Understanding ROC curves

This graphic helps you understand behavior of ROC curve. Positives and negatives are two sets of outcomes for a binary test. The blue curve shows distribution of negatives and the red curve shows distribution of positives. This distribution is obtained from the result of a classifier which estimates the probability of a test point being positive.

The key point to note is the area under curve (AUC) is the highest when the two curves are farthest with little overlap.

Adjust mean of negatives using slider. You can also drag the threshold line in the graph below.