Year
2000
Abstract
The design and topology of a Neural network is still an important and difficult task. To solve this problem, new approaches are proposed, and specially a combination of induction rules with a statistical estimation of the coefficients. This research aims to compare an algorithm of this SLN approach with traditional methods (Regression and classical BP neural net). An application on the price-quality relationship for the English automobile market drives to the conclusion that the claimed superiority of the approach is not validated as the performance of the GMDH method is inferior, compared to BP Neural net and even linear regression.
DESMET, P. (2000). Relative Performance of the Statistical Learning Network: An Application of the Price-quality Relationship in the Automobile. Dans: Proceedings ANZMAC 2000 – Visionary Marketing for the 21st Century: Facing the Challenge. Griffith University, pp. 100.