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Update how-to-machine-learning-interpretability-automl.md
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articles/machine-learning/how-to-machine-learning-interpretability-automl.md

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title: Model interpretability in automated machine learning
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title: Explanability in automated machine learning
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titleSuffix: Azure Machine Learning
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description: Learn how to get explanations for how your automated ML model determines feature importance and makes predictions when using the Azure Machine Learning SDK.
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services: machine-learning
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ms.topic: conceptual
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ms.author: mesameki
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author: mesameki
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ms.reviewer: trbye
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ms.date: 03/11/2020
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---
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# Model interpretability in automated machine learning
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# Interpretability: model explanations in automated machine learning
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[!INCLUDE [applies-to-skus](../../includes/aml-applies-to-basic-enterprise-sku.md)]
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In this article, you learn how to enable the interpretability features for automated machine learning (ML) in Azure Machine Learning. Automated ML helps you understand engineered feature importance.
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In this article, you learn how to get explanations for automated machine learning (ML) in Azure Machine Learning. Automated ML helps you understand engineered feature importance.
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All SDK versions after 1.0.85 set `model_explainability=True` by default. In SDK version 1.0.85 and earlier versions users need to set `model_explainability=True` in the `AutoMLConfig` object in order to use model interpretability.
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