False negative rate

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False Negative Rate

The False Negative Rate (FNR), also known as the Miss Rate, is a statistical measure used in binary classification systems, such as medical testing. It is the proportion of positive instances that are incorrectly classified as negative.

Pronunciation

False Negative Rate: /fɔːls ˈnɛgətɪv reɪt/

Etymology

The term "False Negative Rate" is derived from the field of statistical analysis. "False" refers to an incorrect or mistaken result, "Negative" refers to the absence of a condition or attribute, and "Rate" refers to the frequency or proportion of occurrences.

Definition

In the context of medical testing, the False Negative Rate is the probability that a test incorrectly indicates the absence of a condition when it is actually present. This is a critical measure as it can lead to missed diagnoses and delayed treatment.

Calculation

The False Negative Rate is calculated as the number of false negatives divided by the sum of the number of false negatives and true positives. This can be represented as:

FNR = FN / (FN + TP)

where:

  • FN = False Negatives
  • TP = True Positives

Related Terms

  • False Positive Rate: The proportion of negative instances that are incorrectly classified as positive.
  • Sensitivity: Also known as the True Positive Rate, it is the proportion of actual positive instances that are correctly identified.
  • Specificity: Also known as the True Negative Rate, it is the proportion of actual negative instances that are correctly identified.
  • Positive Predictive Value: The probability that instances predicted as positive are actually positive.
  • Negative Predictive Value: The probability that instances predicted as negative are actually negative.

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