| Título: | Credit rating using fuzzy algorithms |
| Autores: | Hernández Morales, Moisés ; Rodríguez, Juan Tinguaro ; Montero, Javier |
| Tipo de documento: | texto impreso |
| Editorial: | CAEPIA'15, 2015 |
| Dimensiones: | application/pdf |
| Nota general: |
info:eu-repo/semantics/restrictedAccess info:eu-repo/semantics/openAccess |
| Idiomas: | |
| Palabras clave: | Estado = Publicado , Materia = Ciencias: Informática: Inteligencia artificial , Tipo = Sección de libro |
| Resumen: |
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. |
| En línea: | https://eprints.ucm.es/34890/1/Montero263.pdf |
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