calibrating-thresholds-and-baselines

wdm0006/python-skills

Check that a score-threshold-flag pipeline separates anything before trusting or tuning it - reference constants that are hand-authored but formatted as measurements, a feature whose units do not match the constant it is compared against, per-class fire rates exposing a flag that fires on nearly every item of both classes, rate features confounded by item length, confidence scores where one feature family contributes once per sub-feature, threshold sweeps hardcoded to one comparison direction and one statistic, and separating decision-carrying features from display-only ones

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