Questions:
1. Has anyone used a package like "bnlearn" in R to guide the structure learning of one of these starting from data?
2. Would be curious about their relationship to CART models, Random Forest models and Causal Decision Trees (http://nugget.unisa.edu.au/jiuyong/CDT-Revision.pdf)
3. This feels like an important limitation Vs SCMs: "A system of transformations akin to the do-calculus is entirely absent and left for future work. Such a system is necessary for addressing questions about identification, i.e. whether a causal effect can be estimated from observation alone"
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[ 0.20 ms ] story [ 12.2 ms ] threadWhat are the areas where this approach would provide the most benefit Vs SCMs and Bayesian Networks? What are the trade-offs?
Linking to their tutorial notebook: https://colab.research.google.com/github/deepmind/deepmind_r...
Questions: 1. Has anyone used a package like "bnlearn" in R to guide the structure learning of one of these starting from data? 2. Would be curious about their relationship to CART models, Random Forest models and Causal Decision Trees (http://nugget.unisa.edu.au/jiuyong/CDT-Revision.pdf) 3. This feels like an important limitation Vs SCMs: "A system of transformations akin to the do-calculus is entirely absent and left for future work. Such a system is necessary for addressing questions about identification, i.e. whether a causal effect can be estimated from observation alone"