ROC curve with classification problems

1. How the ROC curve is used in classification algorithms?
2. Is ROC curve only for classification?
3. How do you find the ROC curve for multiclass classification?

How the ROC curve is used in classification algorithms?

The receiver operating characteristic (ROC) curve is frequently used for evaluating the performance of binary classification algorithms. It provides a graphical representation of a classifier's performance, rather than a single value like most other metrics.

Is ROC curve only for classification?

The ROC curve is only defined for binary classification problems. However, there is a way to integrate it into multi-class classification problems. To do so, if we have N classes then we will need to define several models.

How do you find the ROC curve for multiclass classification?

For multiclass problems, ROC curves can be plotted with the methodology of using one class versus the rest. Use this one-versus-rest for each class and you will have the same number of curves as classes. The AUC score can also be calculated for each class individually.