partition
Agglomerative Partitioning Framework for Dimension Reduction
A fast and flexible framework for agglomerative partitioning. 'partition' uses an approach called Direct-Measure-Reduce to create new variables that maintain the user-specified minimum level of information. Each reduced variable is also interpretable: the original variables map to one and only one variable in the reduced data set. 'partition' is flexible, as well: how variables are selected to reduce, how information loss is measured, and the way data is reduced can all be customized. 'partition' is based on the Partition framework discussed in Millstein et al. (2020)
- Version0.2.2
- R version≥ 3.3.0
- LicenseMIT
- Licensefile LICENSE
- Needs compilation?Yes
- Languageen-US
- partition citation info
- Last release10/09/2024
Documentation
Team
Malcolm Barrett
Joshua Millstein
Show author detailsRolesAuthorKatelyn Queen
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- Depends1 package
- Imports15 packages
- Suggests8 packages
- Linking To2 packages
- Reverse Imports1 package