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Data Transformation - Scale and Reduce


Support for Machine Learning Studio (classic) will end on 31 August 2024. We recommend you transition to Azure Machine Learning by that date.

Beginning 1 December 2021, you will not be able to create new Machine Learning Studio (classic) resources. Through 31 August 2024, you can continue to use the existing Machine Learning Studio (classic) resources.

ML Studio (classic) documentation is being retired and may not be updated in the future.

This article describes the modules in Machine Learning Studio (classic) that can help you work with numerical data. For machine learning, common data tasks include clipping, binning, and normalizing numerical values. Other modules support dimensionality reduction.


Applies to: Machine Learning Studio (classic) only

Similar drag-and-drop modules are available in Azure Machine Learning designer.

Modeling numerical data

Tasks such as normalizing, binning, or redistributing numerical variables are an important part of data preparation for machine learning. The modules in this group support the following data preparation tasks:

  • Grouping data into bins of varying sizes or distributions.
  • Removing outliers or changing their values.
  • Normalizing a set of numeric values into a specific range.
  • Creating a compact set of feature columns from a high-dimension dataset.

List of modules

This Data Transformation - Scale and Reduce category includes the following modules:

See also