How to assess quality and correctness of classification models? Part 4 – ROC Curve

The ROC curve is one of the methods for visualizing classification quality, which shows the dependency between TPR (True Positive Rate) and FPR (False Positive Rate).

In the previous parts of our tutorial we discussed:

• Basic notation used in assessing classification models
• Quantitative quality indicators
• Confusion Matrix

In this fourth part of the tutorial we will discuss the ROC curve.

What is the ROC curve?

The ROC curve is one of the methods for visualizing classification quality, which shows the dependency between TPR (True Positive Rate) and FPR (False Positive Rate).