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Weighted True Positive Rate in Watson OpenScale quality metrics
Last updated: Jun 15, 2023
Weighted True Positive Rate in Watson OpenScale quality metrics

The weighted true positive rate gives the weighted mean of the class true positive rate (TPR) with weights equal to class probability in Watson OpenScale.

Weighted True Positive Rate (wTPR) at a glance

  • Description: Weighted mean of class TPR with weights equal to class probability

  • 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: Multiclass classification

  • Chart values: Last value in the timeframe

  • Metrics details available: Confusion matrix

Do the math

The True positive rate is calculated by the following formula:

                  number of true positives
TPR =  _________________________________________________________

        number of true positives + number of false negatives

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Reviewing quality results

Parent topic: Quality metrics overview

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