Using Genetic Programming as a Feature Selector and Classifier to Implement Bankruptcy Prediction Models.
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| Title: | Using Genetic Programming as a Feature Selector and Classifier to Implement Bankruptcy Prediction Models. |
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| Authors: | Beade, Ángel1 a.beade@udc.es, Santos, José2 jose.santos@udc.es, Rodríguez, Manuel1 manuel.rodriguez.lopez@udc.es |
| Source: | Computer Science & Information Systems. Jan2026, Vol. 23 Issue 1, p513-534. 22p. |
| Subjects: | Genetic programming, Feature selection, Classification algorithms, United States economy, Business enterprises, Economic indicators, Counterparty risk |
| Abstract: | Genetic Programming (GP) was used as a feature selector and classifier to implement bankruptcy prediction models for medium-sized companies. Two sets of input variables were used for the prediction models: one using a large number of exclusively financial variables and the other incorporating variables from the economic environment, which allows analyzing the capability of the latter to improve performance. Two strategies were defined for GP as a feature selector, based on the statistical relevance of the selected features in the GP process, with a novel proposal based on a progressive reduction of the set of selected variables and with the aim of minimizing the risk of eliminating relevant features. An analysis is performed of the improvement obtained with feature selection with both GP-based methods in comparison with the use of complete sets of variables and using GP as a classifier. With the selected variables, we also compared GP as a classifier with respect to other standard classifiers, using automatic parameter adjustment with AutoWeka for these classifiers. The best results are obtained with the synergy of using GP as a feature selector and as a classifier, with the advantage of the direct interpretability that GP provides in the application. [ABSTRACT FROM AUTHOR] |
| Copyright of Computer Science & Information Systems is the property of ComSIS Consortium and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Items | – Name: Title Label: Title Group: Ti Data: Using Genetic Programming as a Feature Selector and Classifier to Implement Bankruptcy Prediction Models. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Beade%2C+Ángel%22">Beade, Ángel</searchLink><relatesTo>1</relatesTo><i> a.beade@udc.es</i><br /><searchLink fieldCode="AR" term="%22Santos%2C+José%22">Santos, José</searchLink><relatesTo>2</relatesTo><i> jose.santos@udc.es</i><br /><searchLink fieldCode="AR" term="%22Rodríguez%2C+Manuel%22">Rodríguez, Manuel</searchLink><relatesTo>1</relatesTo><i> manuel.rodriguez.lopez@udc.es</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Computer+Science+%26+Information+Systems%22">Computer Science & Information Systems</searchLink>. Jan2026, Vol. 23 Issue 1, p513-534. 22p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Genetic+programming%22">Genetic programming</searchLink><br /><searchLink fieldCode="DE" term="%22Feature+selection%22">Feature selection</searchLink><br /><searchLink fieldCode="DE" term="%22Classification+algorithms%22">Classification algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22United+States+economy%22">United States economy</searchLink><br /><searchLink fieldCode="DE" term="%22Business+enterprises%22">Business enterprises</searchLink><br /><searchLink fieldCode="DE" term="%22Economic+indicators%22">Economic indicators</searchLink><br /><searchLink fieldCode="DE" term="%22Counterparty+risk%22">Counterparty risk</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Genetic Programming (GP) was used as a feature selector and classifier to implement bankruptcy prediction models for medium-sized companies. Two sets of input variables were used for the prediction models: one using a large number of exclusively financial variables and the other incorporating variables from the economic environment, which allows analyzing the capability of the latter to improve performance. Two strategies were defined for GP as a feature selector, based on the statistical relevance of the selected features in the GP process, with a novel proposal based on a progressive reduction of the set of selected variables and with the aim of minimizing the risk of eliminating relevant features. An analysis is performed of the improvement obtained with feature selection with both GP-based methods in comparison with the use of complete sets of variables and using GP as a classifier. With the selected variables, we also compared GP as a classifier with respect to other standard classifiers, using automatic parameter adjustment with AutoWeka for these classifiers. The best results are obtained with the synergy of using GP as a feature selector and as a classifier, with the advantage of the direct interpretability that GP provides in the application. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Computer Science & Information Systems is the property of ComSIS Consortium and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.2298/CSIS250226013B Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: 513 Subjects: – SubjectFull: Genetic programming Type: general – SubjectFull: Feature selection Type: general – SubjectFull: Classification algorithms Type: general – SubjectFull: United States economy Type: general – SubjectFull: Business enterprises Type: general – SubjectFull: Economic indicators Type: general – SubjectFull: Counterparty risk Type: general Titles: – TitleFull: Using Genetic Programming as a Feature Selector and Classifier to Implement Bankruptcy Prediction Models. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Beade, Ángel – PersonEntity: Name: NameFull: Santos, José – PersonEntity: Name: NameFull: Rodríguez, Manuel IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: Jan2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 18200214 Numbering: – Type: volume Value: 23 – Type: issue Value: 1 Titles: – TitleFull: Computer Science & Information Systems Type: main |
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