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Published in:
2010 | OriginalPaper | Chapter
Cluster Integration for the Cluster-Based Instance Selection
Authors : Ireneusz Czarnowski, Piotr Jędrzejowicz
Published in: Computational Collective Intelligence. Technologies and Applications
Publisher: Springer Berlin Heidelberg
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The problem addressed in this paper concerns data reduction through instance selection. The paper proposes an approach based on instance selection from clusters. The process of selection and learning is executed by a team of agents. The approach aims at obtaining a compact representation of the dataset, where the upper bound on the size of data is determined by the user. The basic assumption is that the instance selection is carried out after the training data have been grouped into clusters. The cluster initialization and integration strategies are proposed and experimentally evaluated.