2016
JMLR
JMLR 2016
A Characterization of Linkage-Based Hierarchical Clustering
Abstract
The class of linkage-based algorithms is perhaps the most popular class of hierarchical algorithms. We identify two properties of hierarchical algorithms, and prove that linkage- based algorithms are the only ones that satisfy both of these properties. Our characterization clearly delineates the difference between linkage-based algorithms and other hierarchical methods. We formulate an intuitive notion of locality of a hierarchical algorithm that distinguishes between linkage-based and global hierarchical algorithms like bisecting $k$-means, and prove that popular divisive hierarchical algorithms produce clusterings that cannot be produced by any linkage-based algorithm. [abs] [ pdf ][ bib ] © JMLR 2016. (edit, beta)
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Keyword Pioneer
— linkage-based algorithm
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— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing
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Hot Topic Early Bird
— k-means clustering