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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>.
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Package details |
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| Author | Jeffrey L. Andrews [aut], Mackenzie R. Neal [aut], Paul D. McNicholas [aut, cre] (<https://orcid.org/0000-0002-2482-523X>) |
| Maintainer | Paul D. McNicholas <mcnicholas@math.mcmaster.ca> |
| License | GPL (>= 2) |
| Version | 0.7 |
| Package repository | View on CRAN |
| Installation |
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