Meta Learning in Multi-agent Systems for Data Mining

Authors:
Ondřej Kazík;Klára Pešková;Martin Pilát;Roman Neruda
Affiliations:
Department of Theoretical Computer Science, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic;Department of Theoretical Computer Science, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic;Department of Theoretical Computer Science, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic;Institute of Computer Science, Academy of Sciences of The Czech Republic, Prague, Czech Republic
Venue:
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Year:
2011

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Abstract

In this paper we present the Pikater multi-agent system designed for solving complex data mining tasks. We emphasize the unique intelligent features of the system--its ability to search the parameter space of the data mining methods to find the optimal configuration, and meta learning--finding the best possible method for the given data based on the ontological compatibility of datasets.