Skip to content

caus-am/dom_adapt

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

19 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

dom_adapt

Code for the NIPS 2018 paper "Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions"

Installation instructions

The code expects a Clingo solver in the folder ASP (point 1) and a few R packages (point 2):

1. Download the new clingo

2. Install the R packages(*)

  • 2.1 Install Bioconductor packages

    • With R version 3.5 or greater, use BiocManager:
    if (!requireNamespace("BiocManager", quietly = TRUE))
        install.packages("BiocManager")
    BiocManager::install(version = "3.12")
    
    BiocManager::install(c('graph','RBGL','gmp','RcppArmadillo'))
    
    • With R version lesser than 3.5, install:
    source('http://bioconductor.org/biocLite.R')
    biocLite(c('graph','RBGL','gmp','RcppArmadillo'))
    
  • 2.2 Install the remaining packages:

    install.packages(c('deal','combinat','hash','bnlearn','foreach','doMC','caTools','expm'))
    install.packages(c('pcalg'))
    

    Note that:

    • Installing 'pcalg' may require you to install also a few other packages (e.g. robustbase, ggm).
    • For R version 4.0.4 'pcalg' dependencies are managed automatically.

3. Start R

  • Navigate to the R/ directory and run:
    source('load.R')
    loud()
    

(*) If you want to keep your global environment unchanged, please, consider using the renv package (https://rstudio.github.io/renv/).

About

Code for the NIPS 2018 paper "Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions"

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors