Skip to main content

Module

Monitoring adaptive models

3 Rubriques

40 mins

Visible to: All users
Débutant Pega Customer Decision Hub 8.8 Anglais

Data scientists must regularly inspect the health of the out-of-the-box Pega Customer Decision Hub™ predictions and the adaptive models that drive them, and share their findings with the business team. The predictive performance and success rate of individual adaptive models provide information that can help business users and decisioning architects to refine business processes. Learn how to monitor the performance of predictions, adaptive models, and predictors.

Après avoir terminé ce module, vous pourrez :

Describe the lift metrics of a prediction
Name the key metrics of adaptive models visualized in the bubble chart.
Inspect individual active and inactive predictors.
Explain how predictors with similar predictive performance are grouped.
Examine the propensity distribution and the trend for the whole model.

Appliquez ce que vous avez appris dans les Défis suivants :

Monitoring predictions v5 Monitoring adaptive models v4

Disponible dans la mission suivante :

AI for 1:1 Customer Engagement v2

We'd prefer it if you saw us at our best.

Pega Academy has detected you are using a browser which may prevent you from experiencing the site as intended. To improve your experience, please update your browser.

Close Deprecation Notice