How to Remember all these Classification Concepts forever

Confusion matrix, Accuracy, Precision, Sensitivity, Specificity, F1 score, and Roc curve, let’s remember them once for all

Despite having seen all these concepts more than a thousand times, I’m still getting confused sometimes. Is there a good way to think about all these concepts so that they start making sense?

In this post, I will focus on how to remember them. If you’re not familiar with them, please read the following posts first.

Understanding the Confusion Matrix and How to Implement it in Python

Beyond Accuracy: Precision and Recall

Table of content

1. Confusion Matrix
2. Accuracy
3. Precision
4. Recall
5. Specificity
6. Tradeoff