clusterability: Performs Tests for Cluster Tendency of a Data Set
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 |
| 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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