.png){kind=icon}
返回
Business failure prediction using rough sets
.png){kind=icon}
PRE
AI
DOI：10.1016/S0377-2217(98)00255-0.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A large number of methods like discriminant analysis, legit analysis, recursive partitioning algorithm, etc., have been used in the past for the prediction of business failure. Although some of these methods lead to models with a satisfactory ability to discriminate between healthy and bankrupt firms, they suffer from some limitations, often due to the unrealistic assumption of statistical hypotheses or due to a confusing language of communication with the decision makers. This is why we have undertaken a research aiming at weakening these limitations. In this paper, the rough set approach is used to provide a set of rules able to discriminate between healthy and failing firms in order to predict business failure. Financial characteristics of a large sample of 80 creek firms are used to derive a set of rules and to evaluate its prediction ability. The results are very encouraging, compared with those of discriminant and legit analyses, and prove the usefulness of the proposed method for business failure prediction. The rough set approach discovers relevant subsets of financial characteristics and represents in these terms all important relationships between the image of a firm and its risk of failure. The method analyses only facts hidden in the input data and communicates with the decision maker in the natural language of rules derived from his/her experience. (C) 1999 Elsevier Science B.V. All rights reserved.
Keyword:
business failure prediction
rough set theory
discriminant analysis
decision rules
classification
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6
论文数:
2.2W
被引数:
6.4W
机构
暂无机构信息
引用论文
.png){kind=icon}
A survey of business failures with an emphasis on prediction methods and industrial applications
PREAI
分享收藏分享收藏Modulation of the Cold-Activated Channel TRPM8 by Lysophospholipids and Polyunsaturated Fatty Acids
OAAI
OAAI分享收藏
查看更多内容