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5.2码/包

 

人工智能之强化学习 

 

 

  在这一部分中,我们学习用于因果推理的可用代码或工具包。

 

表2和表3提供了第3节中提到的方法的代码,

其中表2列出了工具包及其支持的方法和语言,表3列出了一种特定方法的开源代码。

 

                            表2.用于因果推断的可用工具包

工具包支持方法语言链接
Dowhy [124]基于倾向的分层,PSM, IPW,回归Python
https://github.com/microsoft/dowhy
Causal ML基于树的算法,X/T/X/R-learnerPythonhttps://github.com/uber/causalml
EconML [100]双重健壮的学习者,正交随机森林,元学习者,深度工具变量Pythonhttps://github.com/microsoft/EconML#blogs-and-publications
causalToolboxBART,因果森林,T/X/S-learner以及BART/RF作为基础学习Rhttps://github.com/soerenkuenzel/causalToolbox

 

 

                                        表3  第3节中可用的方法代码

方法语言链接
IPWhttps://cran.r-project.org/web/packages/ipw/index.html
DRR fastDR: https://github.com/gregridgeway/fastDR DR for High dimension: https://github.com/gregridgeway/fastDR
主要分层https://cran.r-project.org/web/packages/sensitivityPStrat/index.html
分层https://cran.r-project.org/web/packages/stratification/

PSM

重叠的重量

梯形的重量

Python https://cran.r-project.org/web/packages/PSW/

基于匹配的算法:

完全匹配,

完全匹配,

基因匹配,

最近邻居匹配,

最佳匹配,

子分类

https://cran.r-project.org/web/packages/MatchIt/
PSM Python https://github.com/akelleh/causality
完美的匹配Pythonhttps://github.com/d909b/perfect_match
最优匹配 https://cran.r-project.org/web/packages/Matching/
CEM https://cran.r-project.org/web/packages/cem/
TMLE https://cran.r-project.org/web/packages/tmle/index.html
CMGP Python https://bitbucket.org/mvdschaar/mlforhealthlabpub/src/ baa0aa33a6af3fe490484c9e11e3a158968ae56a/ alg/causal_multitask_gaussian_processes_ite/
BART  Rhttps://cran.r-project.org/web/packages/BayesTree/index.html Python https://github.com/JakeColtman/bartpy
GANITE Python  https://bitbucket.org/mvdschaar/mlforhealthlabpub/src/ baa0aa33a6af3fe490484c9e11e3a158968ae56a/alg/ganite/

BNN , 

CFR-MMD 

Python https://github.com/clinicalml/cfrnet
CEVAE Python https://github.com/AMLab-Amsterdam/CEVAE
SITE Python https://github.com/Osier-Yi/SITE
grf  Rhttps://cran.r-project.org/web/packages/grf/index.html
R-learner  Rhttps://github.com/xnie/rlearner/blob/master/R/xlearner.R
剩余平衡 R https://github.com/swager/balanceHD
CBPS R https://github.com/kosukeimai/CBPS
龙网Python  github.com/claudiashi57/dragonnet
熵平衡https://cran.r-project.org/web/packages/ebal/
DRNets Python https://github.com/d909b/drnet
网络解构者Pythonhttps://github.com/rguo12/network-deconfounder-wsdm20
网络嵌入Python https://github.com/vveitch/causal-network-embeddings
RMSN Python  https://github.com/vveitch/causal-network-embeddings
TMLE Rhttps://github.com/joshuaschwab/ltmle
LCVA Python https://github.com/rguo12/CIKM18-LCVA

 

 

 

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