Indicates that this binary classification model's AUC metric is so high or low that it warrants further examination.
Actions to Consider
- A low AUC indicates that the model doesn’t perform much better than random guessing. Consider improving the model before deploying it.
- A high AUC indicates that the model performs so well that data leakage can be a factor. Investigate and remove any variables that are implicated in data leakage.
Detection Methodology
Einstein Discovery automatically alerts you when it detects an AUC with a value of:
- Below 0.6 (low)
- Above 0.95 (high)