Confusion Matrix

A confusion matrix is a performance measurement for a classification problem in which there are two or more classes. The confusion matrix gives the number of predicted and actual labels for each of the possible classes. In the picture below, we can see what the classification matrix looks like for a binary problem.

• True positive – predicted positive and it’s true.
• True negative – predicted negative and it’s true.
• False positive – redicted positive but it’s false (it’s actually negative)
• False negative – predicted negative but it’s false (it’s actually positive)