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In QuickSight, ML-powered anomaly detection identifies the causations and correlations to enable you to make data-driven decisions. You still have control over defining how you want the job to work on your data. You can specify your own parameters, and choose additional options, such as identifying key drivers in a contribution analysis. Or you can use the default settings.
You can also refer to Adding an ML insight to detect outliers and key drivers - https://docs.aws.amazon.com/quicksight/latest/user/anomaly-detection-adding-anomaly-insights.html
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