Multi Criteria Decision Methods for Coordinating Case-Based Agents

There is an increasing interest on ensemble learning since it reduces the bias-variance problem of several classifiers. In this paper we approach an ensemble learning method in a multi-agent environment. Particularly, we use genetic algorithms to learnt weights in a boosting scenario where several case-based reasoning agents cooperate. In order to deal with the genetic algorithm results, we propose several multicriteria decision making methods. We experimentally test the methods proposed in a breast cancer diagnosis database.

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