Area under PR in Watson OpenScale quality metrics

Last updated: Jun 15, 2023

Area under Precision Recall gives the area under the precision and recall curve in Watson OpenScale, which can be useful when classes are particularly imbalanced.

Area under PR at a glance

Description: Area under precision and recall curve
Default thresholds: Lower limit = 80%
Default recommendation:
- Upward trend: An upward trend indicates that the metric is improving. This means that model retraining is effective.
- Downward trend: A downward trend indicates that the metric is deteriorating. Feedback data is becoming significantly different than the training data.
- Erratic or irregular variation: An erratic or irregular variation indicates that the feedback data is not consistent between evaluations. Increase the minimum sample size for the Quality monitor.
Problem type: Binary classification
Chart values: Last value in the timeframe
Metrics details available: Confusion matrix

Do the math

Area under Precision Recall gives the total for both Precision + Recall.

       n
AveP = ∑ P(k)∆r(k)
      k=1

Precision (P) is defined as the number of true positives (Tp) over the number of true positives plus the number of false positives (Fp).

               number of true positives
Precision =   ______________________________________________________

              (number of true positives + number of false positives)

Recall (R) is defined as the number of true positives (Tp) over the number of true positives plus the number of false negatives (Fn).

            number of true positives
Recall =   ______________________________________________________

           (number of true positives + number of false negatives)