EconPapers    
Economics at your fingertips  
 

DESIGNING AN IF–THEN RULES‐BASED ENSEMBLE OF HETEROGENEOUS BANKRUPTCY CLASSIFIERS: A GENETIC ALGORITHM APPROACH

Sergio Davalos, Fei Leng, Ehsan Feroz and Zhiyan Cao

Intelligent Systems in Accounting, Finance and Management, 2014, vol. 21, issue 3, 129-153

Abstract: This paper proposes a framework for an ensemble bankruptcy classifier that uses if–then rules to combine the outputs from a heterogeneous set of classifiers. A genetic algorithm (GA) induces the rules using an asymmetric, cost‐sensitive fitness function that includes accuracy and misclassification costs. The GA‐based ensemble classifier outperforms individual classifiers and ensemble classifiers generated by other methods. The results of the classifier are in the form of if–then rules. We apply the approach to a balanced dataset and an imbalanced dataset. Both are composed of firms subject to financial distress and cited in the US Securities and Exchange Commission's Accounting and Auditing Enforcement Releases. Copyright © 2014 John Wiley & Sons, Ltd.

Date: 2014
References: Add references at CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
https://doi.org/10.1002/isaf.1354

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:isacfm:v:21:y:2014:i:3:p:129-153

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=1099-1174
subscrip@blackwellpub.com

Access Statistics for this article

More articles in Intelligent Systems in Accounting, Finance and Management from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery (contentdelivery@wiley.com).

 
Page updated 2024-12-29
Handle: RePEc:wly:isacfm:v:21:y:2014:i:3:p:129-153