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Analysis Of Music Genre Clustering Algorithms, Samuel Walter Stern
Analysis Of Music Genre Clustering Algorithms, Samuel Walter Stern
Theses and Dissertations
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.