Eur. Phys. J. AP
Volume 12, Number 1, October 2000
|Page(s)||61 - 74|
|Published online||15 October 2000|
A binary classification methodology applicable to defects detection. Boosting algorithms
Laboratoire de Traitement du Signal et de Modélisation des
Machines, Institut d'Études Supérieures de la Guyane, avenue d'Estrée, BP 792,
97337 Cayenne Cedex, France
Corresponding author: firstname.lastname@example.org
Accepted: 31 July 2000
Published online: 15 October 2000
This article presents a binary classification method which is used in defects detection. It's presented as recursives “boosting” algorithms which allow us to obtain a precise discriminating function by combination of hypothesis and rules with moderate accuracy. This approach permits the study of random phenomena governed by nonparametric laws and a direct decision for the observations classification and the determination of frontiers in an observation space. The various analyses which will be developed are illustrated by simulations making it possible to evaluate the possibilities of the method.
PACS: 02.50.Rj – Nonparametric inference / 07.05.Tp – Computer modeling and simulation / 42.30.Sy – Pattern recognition
© EDP Sciences, 2000
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.