Corporate bankruptcy prediction through data mining.
This study examines the use of data mining techniques namely decision tree, neural networks and logistic regression to predict the likelihood of a corporate failure through inputs on companies' financial variables.
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2008
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Online Access: | http://hdl.handle.net/10356/10002 |
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sg-ntu-dr.10356-100022023-05-19T06:16:16Z Corporate bankruptcy prediction through data mining. Soh, Amos Sheng En. Lin, Isaac Jia Xin. Ng, Alwyn Liang You. Koh, Hian Chye Nanyang Business School Wu, Yuan DRNTU::Business::Law::Bankruptcy This study examines the use of data mining techniques namely decision tree, neural networks and logistic regression to predict the likelihood of a corporate failure through inputs on companies' financial variables. 2008-09-24T07:38:42Z 2008-09-24T07:38:42Z 2006 2006 Final Year Project (FYP) http://hdl.handle.net/10356/10002 Nanyang Technological University application/pdf |
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DRNTU::Business::Law::Bankruptcy Soh, Amos Sheng En. Lin, Isaac Jia Xin. Ng, Alwyn Liang You. Corporate bankruptcy prediction through data mining. |
description |
This study examines the use of data mining techniques namely decision tree, neural networks and logistic regression to predict the likelihood of a corporate failure through inputs on companies' financial variables. |
author2 |
Koh, Hian Chye |
author_facet |
Koh, Hian Chye Soh, Amos Sheng En. Lin, Isaac Jia Xin. Ng, Alwyn Liang You. |
format |
Final Year Project |
author |
Soh, Amos Sheng En. Lin, Isaac Jia Xin. Ng, Alwyn Liang You. |
author_sort |
Soh, Amos Sheng En. |
title |
Corporate bankruptcy prediction through data mining. |
title_short |
Corporate bankruptcy prediction through data mining. |
title_full |
Corporate bankruptcy prediction through data mining. |
title_fullStr |
Corporate bankruptcy prediction through data mining. |
title_full_unstemmed |
Corporate bankruptcy prediction through data mining. |
title_sort |
corporate bankruptcy prediction through data mining. |
publishDate |
2008 |
url |
http://hdl.handle.net/10356/10002 |
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1770564316692480000 |