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Design and comparison of different evolution strategies for feature selection and consolidation in music classification

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3 Author(s)
I. Vatolkin ; Department of Computer Science, Technical University of Dortmund, Germany ; W. Theimer ; G. Rudolph

Music classification is a complex problem which has gained high relevance for organizing large music collections. Different parameters concerning feature extraction, selection, processing and classification have a strong impact on the categorization quality. Since it is very difficult to design a deterministic approach which provides the efficient parameter tuning, we haven chosen a heuristic approach. In our work we apply and compare different evolution strategies for the optimization of feature selection and consolidation using three pre-defined personal user categories. Concepts of local search operators with domain-specific knowledge and self-adaptation are examined. Several suggestions based on an empirical study are discussed and ideas for future work are given.

Published in:

2009 IEEE Congress on Evolutionary Computation

Date of Conference:

18-21 May 2009