#22 Machine Learning & Data Science Challenge 22

#22 Machine Learning & Data Science Challenge 22

What is False Positive Rate & False-negative Rate?

False Positive Rate:

  • The false positive rate (FPR) is calculated as the number of incorrect positive predictions divided by the total number of negatives.

  • The best false positive rate is 0.0, whereas the worst is 1.0. It can also be calculated as 1 – specificity.

$$SN = TP / TP*FN = TP / P$$

False Negative Rate:

  • The false negative rate (FPR) is calculated as the number of incorrect positive predictions divided by the total number of positives.

  • The best false negative rate is 0.0, whereas the worst is 1.0.