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fastcluster: Fast Hierarchical, Agglomerative Clustering Routines for R and Python

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  • Müllner, Daniel

Abstract

The fastcluster package is a C++ library for hierarchical, agglomerative clustering. It provides a fast implementation of the most efficient, current algorithms when the input is a dissimilarity index. Moreover, it features memory-saving routines for hierarchical clustering of vector data. It improves both asymptotic time complexity (in most cases) and practical performance (in all cases) compared to the existing implementations in standard software: several R packages, MATLAB, Mathematica, Python with SciPy.

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  • Müllner, Daniel, 2013. "fastcluster: Fast Hierarchical, Agglomerative Clustering Routines for R and Python," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 53(i09).
    • Handle: RePEc:jss:jstsof:v:053:i09
    DOI: http://hdl.handle.net/10.18637/jss.v053.i09
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    References listed on IDEAS

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    1. J. C. Gower & G. J. S. Ross, 1969. "Minimum Spanning Trees and Single Linkage Cluster Analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 18(1), pages 54-64, March.
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    2. Bahman Panahi & Mohammad Farhadian & Mohammad Amin Hejazi, 2020. "Systems biology approach identifies functional modules and regulatory hubs related to secondary metabolites accumulation after transition from autotrophic to heterotrophic growth condition in microalg," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-15, February.
    3. Benedict Anchang & Mary T Do & Xi Zhao & Sylvia K Plevritis, 2014. "CCAST: A Model-Based Gating Strategy to Isolate Homogeneous Subpopulations in a Heterogeneous Population of Single Cells," PLOS Computational Biology, Public Library of Science, vol. 10(7), pages 1-14, July.

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