Combining D2K and JGAP for Efficient Feature Weighting for Classification Tasks in Music Information Retrieval
نویسندگان
چکیده
Music classification continues to be an important component of music information retrieval research. An underutilized tool for improving the performance of classifiers is feature weighting. A major reason for its unpopularity, despite its benefits, is the potentially infinite calculation time it requires to achieve optimal results. Genetic algorithms offer potentially sub-optimal but reasonable solutions at much reduced calculation time, yet they are still quite costly. We investigate the advantages of implementing genetic algorithms in a parallel computing environment to make feature weighting an affordable instrument for researchers in MIR.
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