RT Book, Section
T1 Credit rating using fuzzy algorithms
A1 Hernández Morales, Moisés
A1 Rodríguez González, Juan Tinguaro
A1 Montero De Juan, Francisco Javier
AB 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 presentingthe problem and the methodology used in order to lay the foundation for further improvement work.
PB CAEPIA'15
SN 978-84-608-4099-2
YR 2015
FD 2015
LK https://hdl.handle.net/20.500.14352/35796
UL https://hdl.handle.net/20.500.14352/35796
LA eng
NO V Simposio de Lógica Difusa y Soft Computing.
DS Docta Complutense
RD 5 abr 2025