Feature Drift Monitor

機械支援の翻訳下書き (Japanese) for "Feature Drift Monitor": Feature Drift Monitor is a ml monitor that detects when data or predictions no longer match the training baseline for input signals used by a machine learning model. It uses statistical tests, time windows, and alert thresholds so teams can respond before quality drops while keeping evidence, reliability, and public-safe operational boundaries clear.

“例文の下書き: The machine learning team used Feature Drift Monitor when a feature distribution shifted, so the team could respond before quality drops before the model moved into evaluation.”