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Proceedings Paper

Feature selection based on neuro-fuzzy networks
Author(s): Nong Sang; Yantao Xie; Tianxu Zhang
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Paper Abstract

Feature selection algorithm based on artificial neural networks can be taken as a special case of architecture pruning algorithm: compute the sensitivity of network outputs against pruned features. However, these methods usually require preprocessing of data normalization, which will possibly change original data's characters that are important to classification. Neuro-fuzzy (NF) network is a fuzzy inference system (FIS) with self-study ability. We combine it with architecture pruning algorithm based on membership space and propose a new feature selection algorithm. Finally, experiments using both natural and integrated data are carried out and compared with other methods. The results approve the validity of the algorithm.

Paper Details

Date Published: 25 May 2005
PDF: 8 pages
Proc. SPIE 5809, Signal Processing, Sensor Fusion, and Target Recognition XIV, (25 May 2005); doi: 10.1117/12.606149
Show Author Affiliations
Nong Sang, Huazhong Univ. of Science and Technology (China)
Yantao Xie, Huazhong Univ. of Science and Technology (China)
Tianxu Zhang, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 5809:
Signal Processing, Sensor Fusion, and Target Recognition XIV
Ivan Kadar, Editor(s)

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