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

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

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26 Jan 2010 (Updated )

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

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Description

      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)
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Comments and Ratings (4)
12 Feb 2010 Guangdi Li

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.

12 Feb 2010 Liviu Vladutu

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

01 Feb 2010 Guangdi Li

sorry about it , I have updated it.

01 Feb 2010 Sebastien PARIS

IsLeaf function undefined ....

Updates
01 Feb 2010

update the graph

01 Feb 2010

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

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