Selecting Neural Networks for Making a Committee Decision

Authors:
Antanas Verikas;Arunas Lipnickas;Kerstin Malmqvist
Affiliations:
-;-;-
Venue:
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Year:
2002

Citing 3
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Abstract

To improve recognition results, decisions of multiple neural networks can be aggregated into a committee decision. In contrast to the ordinary approach of utilizing all neural networks available to make a committee decision, we propose creating adaptive committees, which are specific for each input data point. A prediction network is used to identify classification neural networks to be fused for making a committee decision about a given input data point. The jth output value of the prediction network expresses the expectation level that the jth classification neural network will make a correct decision about the class label of a given input data point. The effectiveness of the approach is demonstrated on two artificial and three real data sets.