More features is not more signal, it is more variance, more leakage surface, and a thinner data manifold. The disciplined answer ranks filter, embedded, and wrapper methods by cost, leans on L1, and screens every survivor for leakage and stability.
Updated Aug 2026 · Grounded in real Forward Deployed Engineer interview loops and written to a senior-engineer editorial bar.
More features is not more signal, it is more variance, more leakage surface, and a thinner data manifold. The disciplined answer ranks filter, embedded, and wrapper methods by cost, leans on L1, and screens every survivor for leakage and stability.
The leakage point is what interviewers at Capital One and Amazon are really hunting for. A candidate who selects purely by importance score will happily keep a feature that is a proxy for the label and will not exist at scoring time. The senior move is to treat feature importance and predictive-of-the-label as a red flag to investigate, not a green light, and to check selection stability across resamples before trusting any ranking.
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