vscc: Variable Selection for Clustering and Classification
Performs variable selection/feature reduction under a clustering or
classification framework. In particular, it can be used in an automated fashion
using mixture model-based methods ('teigen' and 'mclust' are currently supported).
Can account for mixtures of non-Gaussian distributions via Manly transform (via 'ManlyMix').
See Andrews and McNicholas (2014) <doi:10.1007/s00357-013-9139-2> and Neal and McNicholas (2023)
<doi:10.48550/arXiv.2305.16464>.
| Version: |
0.6 |
| Depends: |
ManlyMix |
| Imports: |
teigen, mclust |
| Published: |
2023-06-06 |
| Author: |
Jeffrey L. Andrews [aut],
Mackenzie R. Neal [aut],
Paul D. McNicholas [aut, cre] |
| Maintainer: |
Paul D. McNicholas <mcnicholas at math.mcmaster.ca> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| Citation: |
vscc citation info |
| Materials: |
ChangeLog |
| CRAN checks: |
vscc results |
Documentation:
Downloads:
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