article

Short communication: Data mining method for listed companies' financial distress prediction

Authors:

Jie Sun,

Hui LiAuthors Info & Claims

Knowledge-Based Systems, Volume 21, Issue 1

Pages 1 - 5

https://doi.org/10.1016/j.knosys.2006.11.003

Published: 01 February 2008 Publication History

Abstract

Data mining technique is capable of mining valuable knowledge from large and changeable database. This paper puts forward a data mining method combining attribute-oriented induction, information gain, and decision tree, which is suitable for preprocessing financial data and constructing decision tree model for financial distress prediction. On the base of financial ratios attributes and one class attribute, adopting entropy-based discretization method, a data mining model for listed companies' financial distress prediction is designed. The empirical experiment with 35 financial ratios and 135 pairs of listed companies as initial samples got satisfying result, which testifies the feasibility and validity of the proposed data mining method for listed companies' financial distress prediction.

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Guillén-Pujadas MVizuete-Luciano EAlaminos DCarmen Gracia-Ramos M(2024)Understanding evolving user choices: a neural network analysis of TAXI and ride-hailing services in BarcelonaSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-09239-w28:5(4649-4665)Online publication date: 1-Mar-2024
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Mao ZWu C(2023)Dynamic Prediction of Corporate Financial Crisis Based on N-Step Ahead Kalman FilterProceedings of the 2023 7th International Conference on Cloud and Big Data Computing10.1145/3616131.3616134(21-27)Online publication date: 17-Aug-2023
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Qian HWang BYuan MGao SSong Y(2022)Financial distress prediction using a corrected feature selection measure and gradient boosted decision treeExpert Systems with Applications: An International Journal10.1016/j.eswa.2021.116202190:COnline publication date: 9-Apr-2022
https://dl.acm.org/doi/10.1016/j.eswa.2021.116202
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Short communication: Data mining method for listed companies' financial distress prediction

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Published In

Knowledge-Based Systems Volume 21, Issue 1

February, 2008

88 pages

ISSN:0950-7051

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 February 2008

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Short Communication: American Student Loans: Repayment and Valuation

Data Mining for Municipal Financial Distress Prediction

The effect of feature selection on financial distress prediction

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