Bagging of Artificial Neural Networks for Bankruptcy Prediction

Author

Shi, Lei ; Xi, Lei ; Ma, Xinming ; Hu, Xiaohong

Author_Institution

Coll. of Inf. & Manage. Sci., Henan Agric. Univ., Zhengzhou, China

fYear

2009

fDate

17-20 April 2009

Firstpage

154

Lastpage

156

Abstract

Bankruptcy prediction has been one of the most challenging tasks and a major research topic in accounting and finance. In this paper, bagging ensemble, a popular technique in the machine learning community, is proposed to improve the prediction performance of artificial neural networks in bankruptcy prediction analysis. The experiments conducted on the public dataset show that the proposed approach achieves obvious improvement of performance.

Keywords

accounts data processing; learning (artificial intelligence); neural nets; pattern classification; regression analysis; sampling methods; accounting domain; artificial neural network; bagging ensemble technique; bankruptcy prediction analysis; bootstrap sampling technique; data classification; finance domain; machine learning; regression analysis; Artificial neural networks; Bagging; Educational institutions; Finance; Financial management; Information management; Machine learning; Performance analysis; Sampling methods; Voting; Bagging ensemble; artificial neural network; bankruptcy prediction;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Financial Engineering, 2009. ICIFE 2009. International Conference on

Conference_Location

Singapore

Print_ISBN

978-0-7695-3606-4

Type

conf

DOI

10.1109/ICIFE.2009.17

Filename

5189988