A confusion matrix displays the number of correct or incorrect predictions made by a classifier such as a Bayesian network.
Diagonal elements of the matrix show the number of correct predictions, while offdiagonal elements show incorrect predictions.
An example is shown below.
Note 

When classifiers predict an output which is true or false, we get the following terms:
