Skip to content

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

Notifications You must be signed in to change notification settings

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

No packages published

Contributors 3

  •  
  •  
  •