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> And also: when do we want to decide to use alternatives like decision trees instead -- because despite being less accurate, they can have designers who can be held legally accountable and liable, which can be more important in certain situations?

Decision trees are black box models and are highly accurate. (Think XGBoost, LightGBM, Random Forest, etc)

Not sure what point you are trying to make here.



Those models are ensembles of decision trees. A single tree is interpretable, but sensitive to overfitting.




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