Actually causal inference is also really hard to benchmark. My colleague started an effort to be actually able to reproduce and compare results. Also the algorithms often do not scale too well.
Everytime we wanted to use this for real data it is just a little bit too much effort and the results are not conclusive because it is hard to verify huge graphs. My colleague e.g. wanted to apply it explain risk confounders in investment funds.
I personally also do not like the definition of causality they base it on.
Everytime we wanted to use this for real data it is just a little bit too much effort and the results are not conclusive because it is hard to verify huge graphs. My colleague e.g. wanted to apply it explain risk confounders in investment funds.
I personally also do not like the definition of causality they base it on.