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Relative performance of the statistical learning network: An application of the price-quality relationship in the automobile

Desmet, Pierre (2000), Relative performance of the statistical learning network: An application of the price-quality relationship in the automobile, European Journal of Economic and Social Systems, 14, 1, p. 69-79. 10.1051/ejess:2000109

Type
Article accepté pour publication ou publié
Date
2000-01
Journal name
European Journal of Economic and Social Systems
Volume
14
Number
1
Publisher
EDP sciences
Pages
69-79
Publication identifier
10.1051/ejess:2000109
Metadata
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Author(s)
Desmet, Pierre
Abstract (EN)
The design and topology of a neural network is still an important and difficult task. To solve the problems of topology posed by the introduction of connexionism, new approaches are proposed, and especially a combination of induction rules with a statistical estimation of the neuron coefficients for each layer. This research aims to compare an algorithm of this SLN approach with traditional methods (regression and classical BP neural networks) using the gradient method. Methods are put into application to determine the price-quality relationship of a complex product, the automobile, according to the hedonic price model. This application of the price-quality relationship to the English automobile market leads to the conclusion that the claimed superiority of this approach is unsubstantiated since, compared to the BP neural networks and even linear regression, the performance of the GMDH method is inferior.
Subjects / Keywords
Neural networks; Statistical learning networks; Hedonic prices; Connexionism
JEL
Z13 - Economic Sociology; Economic Anthropology; Social and Economic Stratification
L14 - Transactional Relationships; Contracts and Reputation; Networks
M11 - Production Management
M31 - Marketing

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