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Music education informatization system can promote music teaching; in addition, due to the characteristics of music disciplines such as the audiovisual nature of music, the influence of informatization on music teaching is self-evident. With the rapid development of the human ability to obtain information, machine learning algorithms have been widely used in various fields of scientific research and engineering, involving chemical production statistical process control, archeology text recognition, social and criminal investigation field fingerprint and image recognition, and genomic information research in the field of biomedicine. In order to correctly evaluate the music education information system based on machine learning, through the comparison of four models, it is concluded that the construction of the GBDT model is optimal.
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Wang et al. (2022) studied this question.
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