Causes of Outcome Learning

Implementing the computational phase of the Causes of Outcome Learning approach as described in Rieckmann, Dworzynski, Arras, Lapuschkin, Samek, Arah, Rod, Ekstrom. Causes of outcome learning: A causal inference-inspired machine learning approach to disentangling common combinations of potential causes of a health outcome. medRxiv (2020) . The optional 'ggtree' package can be obtained through Bioconductor.


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install.packages("CoOL")

1.0.3 by Andreas Rieckmann, 17 days ago


https://bioconductor.org


Browse source code at https://github.com/cran/CoOL


Authors: Andreas Rieckmann [aut, cre] , Piotr Dworzynski [aut] , Leila Arras [ctb] , Claus Thorn Ekstrom [aut]


Documentation:   PDF Manual  


GPL-2 license


Imports Rcpp, data.table, pROC, graphics, mltools, stats, plyr, ggplot2, ClustGeo, wesanderson

Suggests ggtree, imager

Linking to Rcpp, RcppArmadillo


See at CRAN