Conformal prediction silently breaks under drift - and how to make it hold

Conformal prediction is the easiest way to put a calibrated uncertainty band around any model: wrap a point predictor, and you get intervals with a finite-sample coverage guarantee — no distributional assumptions. It's deservedly popular. There's a catch that bites in production: that guarantee...

Source: [Dev.to](https://dev.to/whatsonyourmind/conformal-prediction-silently-breaks-under-drift-and-how-to-make-it-hold-466g)