> EVEN in the extreme that you're right more often than you're wrong if you make that assumption. And this is actually the rational thing to do. Reason: There

> EVEN in the extreme that you're right more often than you're wrong if you make that assumption. And this is actually the rational thing to do. Reason: There are two potential errors involved here: labeling an innocent person a criminal (false positive) and labeling a criminal as innocent (false negative). The key is to realize that the cost of these two errors is not the same. For instance, treating an innocent person as a criminal could be much more expensive for the person and society than not detecting a criminal with a given classifier. For that very reason, we have the presumption of innocence as a principle in law. As a consequence, you don't want to select a classifier based on just the rate of errors overall, but you want to incorporate some kind of loss function that minimizes the cost for individuals and society. Under that loss function, the best classifier may actually be wrong more often than some other classifier.