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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. Edrisse Chermak & Renato De Donato & Marc F Lensink & Andrea Petta & Luigi Serra & Vittorio Scarano & Luigi Cavallo & Romina Oliva, 2016. "Introducing a Clustering Step in a Consensus Approach for the Scoring of Protein-Protein Docking Models," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-15, November.
    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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