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      Selection of attributes for modelling Bach chorales by a genetic algorithm

      Hall, Mark A.
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      selection of attributes for modeling bach.pdf
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      DOI
       10.1109/ANNES.1995.499468
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      Hall, 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).
      Permanent Research Commons link: https://hdl.handle.net/10289/1511
      Abstract
      A 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.
      Date
      1995
      Type
      Conference Contribution
      Publisher
      IEEE Computer Society
      Rights
      This 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.
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      • Computing and Mathematical Sciences Papers [1452]
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