One image can be worth thousands of words.
A confusion matrix is a convenient way to present the types of mistakes a machine learning mode makes. It is an N by N grid with numbers, where the value in the [n, m] cell represents the number of examples annotated with the n-th class recognized as the m-th class. In this tutorial, I will focus on creating a confusion matrix and a heatmap. The color palette will be used to display the sizes of different groups, making it easy to notice similarities or significant differences in group sizes. This kind of visualization is handy when you deal with numerous categories.
Here is a visual explanation of the elements of the confusion matrix.
