The sealed holdout: why we looked at our test data exactly once

Here's a loop most of us have run: Build a model. Check it on the test set. Not great. Tweak a feature. Check again. After twenty rounds the test score looks good. But you've been fitting the test set, one decision at a time. The number no longer estimates how the model does on new data. Sealing it…

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1. 2026-10-29 11:17 · DEV Community — Machine Learning
   The sealed holdout: why we looked at our test data exactly once