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I am curious when I can use cook's distance. I read here that it is only used for linear regression, but then on another site that it can be used for regression trees. So when is it appropriate to use Cook's distance. Can we use it for RF or SVR?

Thank you for all information or additional sources.

EDIT: From second source a user said:

I'd say that Cook's distance and Leverage generalize to a tree ensemble if we assume that the ensemble should approximate a function whose behavior could also be represented with a desired level of precision by a Generalized Linear Model. Not sure if this is the case.

Klemz
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