
Proceedings Paper
Knowledge extracted from trained neural networks: What's next?Format | Member Price | Non-Member Price |
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Paper Abstract
One of the major drawbacks or challenges of neural network models
is that these models can not explain what they have done. Extracting rules from trained neural networks is one of the solutions for understanding the networks. However, what we should do with these extracted rules remains a research question. This paper tries to address issues on effectively and efficiently utilizing extracted rules or knowledge.
Paper Details
Date Published: 28 March 2005
PDF: 7 pages
Proc. SPIE 5812, Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2005, (28 March 2005); doi: 10.1117/12.604463
Published in SPIE Proceedings Vol. 5812:
Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2005
Belur V. Dasarathy, Editor(s)
PDF: 7 pages
Proc. SPIE 5812, Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2005, (28 March 2005); doi: 10.1117/12.604463
Show Author Affiliations
Jing Tao Yao, Univ. of Regina (Canada)
Published in SPIE Proceedings Vol. 5812:
Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2005
Belur V. Dasarathy, Editor(s)
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