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Suppose I have an existing decision tree. I feel that variable "a" is a useful predictor when combined with variable "b", but that it is not being considered useful as "a" is correlated with "c" and "c" and "b" are already in my decision tree. How do I solve this issue?

I was hoping someone could help me with this.

Aurpa
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  • Correlated features should not be a problem for a decision tree https://stats.stackexchange.com/questions/377033/collinearity-of-features-and-random-forest/377047#377047 – Tim Dec 04 '21 at 19:05

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