USCbiostats/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.

Getting started

Package details

MaintainerMalcolm Barrett <[email protected]>
LicenseMIT + file LICENSE
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
USCbiostats/partition documentation built on June 5, 2019, 10:27 a.m.