Date of Award
Master of Science
Jun Zhang, Tian Zhao
Algorithms, Classification, Clustering, Music
Classification and clustering of music genres has become an increasingly prevalent focusin recent years, prompting a push for research into relevant algorithms. The most successful algorithms have typically applied the Naive Bayes or k-Nearest Neighbors algorithms, or used Neural Networks to perform classification. This thesis seeks to investigate the use of unsupervised clustering algorithms such as K-Means or Hierarchical clustering, and establish their usefulness in comparison to or conjunction with established methods.
Stern, Samuel Walter, "Analysis of Music Genre Clustering Algorithms" (2021). Theses and Dissertations. 2839.