# 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.

In a later Statistics and Machine Learning Lesson of the Day, I will discuss the differences between PPV/NPV and sensitivity/specificity in assessing the predictive accuracy of a binary classifier.

(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.)

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