Causal Polytree ---Pearl's classical algorithm(1988)
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
Citation pour cette source
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. Récupéré le .
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Version | Publié le | Notes de version | |
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1.3.0.0 | update the file "IsLeaf.m", sorry about my carelessness. |
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1.2.0.0 | update the graph |
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1.0.0.0 |