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Abstract: Interest in the application of neural networks as tools for decision support has been growing in recent years. A major drawback often associated with neural networks is the difficulty in understanding the knowledge represented by a trained network. This paper describes an approach that can extract symbolic rules from neural networks. We illustrate how the approach successfully extracted rules from a data set collected from a survey of the service sectors in the United Kingdom. The extracted... (Update)
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BibTeX entry: (Update)
@misc{ setiono-symbolic,
author = "Rudy Setiono and James Y.L. Thong and Chee-Sing Yap",
title = "Symbolic rule extraction from neural networks: An application to identifying
organizations adopting IT",
url = "citeseer.ist.psu.edu/281314.html" }
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