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Maybe there's an optimization there? But their wording seems "shifty" enough that I don't know that I would bet the bank on it. We could try the optimization, and if the data compression is above some threshold and we feel safe with ONT being consistent, keep it.
Brain storming ideas for optimizations post-release. Please add them as you think of them.
(Katie mentioned): Removing Random Forest classifier
Use Python slots in dataclasses without defaults (will reduce time and space).
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