False Positive Rate Calculator

False Positive Rate Calculator calculator can be used to calculate the proportion of actual negatives that are incorrectly identified as positives. This is useful in medical testing, quality control, and machine learning.

Input Parameters

Calculation Results

False Positive Rate (FPR)

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Where:
FPR = False Positives / (False Positives + True Negatives)
FPR represents the proportion of actual negatives that are incorrectly identified as positives.

False Positive Rate Calculator Usage Guide

Learn how to use the False Positive Rate Calculator and its working principles

What is False Positive Rate (FPR)?

False Positive Rate (FPR), also known as the False Alarm Rate, is a measure of the rate of false positive inferences made by a binary classification system. It is defined as the ratio of false positives to the total actual negatives in a dataset.

How to Use This Calculator

  1. Enter the number of True Negatives (TN): This is the count of actual negatives that were correctly identified as negatives.
  2. Enter the number of False Positives (FP): This is the count of actual negatives that were incorrectly identified as positives.
  3. Click the "Calculate" button to compute the False Positive Rate.
  4. The result will be displayed as a decimal value (e.g., 0.05 represents 5% FPR).

Example

If you have 95 true negatives and 5 false positives, the FPR would be calculated as:

5 / (5 + 95) = 5 / 100 = 0.05 or 5%

When to Use FPR

FPR is particularly important in scenarios where false alarms are costly or undesirable:

  • Medical testing where false positive diagnoses may lead to unnecessary treatments
  • Security systems where false alarms can cause panic or resource wastage
  • Quality control in manufacturing where false positives can lead to discarding good products