Implementation of Parameter Space Search for Meta Learning in a Data-Mining Multi-agent System

Authors:
Ondrej Kazik;Klára Peskova;Martin Pilát;Roman Neruda
Affiliations:
-;-;-;-
Venue:
ICMLA '11 Proceedings of the 2011 10th International Conference on Machine Learning and Applications and Workshops - Volume 02
Year:
2011

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A Novel Meta Learning System and Its Application to Optimization of Computing Agents' Results

WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02

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Abstract

In this paper an implementation of a multi-agent system designed for solving complex data mining tasks is presented. The system is based on ontologically sound AGR (agents, groups, roles) model and encapsulates Weka library methods in JADE agents. 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.