Application of improved K-means algorithm in the cultivation of creative music talents under the needs of sustainable development and transformation
by Peng Li; Zeng Fan
International Journal of Web Engineering and Technology (IJWET), Vol. 19, No. 1, 2024

Abstract: In order to cultivate innovative personnel who are adapted to the development of university education, this paper proposes a K-means clustering algorithm (K-means) based on noise reduction autoencoder for the cultivation of creative music talents and explores the difficulties in cultivating innovative talents. The results show that the research-designed method outperforms K-means on the performance metrics NMI, AMI and FMI for the same dataset. The results of the practical application analysis show that the training of practical operation is weakened in talent training, and the emphasis on practical courses should be strengthened in the subsequent talent training plan.

Online publication date: Mon, 29-Apr-2024

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