I can use random forests to determine which features are important when doing a prediction problem; for example.
< height, weight, IQ measure> -> Is considered obese?
Applying random forests could tell me that weight contributes 0.75 percent to obesity.
But what if weight was dependent on height? For example
weight = height^2 + IQ Measure^3/height or something?
How would this affect the generated feature importances? Would this 'hidden' relationship have any consequences?
I just thought about this, and was wondering whether this could be an issue. As in, my feature importances would be inaccurate.