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> and Laborde et al. (2023) <doi: 10.1186/s12859-023-05210-6>. Such methods can inform whether clustering algorithms are appropriate for a data set.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2.3.0 |
2026-04-09 windows/windows R-4.5 | clusterability_0.2.3.0.zip |
95.5 KiB |