What is the difference between precision and recall?<br /> A. 1. Precision measures the accuracy of positive predictions, while recall measures the ability to capture all positive instances <br />B. 2. Precision is the ratio of true positives to true negatives, while recall is the ratio of false positives to false negatives <br />C. 3. Precision and recall are synonymous and used interchangeably <br />D. 4. Precision focuses on false positives, while recall focuses on false negatives
Question
What is the difference between precision and recall?<br /> A. 1. Precision measures the accuracy of positive predictions, while recall measures the ability to capture all positive instances <br />B. 2. Precision is the ratio of true positives to true negatives, while recall is the ratio of false positives to false negatives <br />C. 3. Precision and recall are synonymous and used interchangeably <br />D. 4. Precision focuses on false positives, while recall focuses on false negatives
Solution
The correct answer is A. Precision measures the accuracy of positive predictions, while recall measures the ability to capture all positive instances.
Precision is the ratio of correctly predicted positive observations to the total predicted positive observations. High precision relates to the low false positive rate.
On the other hand, recall (Sensitivity) - the ratio of correctly predicted positive observations to the all observations in actual class. High recall relates to the low false negative rate.
So, Precision is about being precise. Even if you managed to capture only one positive, and there are no false positives, it's totally fine.
On the other hand, Recall is not about being precise - it's about capturing the most positive instances. It doesn't matter if you collect a lot of negatives.
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