Confusion Matrices

In Luis's Evaluation Metrics section, we learned about confusion matrices, and if you need a refresher, the video is below.

Type 1 and Type 2 Errors

Sometimes in the literature, you'll see False Positives and True Negatives as Type 1 and Type 2 errors. Here is the correspondence:

• Type 1 Error (Error of the first kind, or False Positive): In the medical example, this is when we misdiagnose a healthy patient as sick.
• Type 2 Error (Error of the second kind, or False Negative): In the medical example, this is when we misdiagnose a sick patient as healthy.

But confusion matrices can be much larger than
2 \times 2. Here's an example of a larger one. Let's say we have three illnesses called A, B, C. And here is a confusion matrix:

As you can see, each entry in the
i-th row and the
j-th column will tell you the probability of the patient having illness
i and getting diagnosed with illness
j.

For example, from the entry on the second row and the first column, we can determine that if a patient has illness B, the probability of getting diagnosed with illness A is exactly 0.08.

Now, let's test our knowledge with some quizzes.