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Asian Journal of Scientific Research
  Year: 2012 | Volume: 5 | Issue: 3 | Page No.: 121-132
DOI: 10.3923/ajsr.2012.121.132
 
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A Rule Extraction Algorithm That Scales Between Fidelity and Comprehensibility

Kalaiarasi Sonai Muthu Anbananthen, Fabian Chan Huan Pheng, Subhacini Subramaniam, Shohel Sayeed and Eimad Eldin Abdu Ali Abusham

Abstract:
Fidelity and comprehensibility are the common measures used in the evaluation of rules extracted from neural networks. However, these two measures are found to be inverse relations of one another. Since the needs of comprehensibility or fidelity may vary depending on the user or application, this paper presented a significance based rule extraction algorithm that allows a user set parameter to scale between the desired degree of fidelity and comprehensibility of the rules extracted. A detailed explanation and example application of this algorithm is presented as well as experimental results on several neural network ensembles.
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How to cite this article:

Kalaiarasi Sonai Muthu Anbananthen, Fabian Chan Huan Pheng, Subhacini Subramaniam, Shohel Sayeed and Eimad Eldin Abdu Ali Abusham, 2012. A Rule Extraction Algorithm That Scales Between Fidelity and Comprehensibility. Asian Journal of Scientific Research, 5: 121-132.

DOI: 10.3923/ajsr.2012.121.132

URL: https://scialert.net/abstract/?doi=ajsr.2012.121.132

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