Final answer:
True Positive Rate (TPR) and Recall are related in binary classification. They have the same equation: TPR = Recall = True Positives / (True Positives + False Negatives).
Step-by-step explanation:
True Positive Rate (TPR) and Recall are related in the context of binary classification.
The True Positive Rate, also known as sensitivity, is the ratio of correctly predicted positive instances to the total actual positive instances. It is defined as:
TPR = True Positives / (True Positives + False Negatives)
Recall, on the other hand, measures the ability of a model to identify all the relevant instances. It is also defined as the ratio of true positives to the sum of true positives and false negatives:
Recall = True Positives / (True Positives + False Negatives)
Hence, we can see that TPR and Recall are the same, and the equation for both is:
TPR = Recall = True Positives / (True Positives + False Negatives)