SYSTEMA CONSTRUCTUM

Accepted ontology entry

false negative rate

A false negative rate is the proportion of actual positive cases that are incorrectly classified as negative by a binary classifier. It is computed as FN/(TP+FN), where FN is the count of false negatives and TP+FN is the total number of ac…

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Definition

A false negative rate is the proportion of actual positive cases that are incorrectly classified as negative by a binary classifier. It is computed as FN/(TP+FN), where FN is the count of false negatives and TP+FN is the total number of actual positives. Unlike the false positive rate which measures error among actual negatives, the false negative rate measures the classifier's failure to detect actual positives. Low false negative rates are critical in safety-sensitive applications such as medical screening and fraud detection, where missing a true positive carries high cost. [formal: fnr | substrate: behavior | horizon: a moment | explicit: yes | epoch: 0.01]

Why it is in scope

A human-made statistical measure used in binary classification evaluation: the proportion of actual positives that are incorrectly identified as negative, computed as FN/(TP+FN). Built to persist through repeated use in model evaluation, reporting, and comparison of classification systems.

Names and aliases

Relations from this entry

  • cmrwiv1rn00a8soacg5vdpiogINSTANCE_OF →

    Tested INSTANCE_OF: Is false negative rate a specific kind of metric? Yes — it is a single numerical measure (FN/(TP+FN)) of classifier performance. A competent speaker would call false negative rate 'a metric'. Direction is specific→general against the nearest kind.

  • cmrxj3acr03cmsoacx73fal1oDEPENDS_ON →

    False negative rate is a statistical metric that requires statistical theory to operate. Remove statistics and the concept, calculation, and interpretation of false negative rate ceases to function.

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Record identity

Created
Aug 5, 2026, 2:57 AM UTC
Content hash
0cbcc93489b4e07b0c5cce5df1f6329cf11a61effdb4fadbd361d5e4a884020d

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