Hi everyone,
I have an outcome that depends on ~1000 features, and I was wondering if there is a standard/optimal way to find the features that most impact this outcome.
I thought about fitting interpretable models such as decision trees or random forests, but I wonder if it’s right to use machine learning for this, because I think a feature can have a lot of influence without necessarily be a good predictor (for example, if a feature generates a lot of randomness in the output when given a certain value).
Does anyone have any advice or pointer to resources regarding this topic?
Thanks