True positive rate in Watson OpenScale quality metrics

The true positive rate (TPR) gives the proportion of correct predictions in predictions of positive classes in Watson OpenScale.

True positive rate at a glance

Description: Proportion of correct predictions in predictions of positive class
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 True positive rate is calculated by the following formula:

                  number of true positives
TPR =  _________________________________________________________

        (number of true positives + number of false negatives)

Learn more

Reviewing quality results

Parent topic: Quality metrics overview