Forest-Based regression with non-normally distributed data?

2 weeks ago
New Contributor

Does anyone know how robust the Forest-Based regression is to non-normally distributed data? I've tried every data transformation possible and settled with a square root transformation which turned out to be the "least unsuccessful transformation. The subsequent model was still able to get a good R2 of 0.91, but I'm wondering how robust/sensitive the forest-based algorithm is.

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