Non-linear model for classification based on product-unit neural networks. An application to determine credit card risk

Authors

  • F. J. Martínez-Estudillo Departamento de Gestión y Métodos Cuantitativos ETEA Córdoba
  • C. Hervás-Martínez Departamento de Informática y Análisis Numérico Universidad de Córdoba
  • M. Torres-Jiménez Departamento de Gestión y Métodos Cuantitativos ETEA Córdoba
  • A. C. Martínez-Estudillo Departamento de Gestión y Métodos Cuantitativos ETEA Córdoba

DOI:

https://doi.org/10.46661/revmetodoscuanteconempresa.2064

Keywords:

Clasificación, redes neuronales de unidades producto, redes neuronales evolutivas, classification, product unit neural networks, evolutionary neural networks

Abstract

The main aim of this work is to show a neural network model called product unit neural network (PUNN), which is a non-linear model to solve classification problems. We propose an evolutionary algorithm to simultaneously design the topology of the network and estimate its corresponding weights. The methodology proposed combines a non-linear model and an evolutionary algorithm and it is applied to solve a real economic problem that occurs in the financial management. To evaluate the performance of the classification models obtained, we compare our approach with several classic statistical techniques such us logistic regression and linear discriminat analysis, and with the multilayer perceptron neural network model based on sigmoidal units trained by means of Back-Propagation algorithm (MLPBP).

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Published

2016-11-04

How to Cite

Martínez-Estudillo, F. J., Hervás-Martínez, C., Torres-Jiménez, M., & Martínez-Estudillo, A. C. (2016). Non-linear model for classification based on product-unit neural networks. An application to determine credit card risk. Journal of Quantitative Methods for Economics and Business Administration, 3, Páginas 40 a 62. https://doi.org/10.46661/revmetodoscuanteconempresa.2064

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