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Comparison of the Predictability of a Neural Network with Retropropagation with Those using Linear Regression, Logistic and A.I.D. Methods for Direct Marketing Scoring

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Date
1998
Dewey
Marketing direct
Sujet
empirical results; direct marketing; scoring; algorithm; bio mimetic; neural networks
JEL code
G.G2.G24; M.M3.M31; C.C4.C45
Book title
Bio-Mimetic Approaches in Management Science
Author
Aurifeille, Jacques-Marie; Deissenberg, Christophe
Publisher
Springer
Publisher city
Berlin Heidelberg
Year
1998
ISBN
978-0792349938
URI
https://basepub.dauphine.fr/handle/123456789/19617
Collections
  • DRM : Publications
Metadata
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Author
Desmet, Pierre
1032 Dauphine Recherches en Management [DRM]
Type
Chapitre d'ouvrage
Item number of pages
61-75
Abstract (EN)
In comparison with other usual statistical methods (MCO, logistic regression, discriminant analysis, AID), advantages of neural network with backpropagation are numerous and well known (non linear effects, distribution flee variables, low sensibility to outliers or missing variables). However, implementation and efficiency have not yet received a strong interest. The paper reviews comparative analyses and presents results obtained for prediction of a behaviour in Fund raising.

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