- Block 15 — The classification metrics
- Objective
- define specificity as the fraction of actual negatives a rule leaves alone;
establish
specificity = 1 − FPR and why the ROC axis is the complement rather than the quantity;
derive its invariance to prevalence and its monotone non-decrease in the threshold, the exact
mirror of recall, and tabulate both rates on one score vector; give the three correct ways to
compute it in a library that has no specificity_score; measure the central warning, that under
imbalance specificity is almost always high and almost always uninformative, with an
information-free rule measured at 0.998; work the alarm-volume arithmetic n(1 − p)(1 − s) and a
costed screening program in which the specificity floor fixes the operating point; compute
Youden's J as a threshold rule; compute one-vs-rest specificity and its inflation by the number
of classes; compute confidence intervals; and measure what an unverified negative class does to a
specificity figure. - Estimated duration
- 85 minutes
- Prerequisites
- chapters 011, 029, 030, 034, 050, 051, 052, 053, 054 and 055
- Associated quizzes
056.1-quiz-definition-and-the-negative-row.md to
056.10-quiz-reporting-specificity.md