基于遗传算法的巴赫曲谱建模属性选择

M. Hall
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引用次数: 6

摘要

遗传算法为机器学习系统选择属性组合。该算法使用90首巴赫赞美诗旋律来训练模型,并随机选择10首赞美诗进行评估。采用节距压缩作为适应度评价标准。将最佳模型用于压缩不同的合唱测试集,并将其性能与人类生成的模型进行比较。遗传算法模型的表现优于人类模型,压缩率提高了10%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Selection of attributes for modeling Bach chorales by a genetic algorithm
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 generated models. GA models outperformed the human models, improving compression by 10 percent.
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