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

Pearl's famous causal polytree recover algorithm is implemented here.
821 Downloads
Updated 1 Feb 2010

View License

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

Cite As

Guangdi Li (2024). Causal Polytree ---Pearl's classical algorithm(1988) (https://www.mathworks.com/matlabcentral/fileexchange/26489-causal-polytree-pearl-s-classical-algorithm-1988), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2008a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
Find more on Statistics and Machine Learning Toolbox in Help Center and MATLAB Answers

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Published Release Notes
1.3.0.0

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

1.2.0.0

update the graph

1.0.0.0