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Precision and Recall
Introduction
Precision and Recall
The F1-Score
The Tradeoff... Again
Not the End
Code with Python
Summary
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Precision and RecallNot the End

Reading time: ~5 min

You now have the main tools for judging a classifier: the confusion matrix, precision, recall and F1. There are more. Doctors also quote specificity: of all the healthy people, how many did the test correctly clear?

At threshold 50,

\text{specificity} = \dfrac{\text{TN}}{\text{TN} + \text{FP}} = \dfrac{181}{181 + 9} \approx

Everything in this chapter also works with more than two groups — say, a test that tells dengue, malaria and typhoid apart. Each group then gets its own precision and recall, worked out as "this group against all the others". Sorting into three or more groups is called classification.

Coming up

Every threshold gave a different confusion matrix. In the next chapter, ROC and AUC, you will draw one curve that shows the test at every threshold at once — and sum it up in a single number.

Speed Round: Read the Matrix

Get five right to move on.

Sina