Analysis of the Performance of AdaBoost.M2 for the Simulated Digit-Recognition-Example

Authors:
Günther Eibl;Karl Peter Pfeiffer
Affiliations:
-;-
Venue:
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Year:
2001

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Abstract

In simulation studies boosting algorithms seem to be susceptible to noise. This article applies Ada.Boost.M2 used with decision stumps to the digit recognition example, a simulated data set with attribute noise. Although the final model is both simple and complex enough, boosting fails to reach the Bayes error. A detailed analysis shows some characteristics of the boosting trials which influence the lack of fit.