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Merge pull request #210475 from cnabay/patch-1
Update for new transformer, non-stationarity detection.
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articles/machine-learning/how-to-auto-train-forecast.md

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@@ -148,6 +148,7 @@ However, the following steps are performed only for `forecasting` task types:
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* Create features based on time series identifiers to enable fixed effects across different series
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* Create time-based features to assist in learning seasonal patterns
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* Encode categorical variables to numeric quantities
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* Detect the non-stationary time series and automatically differencing them to mitigate the impact of unit roots.
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To view the full list of possible engineered features generated from time series data, see [TimeIndexFeaturizer Class](/python/api/azureml-automl-runtime/azureml.automl.runtime.featurizer.transformer.timeseries.time_index_featurizer).
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