Analysis of Methods for Generating Classification Rules Applicable to Credit Risk
Credit risk is defined as the probability of loss due to non-compliance by the borrower with the required payments in relation to any type of debt. When financial institutions select their customers correctly, they can reduce their credit risk. To achieve this, they use various classification metho...
Guardado en:
| Autores principales: | Jimbo Santana, Patricia, Villa Monte, Augusto, Rucci, Enzo, Lanzarini, Laura Cristina, Fernández Bariviera, Aurelio |
|---|---|
| Formato: | Articulo |
| Lenguaje: | Español |
| Publicado: |
2017
|
| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/59978 http://journal.info.unlp.edu.ar/wp-content/uploads/2017/05/JCST-44-Paper-3.pdf |
| Aporte de: |
Ejemplares similares
-
An exploratory analysis of methods for extracting credit risk rules
por: Jimbo Santana, Patricia, et al.
Publicado: (2016) -
Variations of Particle Swarm Optimization for Obtaining Classification Rules Applied to Credit Risk in Financial Institutions of Ecuador
por: Jimbo Santana, Patricia, et al.
Publicado: (2019) -
Extraction of Knowledge with Population-Based Metaheuristics Fuzzy Rules Applied to Credit Risk
por: Jimbo Santana, Patricia Rosalía, et al.
Publicado: (2018) -
Simplifying credit scoring rules using LVQ + PSO
por: Lanzarini, Laura Cristina, et al.
Publicado: (2017) -
User-Oriented Summaries Using a PSO Based Scoring Optimization Method
por: Villa Monte, Augusto, et al.
Publicado: (2019)