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Hybrid Multi-Agent System for Metalearning in Data Mining
- 1.0436190 - ÚI 2015 DE eng A - Abstract
Pešková, K. - Šmíd, J. - Pilát, M. - Kazík, O. - Neruda, Roman
Hybrid Multi-Agent System for Metalearning in Data Mining.
Proceedings of the International Workshop on Meta-learning and Algorithm Selection. Aachen University: CEUR, 2014. s. 53-54. ISSN 1613-0073.
[MetaSel 2014. Meta-learning and Algorithm Selection. 19.08.2014, Prague]
R&D Projects: GA MŠMT(CZ) LD13002
Grant - others:GA UK(CZ) 610214
Institutional support: RVO:67985807
Keywords : data mining * multi-agent systems * artificial intelligence
Subject RIV: IN - Informatics, Computer Science
http://ceur-ws.org/Vol-1201/paper-13.pdf
In this paper, a multi-agent system for metalearning in the data mining domain is presented. The system provides a user with intelligent features, such as recommendation of suitable data mining techniques for a new dataset, parameter tuning of such techniques, and building up a metaknowledge base. The architecture of the system, together with different user scenarios, and the way they are handled by the system, are described.....
Permanent Link: http://hdl.handle.net/11104/0239976
Number of the records: 1