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Merge pull request #150 from peytonfraser/patch-2
Update best-practices.md for OOS recipe
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articles/ai-services/language-service/conversational-language-understanding/concepts/best-practices.md

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@@ -243,15 +243,15 @@ curl --request POST \
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## Address out-of-domain utterances
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Customers can use the new recipe version `2024-06-01-preview` if the model has poor AIQ on out-of-domain utterances. An example of this scenario with the default recipe can be like the following example where the model has three intents: `Sports`, `QueryWeather`, and `Alarm`. The test utterances are out-of-domain utterances and the model classifies them as `InDomain` with a relatively high confidence score.
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Customers can use the newly updated recipe version `2024-08-01-preview` (previously `2024-06-01-preview`) if the model has poor AIQ on out-of-domain utterances. An example of this scenario with the default recipe can be like the following example where the model has three intents: `Sports`, `QueryWeather`, and `Alarm`. The test utterances are out-of-domain utterances and the model classifies them as `InDomain` with a relatively high confidence score.
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| Text | Predicted intent | Confidence score |
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|----|----|----|
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| "Who built the Eiffel Tower?" | `Sports` | 0.90 |
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| "Do I look good to you today?" | `QueryWeather` | 1.00 |
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| "I hope you have a good evening." | `Alarm` | 0.80 |
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To address this scenario, use the `2024-06-01-preview` configuration version that's built specifically to address this issue while also maintaining reasonably good quality on `InDomain` utterances.
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To address this scenario, use the `2024-08-01-preview` configuration version that's built specifically to address this issue while also maintaining reasonably good quality on `InDomain` utterances.
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```console
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curl --location 'https://<your-resource>.cognitiveservices.azure.com/language/authoring/analyze-conversations/projects/<your-project>/:train?api-version=2022-10-01-preview' \
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--data '{
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      "modelLabel": "<modelLabel>",
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      "trainingMode": "advanced",
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      "trainingConfigVersion": "2024-06-01-preview",
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      "trainingConfigVersion": "2024-08-01-preview",
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      "evaluationOptions": {
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            "kind": "percentage",
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            "testingSplitPercentage": 0,

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