[Research on operating characteristics of multiclass receiver in machine learning].

The Receiver Operating Characteristic (ROC) curve has become a standard tool for the analysis and comparison of binary classifiers when the costs of misclassification are unknown. In fact ROC curve has replaced the correct rate or error rate. Extending this to the multiclass case has recently become a growing topic of interest. The conceptions and application of ROC curve are expounded. The history and some algorithms of the multi-class ROC surface are given in detail in this paper. Finally research trends of the multi-class ROC surface are approximating computing and visualization.