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Hernández Morales, Moisés and Rodríguez, Juan Tinguaro and Montero, Javier (2015) Credit rating using fuzzy algorithms. In Actas de la XVI Conferencia de la Asociación Española para la Inteligencia Artificial. CAEPIA'15, Albacete, pp. 539-548. ISBN 978-84-608-4099-2
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Official URL: http://simd.albacete.org/actascaepia15/papers/00539.pdf
Abstract
This article is devoted to the replication of the nternal methodologies of credit rating agencies for rating lassification using fuzzy algorithms. To achieve this goal, the usage of different types of fuzzy algorithms (evolutionary and non-evolutionary fuzzy rule learning for classification) is explored, departing from historical data on credit ratings (ratings) and fourteen financial ratios used as explanatory variables. This study is a preliminary work focused on presenting
the problem and the methodology used in order to lay the foundation for further improvement work.
| Item Type: | Book Section |
|---|---|
| Additional Information: | V Simposio de Lógica Difusa y Soft Computing. |
| Uncontrolled Keywords: | Credit rating; Corporate rating; Fuzzy algorithms; Fuzzy classification |
| Subjects: | Sciences > Computer science > Artificial intelligence |
| ID Code: | 34890 |
| Deposited On: | 18 Dec 2015 09:31 |
| Last Modified: | 27 Jul 2017 06:28 |
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