A note on knowledge discovery using neural networks and its application to credit card screening


Setiono, R., Baesens, B. and Mues, C. (2009) A note on knowledge discovery using neural networks and its application to credit card screening. European Journal of Operational Research, 192, (1), 326-332. (doi:10.1016/j.ejor.2007.09.022).

Download

Full text not available from this repository.

Description/Abstract

We address an important issue in knowledge discovery using neural networks that has been left out in a recent article “Knowledge discovery using a neural network simultaneous optimization algorithm on a real world classification problem” by Sexton et al. [R.S. Sexton, S. McMurtrey, D.J. Cleavenger, Knowledge discovery using a neural network simultaneous optimization algorithm on a real world classification problem, European Journal of Operational Research 168 (2006) 1009–1018]. This important issue is the generation of comprehensible rule sets from trained neural networks. In this note, we present our neural network rule extraction algorithm that is very effective in discovering knowledge embedded in a neural network. This algorithm is particularly appropriate in applications where comprehensibility as well as accuracy are required. For the same data sets used by Sexton et al. our algorithm produces accurate rule sets that are concise and comprehensible, and hence helps validate the claim that neural networks could be viable alternatives to other data mining tools for knowledge discovery.

Item Type: Article
ISSNs: 0377-2217 (print)
Related URLs:
Keywords: knowledge discovery, neural networks, rule extraction, credit screening
Subjects: H Social Sciences > HG Finance
H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: University Structure - Pre August 2011 > School of Management
ePrint ID: 51612
Date Deposited: 06 Jun 2008
Last Modified: 27 Mar 2014 18:34
URI: http://eprints.soton.ac.uk/id/eprint/51612

Actions (login required)

View Item View Item