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Learn assignment-based clustering techniques through this comprehensive lecture covering k-means, k-median, k-medoid, and k-center formulations. Explore the theoretical foundations and practical implementations of the Gonzalez Algorithm and Lloyd's algorithm, while mastering the k-means++ initialization method for improved clustering performance. Gain deep understanding of how these related clustering algorithms work, their mathematical formulations, and when to apply each variant depending on your data characteristics and clustering objectives.
Syllabus
L9 - k-means (and friends)
Taught by
UofU Data Science