Markdown

FPR

FPR is the Acronym for False Positive Rate

A performance metric used to evaluate the effectiveness of a binary classification model. It measures the proportion of actual negative cases that are incorrectly identified as positive by the model.

ROC Curve and AuC
Source: ROC Curve Explained In One Picture

The False Positive Rate is calculated as follows:

Loading formula...

Where:

  • False Positives (FP) are the number of negative cases that were incorrectly classified as positive by the model.
  • True Negatives (TN) are the number of negative cases that were correctly classified by the model.