Classification rules mining based on SOFM networks

Min Yao; Zhiwei Jiang; Bin Shen

doi:10.1117/12.650712

2 December 2005 Classification rules mining based on SOFM networks

Min Yao, Zhiwei Jiang, Bin Shen

Proceedings Volume 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications; 604511 (2005) https://doi.org/10.1117/12.650712
Event: MIPPR 2005 SAR and Multispectral Image Processing, 2005, Wuhan, China

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.

Citation Download Citation

Min Yao, Zhiwei Jiang, and Bin Shen "Classification rules mining based on SOFM networks", Proc. SPIE 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications, 604511 (2 December 2005); https://doi.org/10.1117/12.650712

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