The sound of success: machine learning approaches to song popularity prediction
Ceccarelli, Pierpaolo Maria (A.A. 2024/2025) The sound of success: machine learning approaches to song popularity prediction. Tesi di Laurea in Advanced coding for data analytics, Luiss Guido Carli, relatore Alessio Martino, pp. 21. [Bachelor's Degree Thesis]
Full text for this thesis not available from the repository.
Abstract/Index
Literature review. Music popularity prediction in research. Machine learning applications in music. Gaps and opportunities. Dataset and research methods. Dataset description. Feature engineering and preprocessing. Machine-learning models and hyperparameter tuning. Train–test splitting and reproducibility. Results. Overview and experimental setup. Quantitative results and interpretation. Diagnostic figures and error behaviour. Model selection and practical guidance. Limitations and reproducibility.
References
Bibliografia: p. 17.
| Thesis Type: | Bachelor's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Bachelor's Degree Programs > Bachelor's Degree Program in Management and Computer Science, English language (L-18) |
| Chair: | Advanced coding for data analytics |
| Thesis Supervisor: | Martino, Alessio |
| Academic Year: | 2024/2025 |
| Session: | Autumn |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 26 May 2026 08:49 |
| Last Modified: | 26 May 2026 08:49 |
| URI: | https://tesi.luiss.it/id/eprint/45890 |
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