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dc.contributor.authorHall, Mark A.
dc.coverage.spatialConference held at Dunedin, New Zealanden_NZ
dc.date.accessioned2008-12-02T00:43:33Z
dc.date.available2008-12-02T00:43:33Z
dc.date.issued1995
dc.identifier.citationHall, M. A. (1995). Selection of attributes for modelling Bach chorales by a genetic algorithm. In Proceeding of the 2n New Zealand Two-Stream International Conference on Artificial Neural Networks and Expert Systems (ANNES ‘95), 1995 (pp.182-185).en_US
dc.identifier.urihttps://hdl.handle.net/10289/1511
dc.description.abstractA genetic algorithm selected combinations of attributes for a machine learning system. The algorithm used 90 Bach chorale melodies to train models and randomly selected sets of 10 chorales for evaluation. Compression of pitch was used as the fitness evaluation criterion. The best models were used to compress a different test set of chorales and their performance compared to human generate models. G.A. models outperformed the human models, improving compression by 10 percent.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherIEEE Computer Societyen_US
dc.rightsThis article has been published in the Proceedings of the 2n New Zealand Two-Stream International Conference on Artificial Neural Networks and Expert Systems (ANNES ‘95), 1995. © IEEE Computer Society.en_US
dc.subjectcomputer scienceen_US
dc.subjectgenetic algorithmen_US
dc.titleSelection of attributes for modelling Bach chorales by a genetic algorithmen_US
dc.typeConference Contributionen_US
dc.identifier.doi10.1109/ANNES.1995.499468en_US
dc.relation.isPartOfProceeding of the 2nd New Zealand Two-Stream International Conference on Artificial Neural Networks and Expert Systemsen_NZ
pubs.begin-page182en_NZ
pubs.elements-id18443
pubs.end-page185en_NZ
pubs.finish-date1995-11-23en_NZ
pubs.start-date1995-11-20en_NZ


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