## 21.1 Classifier performance & fairness (1): False positives & negatives

• Above: Correct Classification Rate (CCR) [as opposed to Error Rate]
• For what proportion of the units does the correct output $$y_{i}$$ match the classifier (predicted) output $$\hat{y}_{i}$$?
• Proportion of reoffenders correctly predicted
• False Positive Rate (FPR)
• For what proportion of the units for which the correct output $$y_{i}$$ is negative is the classifier output $$\hat{y}_{i}$$ positive?
• Proportion of NON reoffenders (NON recidivators) predicted as reoffenders (recidivators)
• What then is the False Negative Rate (FNR) be?