Are we happy with Anomaly Detection metrics?

Right now it has two properties.
AUC and DetectionRateAtKFalsePosititives.
We describe `DetectionRateAtKFalsePosititives`
as:
```
/// This is computed as follows:
/// 1.Sort the test examples by the output of the anomaly detector in descending order of scores.
/// 2.Among the top K False Positives, compute ratio : (True Positive @ K) / (Total anomalies in test data)
/// Example confusion matrix for anomaly detection:
/// Anomalies (in test data) | Non-Anomalies (in test data)
/// Predicted Anomalies : TP | FP
/// Predicted Non-Anomalies : FN | TN
```
and we expose nothing of that.
No True positive, no total anomalies, no K which user need to save somewhere else.

Should we expand this metrics right now or wait till v1.0 release?