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)
- Version0.7
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- vscc citation info
- Last release10/17/2023
Documentation
Team
Paul D. McNicholas
Jeffrey L. Andrews
Show author detailsRolesAuthorMackenzie R. Neal
Show author detailsRolesAuthor
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- Depends1 package
- Imports3 packages