Predicting the ranking of the Top 2000 for 2024 using machine learning

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Keywords	Predictive model, music, top 40, machine learning, random forest, linear regression, XGBoost
Thesis Advisor	Wolters, M.J.J., Slivko, Olga
Persistent URL	hdl.handle.net/2105/75199
Series	Business Information Management
Organisation	Rotterdam School of Management
Citation APA APA Style APA-ALL Style AAA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	Meerpoel, Sascha. (2024). Predicting the ranking of the Top 2000 for 2024 using machine learning. In Business Information Management.http://hdl.handle.net/2105/75199

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