Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/26580
Title: Bankruptcy prediction using multiple classifier system with mutual information feature grouping
Authors: Chan, APF
Ng, WWY
Yeung, DS
Tsang, ECC
Firth, M
Keywords: Economic forecasting
Organisational aspects
Pattern classification
Issue Date: 2006
Publisher: IEEE
Source: IEEE International Conference on Systems, Man and Cybernetics, 2006 : SMC '06, 8-11 October 2006, Taipei, p. 845-850 How to cite?
Abstract: The prediction of bankruptcy helps an organization to choose its business partners and banks to approve or reject loan requests. So, it is essential to predict the bankruptcy of an organization. In this work, a multiple classifier system which combines decision from several different base classifiers trained using different samples with different input features is proposed for the bankruptcy prediction. The input features for each base classifier are selected using its mutual information with respect to the output. Experimental results of the proposed method using a real bankruptcy dataset from Compustat Global Dataset are promising.
URI: http://hdl.handle.net/10397/26580
ISBN: 1-4244-0099-6
1-4244-0100-3 (E-ISBN)
DOI: 10.1109/ICSMC.2006.384494
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

WEB OF SCIENCETM
Citations

1
Last Week
0
Last month
0
Citations as of Aug 14, 2017

Page view(s)

36
Last Week
5
Last month
Checked on Aug 13, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.