Abstract
This paper focuses on the possibility of using machine learning to predict song success. The purpose of this paper is to design and implement an application that allows the prediction of the commercial success of a musical piece using machine learning algorithms. The prediction is based on data concerning songs which have been Billboard charts as well as songs that are not on the charts. For the comparison three machine learning algorithms were selected for comparison: random forest, logistic regression and gradient enhancement. Model optimization was also performed using recursive feature elimination and hyperparameters tuning.
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Walczyński, M., Kisz, M. (2023). Using Machine Learning Algorithms to Explore Listeners Musical Tastes. In: Nguyen, N.T., et al. Recent Challenges in Intelligent Information and Database Systems. ACIIDS 2023. Communications in Computer and Information Science, vol 1863. Springer, Cham. https://doi.org/10.1007/978-3-031-42430-4_33
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DOI: https://doi.org/10.1007/978-3-031-42430-4_33
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