Problem
Scenario
You're training a supervised model and have a large set of candidate features, some of which may be redundant, noisy, or unstable across samples.
Question
How would you approach feature selection for a model?
Example Dataset
Size·1.2M TikTok For You impressions, 180 candidate featuresTarget·Binary engagement labelClass balance·14% positiveFeature types·Numerical, categorical, recency, count, and cross features
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