Machine Learning and Applied Statistics Lesson of the Day – Positive Predictive Value and Negative Predictive Value
August 7, 2014 Leave a comment
For a binary classifier,
- its positive predictive value (PPV) is the proportion of positively classified cases that were truly positive.
- its negative predictive value (NPV) is the proportion of negatively classified cases that were truly negative.
(Recall that sensitivity and specificity can also be used to evaluate the performance of a binary classifier. Based on those 2 statistics, we can construct receiver operating characteristic (ROC) curves to assess the predictive accuracy of the classifier, and a minimum standard for a good ROC curve is being better than the line of no discrimination.)