Understand TPR, FPR, Precision and Recall Metrics in Machine Learning – Machine Learning Tutorial

By | July 28, 2022

In machine learning, we may see these metrics: TPR, FPR, Precision and Recall metrics. In this tutorial, we will introduce their relation.

If our result is:

confusion matrix in accuracy precision recall and f1-score

Precision and Recall

They are computed as follows:

how to compute accuracy precision recall and f1-score in machine learning

An Introduction to Accuracy, Precision, Recall & F1-Score in Machine Learning – Machine Learning Tutorial

We can understand Precision and Recall as follows:

Recall vs Precision in machine learning

TPR and FPR

TPR  = True Positive Rate

FPR = False Positive Rate

They can be computed as:

TPR = TP / (TP + FN)

FPR = FP / (FP + TN)

They are:

TPR vs FPR in machine learning

Comparing TPR, FPR and Precision, Recall, we can find:

TPR = Recall

FNR = 1-TPR

Leave a Reply

Your email address will not be published. Required fields are marked *