Answer - A confusion matrix, also known as an error matrix, is a specific table layout that allows visualization of the performance of an algorithm, typically a supervised learning one. Every row of the matrix represents the instances in an actual class while each column represents the instances in a predicted class, or vice versa. The name stems from the fact that it makes it easy to see whether the system is confusing two classes. Further, it can be considered as a special kind of contingency table, with two dimensions (“actual” and “predicted”), and identical sets of “classes” in both dimensions.