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

机译:关于使用神经网络进行知识发现的说明及其在信用卡筛选中的应用

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摘要

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. (C) 2007 Elsevier B.V. All rights reserved.
机译:我们解决了使用神经网络进行知识发现中的一个重要问题,该问题已在Sexton等最近发表的文章“针对现实世界中的分类问题使用神经网络同时优化算法进行知识发现”中省略了。 [R.S. Sexton,S.McMurtrey,D.J. Cleavenger,关于神经网络同步优化算法在现实世界中的知识发现的分类问题,欧洲运筹学杂志168(2006)1009-1018]。这个重要的问题是从受过训练的神经网络生成可理解的规则集。在本说明中,我们介绍了我们的神经网络规则提取算法,该算法对于发现嵌入在神经网络中的知识非常有效。该算法特别适用于需要可理解性和准确性的应用。对于Sexton等使用的相同数据集。我们的算法产生的简明易懂的准确规则集,因此有助于验证关于神经网络可以替代其他用于知识发现的数据挖掘工具的可行选择的说法。 (C)2007 Elsevier B.V.保留所有权利。

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