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Proceedings Paper

Classification rules mining based on SOFM networks
Author(s): Min Yao; Zhiwei Jiang; Bin Shen
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Paper Abstract

Self-organization feature mapping (SOFM) networks have strong ability for self-learning and self-adaptive. According to the characteristics of human thought, this paper constructed a kind of combined criterion, which may be used to guide the learning of self-organization feature mapping network. Then this paper presents subsection algorithm, amalgamation algorithm and dynamical adaptive algorithm for SOFM networks so as to solve a kind of problems of classification rule mining. Finally, a practical example shows its flexibility and practicability.

Paper Details

Date Published: 2 December 2005
PDF: 6 pages
Proc. SPIE 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications, 604511 (2 December 2005); doi: 10.1117/12.650712
Show Author Affiliations
Min Yao, Zhejiang Univ. (China)
Suzhou Univ. (China)
Zhiwei Jiang, Zhejiang Univ. (China)
Bin Shen, Zhejiang Univ. (China)
Suzhou Univ. (China)

Published in SPIE Proceedings Vol. 6045:
MIPPR 2005: Geospatial Information, Data Mining, and Applications
Jianya Gong; Qing Zhu; Yaolin Liu; Shuliang Wang, Editor(s)

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