Result: The Role of Mastering Musical Instrument Playing Skills Combined with Student Behavior Data Mining and Analysis in the Digital Campus Environment to Improve Students' Comprehensive Quality.

Music is closely related to people's lives, and it has a certain impact on people's lives. In school teaching activities, mastering the skills of playing musical instruments can effectively improve students' music appreciation ability and level and enhance students' comprehensive quality through subtle influence. Based on the analysis of students' behavior data, this paper analyzes the role of mastering musical instrument playing skills in improving students' comprehensive quality and puts forward research ideas and schemes. It focuses on students' group behavior in the digital campus environment, integrates multisource data in the digital campus, quantificationally calculates students' multidimensional behaviors, studies the behavior rules of students with different academic performance levels, and uses machine learning algorithm to build a multifeature integrated model of students' comprehensive quality, providing personalized feedback for the improvement of students' comprehensive quality. The results show that the effect of mastering musical instrument playing skills combined with data mining analysis of students' behavior is generally 30% higher than that of the previous research. Compared with a single model, the fused model can fully consider each algorithm to observe data from different data spaces and structures and give full play to the advantages of different algorithms. The training of a single model will fall into the local minimum, which may lead to the relatively poor generalization performance of its model. However, the weighted fusion of multiple basic learners can effectively reduce the probability of falling into the local minimum. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Environmental & Public Health is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)