Code covered by the BSD License  

Highlights from
Causal Polytree ---Pearl's classical algorithm(1988)

Be the first to rate this file! 7 Downloads (last 30 days) File Size: 3.23 KB File ID: #26489 Version: 1.3
image thumbnail

Causal Polytree ---Pearl's classical algorithm(1988)


Guangdi Li (view profile)


26 Jan 2010 (Updated )

Pearl's famous causal polytree recover algorithm is implemented here.

| Watch this File

File Information

      As a famous sub-structure of Bayesian network, causal polytree is able to recover the causality very efficiently.

       Here, I implement pearl's classical algorithm here for easy using. Details can be seen in Pearl's paper[1].

       To recover general Causal polytree, one can download "Fisher's exact test" in my space for conditional independence test.

       One can start from ControlCenter.m, I add a simple example there for better understanding.

       If there is any question, just let me know, I will response to you as soon as possible.

[1] G. Rebane, J. Pearl, The recovery of causal poly-trees from statistical data, in: Proceedings of the Third Conference on Uncertainty Artificial Intelligence, Seattle, Washington, 1987, pp. 222–228

MATLAB release MATLAB 7.6 (R2008a)
Tags for This File   Please login to tag files.
Please login to add a comment or rating.
Comments and Ratings (4)
12 Feb 2010 Guangdi Li

Guangdi Li (view profile)

The function " view(biograph( A ))"
demonstrates the matrix A in the form of nice graph. Indeed, you need that toolbox to visually check the result, instead of checking the produced matrix manually.

Comment only
12 Feb 2010 Liviu Vladutu

Your example it relies on a script biograph from Computational Biology tbox....

Comment only
01 Feb 2010 Guangdi Li

Guangdi Li (view profile)

sorry about it , I have updated it.

Comment only
01 Feb 2010 Sebastien PARIS

Sebastien PARIS (view profile)

IsLeaf function undefined ....

Comment only
01 Feb 2010 1.2

update the graph

01 Feb 2010 1.3

update the file "IsLeaf.m", sorry about my carelessness.

Contact us