In estimating the accuracy of data mining (or other) classification models, the true positive rate is
A) the ratio of correctly classified positives divided by the total positive count.
B) the ratio of correctly classified negatives divided by the total negative count.
C) the ratio of correctly classified positives divided by the sum of correctly classified positives and incorrectly classified positives.
D) the ratio of correctly classified positives divided by the sum of correctly classified positives and incorrectly classified negatives.

Question

Quizplus · Accepted Answer

The true positive rate, also known as sensitivity or recall, is defined as the ratio of correctly classified positive instances (true positives) divided by the total actual positive instances in the dataset. This measures the model's ability to correctly identify all relevant instances.

In Estimating the Accuracy of Data Mining (Or Other) Classification