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articles/cognitive-services/personalizer/concept-active-inactive-events.md

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## Typical active events scenario
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When your application calls the Rank API, you receive the action which the application should show in the **rewardActionId** field. From that moment, Personalizer expects a Reward call with a reward score that has the same eventId. The reward score is used to train the model for future Rank calls. If no Reward call is received for the eventId, a default reward is applied. [Default rewards](how-to-settings.md#configure-rewards-for-the-feedback-loop-based-on-use-case) are set on your Personalizer resource in the Azure portal.
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When your application calls the Rank API, you receive the action which the application should show in the **rewardActionId** field. From that moment, Personalizer expects a Reward call with a reward score that has the same eventId. The reward score is used to train the model for future Rank calls. If no Reward call is received for the eventId, a default reward is applied. [Default rewards](how-to-settings.md#configure-rewards-for-the-feedback-loop) are set on your Personalizer resource in the Azure portal.
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## Other event type scenarios
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articles/cognitive-services/personalizer/concept-active-learning.md

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Learning settings determine the *hyperparameters* of the model training. Two models of the same data that are trained on different learning settings will end up different.
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[Learning policy and settings](how-to-settings.md#configure-rewards-for-the-feedback-loop-based-on-use-case) are set on your Personalizer resource in the Azure portal.
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[Learning policy and settings](how-to-settings.md#configure-rewards-for-the-feedback-loop) are set on your Personalizer resource in the Azure portal.
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### Import and export learning policies
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