learning systems has been applied to two case studies comprising one benchmark and one real data sets. Overall, the results after feature selection using the circle segments method demonstrate improvements in performance even with more than 50% of the input features eliminated from the original data sets.
ISBN 3540691545
9783540691549
Language eng
Field of Research 109999 Technology not elsewhere classified
Socio Economic Objective 970110 Expanding Knowledge in Technology
HERDC Research category B1.1 Book chapter
Persistent URL http://hdl.handle.net/10536/DRO/DU:30050274

Document type: Book Chapter
Collection: Institute for Frontier Materials
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