doi:10.1016/j.patcog.2018.10.026>. Such methods can inform whether clustering algorithms are appropriate for a data set.">

clusterability: Performs Tests for Cluster Tendency of a Data Set (original) (raw)

Test for cluster tendency (clusterability) of a data set. The methods implemented - reducing the data set to a single dimension using principal component analysis or computing pairwise distances, and performing a multimodality test like the Dip Test or Silverman's Critical Bandwidth Test - are described in Adolfsson, Ackerman, and Brownstein (2019) <doi:10.1016/j.patcog.2018.10.026>. Such methods can inform whether clustering algorithms are appropriate for a data set.

Version: 0.1.1.0
Depends: R (≥ 3.4.0)
Imports: diptest, splines
Suggests: testthat
Published: 2020-03-04
DOI: 10.32614/CRAN.package.clusterability
Author: Zachariah Neville [aut, cre], Naomi Brownstein [aut], Maya Ackerman [aut], Andreas Adolfsson [aut]
Maintainer: Zachariah Neville <z.neville at stat.fsu.edu>
License: GPL-2
NeedsCompilation: no
Materials: README NEWS
CRAN checks: clusterability results

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