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Data to Weights (RapidMiner Studio Core)


This operator simply generates an attribute weights vector with weight 1.0 for each input attribute.


The Data to Weights operator creates a new attribute weights IOObject from the given ExampleSet. The result is a vector of attribute weights containing the weight 1.0 for each attribute of the input ExampleSet.


  • example set (Data Table)

    This input port expects an ExampleSet. It is output of the Retrieve operator in the attached Example Process.


  • weights (Attribute Weights)

    This port delivers the weights of the attributes with respect to the label attribute.

  • example set (Data Table)

    The ExampleSet that was given as input is passed without changing to the output through this port. This is usually used to reuse the same ExampleSet in further operators or to view the ExampleSet in the Results Workspace.


  • normalize_weightsThis parameter indicates if the calculated weights should be normalized or not. If set to true, all weights are normalized in range from 0 to 1. Range: boolean
  • sort_weightsThis parameter indicates if the attributes should be sorted according to their weights in the results. If this parameter is set to true, the order of the sorting is specified using the sort direction parameter. Range: boolean
  • sort_directionThis parameter is only available when the sort weights parameter is set to true. This parameter specifies the sorting order of the attributes according to their weights. Range: selection

Tutorial Processes

Generating a weight vector with weight 1.0 for all the attributes

The 'Golf' data set is loaded using the Retrieve operator. The Data to Weights operator is applied on it to generate the weights of the attributes. All parameters are used with default values. The normalize weights parameter is set to true, the sort weights parameter is set to true and the sort direction parameter is set to 'ascending'. Run the process and see the results of this process in the Results Workspace. You can see that all attributes have been assigned to weight 1.0.