A rule extraction algorithm that scales between fidelity and comprehensibility

Anbananthen, K.S.M. and Pheng, F.C.H. and Subramaniam, S. and Sayeed, S. and Abusham, E.E.A.A. (2012) A rule extraction algorithm that scales between fidelity and comprehensibility. Asian Journal of Scientific Research, 5 (3). pp. 121-132. ISSN 19921454

[img] PDF
11.pdf
Restricted to Repository staff only

Download (0B)

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.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Information Science and Technology (FIST)
Centre for Diploma Programmes (CDP)
Depositing User: Users 1102 not found.
Date Deposited: 04 Jan 2013 01:55
Last Modified: 04 Jan 2013 01:55
URI: http://shdl.mmu.edu.my/id/eprint/3778

Actions (login required)

View Item View Item