Time series forecasting AutoML Automatic featurization groupby specific column values

Marcrb 1 Reputation point

I'm training time-series forecasting models with Azure AutoML.

As far as I’m concerned, featurization techniques such as Normalization and Scaling or Impute missing values, are applied by columns.

Given that I’m dealing with time-series data, is there a way to apply these kinds of featurization using a group by some column values? Otherwise, I feel the transformations applied make no sense at all.

For instance, If I want to predict product demand from different stores, would be possible to impute missing values from one article given the median of that article (not the one of the column) modifying AutoML Automatic featurization? Or standardize the target values for each article separately?

Thanks in Advance.

Azure Machine Learning
Azure Machine Learning
An Azure machine learning service for building and deploying models.
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  1. Ramr-msft 17,621 Reputation points

    @Marcrb Thanks for the question. "featurization": 'FeaturizationConfig' Indicates customized featurization step should be used. Learn how to customize featurization.
    Here is link to Currently Supported customization.

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