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Champion–challenger

Champion–challenger means one model is live (the champion) while others train on the same data and folds (challengers). If a challenger wins by enough, it takes the job. Loyalty is to the score.

This is how you avoid the annual model rewrite. The world changes in weeks. Bake-offs that happen in Q4 for a Q1 launch are already late.

Pinning is allowed. A human can freeze a champion for a regulated line. The tournament still runs in the dark, so you know what you are refusing.

Same folds, five candidates

Seasonal naive

16.4%

Smoothing

14.1%

Gradient boost

11.2%

Foundation

9.7%

Fine-tuned

10.1%

The champion is a job title for this run. Next month the booster might take it back. Loyalty belongs to the score.

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