PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Bias-Variance Analysis of ECOC and Bagging Using Neural Nets
Cemre Zor, Terry Windeatt and Berrin Yanikoglu
In: ECML PKDD - SUEMA workshop, Barcelona, Spain(2010).


One of the methods used to evaluate the performance of ensemble classiers is bias and variance analysis. In this paper, we analyse bagging and ECOC ensembles using bias-variance domain of James [1] and make a comparison with single classiers, when using Neural Networks (NNs) as base classiers. As the performance of the ensembles depends on the individual base classiers, it is important to understand the overall trends when the parameters of the base classiers, nodes and epochs for NNs, are changed. We show experimentally on 5 articial and 4 UCI MLR datasets that there are some clear trends in the analysis that should be taken into consideration while designing NN classier systems.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:8104
Deposited By:Cemre Zor
Deposited On:18 April 2011