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) and Faucheux et al. (2021) , respectively.


Reference manual

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1.0.0 by Lilith Faucheux, 2 months ago

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Authors: Lilith Faucheux [aut, cre] , Sylvie Chevret [ths] , Matthieu Resche-Rigon [ctb] , Marie Perrot-Dock├Ęs [ctb] , Eric Han [ctb]

Documentation:   PDF Manual  

GPL (>= 3) license

Imports aricode, arules, clusterCrit, dplyr, ggplot2, Gmedian, graphics, MASS, methods, mice, NbClust, ncvreg, plyr, scales, stats, survival, utils, withr

Suggests censReg, cluster, CPE, dbscan, e1071, ggpubr, Hmisc, igraph, mclust, parallel, RColorBrewer, reshape2, testthat, timeROC, truncnorm

See at CRAN