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The goal of our data-mining multi-agent system is to facilitate data-mining experiments without the necessary knowledge of the most suitable machine learning method and its parameters to the data. In order to replace the experts knowledge, the meta-learning subsystems are proposed including the parameter-space search and method recommendation based on previous experiments. In this paper we show the results of the parameter-space search with several search algorithms - tabulation, random search, simmulated annealing, and genetic algorithm.
Machine Learning and Applications (ICMLA), 2012 11th International Conference on (Volume:2 )
Date of Conference: 12-15 Dec. 2012