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Area under ROC in Watson OpenScale quality metrics
Last updated: Jun 15, 2023
Area under ROC in Watson OpenScale quality metrics

Area under receiver-operating characteristic curve (ROC) gives the area under recall and false positive rate curve in Watson OpenScale. It calculates the sensitivity against the fallout rate.

Area under ROC at a glance

  • Description: Area under recall and false positive rate 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

The Area under ROC is plotted parametrically as the True positive rate versus the False positive rate withe respect to a threshold T.

Learn more

Reviewing quality results

Parent topic: Quality metrics overview