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Reseach Article

Effective Prediction of Bankruptcy based on the Qualitative factors using FID3 Algorithm

by A. Martin, S.Balaji, V. Prasanna Venkatesan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 43 - Number 21
Year of Publication: 2012
Authors: A. Martin, S.Balaji, V. Prasanna Venkatesan
10.5120/6389-8799

A. Martin, S.Balaji, V. Prasanna Venkatesan . Effective Prediction of Bankruptcy based on the Qualitative factors using FID3 Algorithm. International Journal of Computer Applications. 43, 21 ( April 2012), 28-32. DOI=10.5120/6389-8799

@article{ 10.5120/6389-8799,
author = { A. Martin, S.Balaji, V. Prasanna Venkatesan },
title = { Effective Prediction of Bankruptcy based on the Qualitative factors using FID3 Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 43 },
number = { 21 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 28-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume43/number21/6389-8799/ },
doi = { 10.5120/6389-8799 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:34:19.625948+05:30
%A A. Martin
%A S.Balaji
%A V. Prasanna Venkatesan
%T Effective Prediction of Bankruptcy based on the Qualitative factors using FID3 Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 43
%N 21
%P 28-32
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Bankruptcy is one of the most important issues in Financial Management and investment. Numerous studies on Bankruptcy Prediction have been carried out considering Quantitative factors and they applied different techniques on it to predict Bankruptcy, while only fewer studies have proposed and considered Qualitative factors for prediction of Bankruptcy and even then failure of bankruptcy persists. This paper proposes a model involving Experts decision and Fuzzy ID based algorithm to predict Bankruptcy in an effective manner. In Fuzzy ID3 the evaluation of Entropy and Information Gain helps to rank the qualitative parameters and the membership function evaluation is used to generate prediction rules in qualitative Bankruptcy prediction. The result of the prediction provides the most important factors that have more impact on the Bankruptcy. Since, the prediction is carried out with the experts listed factors the prediction accuracy is raised along with better performance

References
  1. The discovery of experts' decision rules from qualitative bankruptcy data using genetic algorithms. Myoung-Jong Kim*, Ingoo HanB. 2003.
  2. "Applying Fuzzy ID3 Decision Tree for Software Effort Estimation ", Ali Idri and Sanaa Elyassami, International Journal of Computer Science Issues, Vol. 8, Issue 4, No 1, July 2011.
  3. W. H. Beaver, M. F. McNichols and J. W. Rhie,"Have financial Statements Become Less Informative? Evidence from the Ability of Financial Ratios to Predict Bankruptcy", Review of Accounting Studies, pp. 93 – 122, 2005.
  4. Nasir, M. L. , John, RA. , Bennett, S. C. , Russell, D. M. , Patel, A. "Predicting Corporate Bankruptcy using Artificial Neural Networks'' Journal of Applied Accounting Research, Spring. 2000
  5. "The prediction of bankruptcy using fuzzy classifiers" R. Nogueira, S. M. Vieira and J. M. C. Sousa, ieee 2005.
  6. Jan Vandeweyer, "Electre Tri as a method for bankruptcy prediction", Department Handels wetenschappen en Bedrijfskunde Strategisch KMO- en Retail management International Business, Academiejaar 2004-2005.
  7. LUAN Fugui, LI Jia," The Construction of Assessment System: Bankruptcy Reorganization Value of corporate", ORIENT ACADEMIC FORUM, 2009.
  8. "Using partial least squares and support vector machines for bankruptcy prediction", Zijiang Yang a, Wenjie You b, c, Guoli Ji Elsevier 2011.
  9. P. R. Kumar and V. , Ravi, "Bankruptcy Prediction in Banks and Firms via Statistical and Intelligent Techniques–A Review, "European Journal of perational Research, 180(1), 2007.
  10. "M. Umano, H. Okamoto, I. Hatono, H. Tamura, F. Kawachi, S. Umedzu, J. Kinoshita. "Fuzzy Decision Trees by Fuzzy ID3 algorithm and Its Application to Diagnosis Systems". IEEE Conference on Fuzzy Systems, vol. 3, June, 1994.
  11. Olaru C. , Wehenkel L. " A complete fuzzy decision tree technique. Fuzzy set and systems", pp. 221-254, 2003.
  12. Caouette, J. B. , Altman, E. I. , & Narayanan, P. "Managing credit risk: The next great financial challenge. New York: Wiley & Sons Inc", 1998.
  13. J. R. Quinlan, "Introduction of Decision Trees", Machine Learning 1 pp81-106, 1986.
Index Terms

Computer Science
Information Sciences

Keywords

Bankruptcy Prediction Qualitative Factors Fuzzy Id Information Gain.