Precision
Of all the cases the model flagged as positive, the share that truly were positive. High precision means few false alarms. Prioritized when a false positive is the more expensive mistake. Formula: true positives divided by all predicted positives.
Defined in 3 GAGE programs, which carry 4 distinct definitions of it. The wording above is taught in Certified AI Transformation Professional (CATP).
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
Of all the cases the model flagged as positive, the share that truly were positive. High precision means few false alarms. Prioritized when a false positive is the more expensive mistake. Formula: true positives divided by all predicted positives.
Citing the exact instrument, date, section, or figure behind a claim, specific enough that the answer survives being repeated by someone else without introducing an error.
Of the cases a model flagged as positive, the fraction that were actually positive. Rises when you tighten the model to flag less.
Of the cases a model flagged as positive, the proportion that were actually positive; a measure of how often a positive flag is correct.
Where it is taught
The exact lessons this term appears in. The first 7 topics of every program are free with a free account.
- Fixing the model, breaking it again: why fixes are never free · Build Before You Govern, Certified AI Governance Professional (CAIGP)
- Trusted Expert Protocols: Being the Call They Make First · Positioning as the AI Point Person, The AI Lobbyist: Certified AI Policy Strategist
- How AI Actually Works Under the Hood: Architectures and Limits for Policy People · Technical Credibility Deep Dive, The AI Lobbyist: Certified AI Policy Strategist
- Analytics, Telemetry and Observability · Technology, Platforms and Vendors, Certified AI Transformation Professional (CATP)
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.