Answer
A confusion matrix is a table used to evaluate a classification model by showing the counts of correct and incorrect predictions broken down by actual and predicted classes.
Real-world example A confusion matrix reveals that a medical AI model often mistakenly predicts a healthy patient as sick, which is a false positive.