Title Modelo no lineal basado en redes neuronales de unidades producto para clasificación. Una aplicación a la determinación del riesgo en tarjetas de crédito
Authors MARTÍNEZ ESTUDILLO, FRANCISCO JOSÉ, Hervás-Martínez C., TORRES JIMÉNEZ, MERCEDES, MARTÍNEZ ESTUDILLO, ALFONSO CARLOS, MARTÍNEZ ESTUDILLO, FRANCISCO JOSÉ, TORRES JIMÉNEZ, MERCEDES, MARTÍNEZ ESTUDILLO, ALFONSO CARLOS
External publication No
Means Rev. Metodos Cuantitativos Econ. Empresa
Scope Article
Nature Científica
SJR Quartile 3
SJR Impact 0.11400
Area International
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-38749146482&partnerID=40&md5=bfc7e9d8a1a10f66c7259d07e0b5cea5
Publication date 01/01/2007
Scopus Id 2-s2.0-38749146482
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).
Keywords Classification; Evolutionary neural networks; Product unit neural networks
Universidad Loyola members