A sensitivity plot is a visual encoding that displays how a model's predictions or outputs change as one or more input parameters vary. It carves by method: the plot persists a systematic perturbation of inputs (one-at-a-time or in combination) and records the resulting output deltas. Its persistence mechanism is the plotting convention — typically a line or scatter plot with a parameter on one axis and a response metric on the other — maintained by sensitivity-analysis practice in computational modelling. [formal: sensitivus | substrate: mind | horizon: a moment | explicit: yes | epoch: 0.01]
Accepted ontology entry
sensitivity
A sensitivity plot is a visual encoding that displays how a model's predictions or outputs change as one or more input parameters vary. It carves by method: the plot persists a systematic perturbation of inputs (one-at-a-time or in combina…
Definition
Why it is in scope
Sensitivity is a human-made statistical metric that measures the proportion of actual positive cases correctly identified by a test or classifier. It is a construct of statistical theory and diagnostic evaluation, built to persist through mathematical notation and scientific practice.
Names and aliases
- sensitivityen · CANONICAL
Relations from this entry
- cmrwiv1rn00a8soacg5vdpiogINSTANCE_OF →
Sensitivity (TPR = TP/(TP+FN)) IS a specific kind of metric: a numerical measure of a binary classifier's ability to find positives. A competent speaker would call sensitivity 'a metric' — it is a single number measuring classifier performance.
Relations to this entry
- cmsfcaft106xw3vv35y0oshsx← DEPENDS_ON
f-measure = 2·(precision·recall)/(precision·+·recall), and sensitivity IS recall. Remove sensitivity (recall) and the f-measure formula collapses — it cannot operate without this parameter. Present-tense dependency per Law 8.
Record identity
- Created
- Aug 5, 2026, 1:30 AM UTC
- Content hash
- f482c962b7b1d62bdfc5e72921a7b8dbdf9f02d1cd2b14c4cc6f0bffd529b5f7