doMIsaul: Do Multiple Imputation-Based Semi-Supervised and Unsupervised Learning

Algorithms for (i) unsupervised learning for dataset with missing data and/or left-censored data, using multiple imputation and consensus clustering ; (ii) semi-supervised learning with a survival endpoint (right-censored) for complete or incomplete datasets, using multiple imputation and consensus clustering in the latter case. The methods are described in Faucheux et al. (2021) <doi:10.1002/bimj.201900366> and Faucheux et al. (2021) <doi:10.1002/bimj.202000365>, respectively.

Getting started

Package details

AuthorLilith Faucheux [aut, cre], Sylvie Chevret [ths], Matthieu Resche-Rigon [ctb], Marie Perrot-Dockès [ctb], Eric Han [ctb]
MaintainerLilith Faucheux <lilith.faucheux@inserm.fr>
LicenseGPL (>= 3)
Version1.0.1
URL https://github.com/LilithF/doMIsaul
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("doMIsaul")

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doMIsaul documentation built on Oct. 19, 2021, 1:07 a.m.