What is Confusion Matrix?
In the field of machine learning, a confusion matrix, also known as a contingency table or an error matrix is a specific table layout that allows visualization of the performance of an algorithm, typically a supervised learning one. Each column of the matrix represents the instances in a predicted class, while each row represents the instances in an actual class. The name stems from the fact that it makes it easy to see if the system is confusing two classes (i.e. commonly mislabeling one as another).
Input: Dictionary [keys: actual, items: predicted]
Output: Formatted confusion matrix on screen
Run: python ConfusionMatrix.py