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Weight by SVM (RapidMiner Studio Core)

Synopsis

This operator calculates the relevance of the attributes by computing for each attribute of the input ExampleSet the weight with respect to the class attribute. The coefficients of a hyperplane calculated by an SVM (Support Vector Machine) are set as attribute weights.

Description

The Weight by SVM operator uses the coefficients of the normal vector of a linear SVM as attribute weights. In contrast to most of the SVM based operators available in RapidMiner, this operator works for multiple classes too. Please note that the attribute values still have to be numerical. This operator can be applied only on ExampleSets with numerical label. Please use appropriate preprocessing operators (type conversion operators) in order to ensure this. For more information about SVM please study the documentation of the SVM operator.

Input

  • example set (Data Table)

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

Output

  • weights

    This port delivers the weights of the attributes with respect to the label attribute. The attributes with higher weight are considered more relevant.

  • 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.

Parameters

  • normalize_weightsThis parameter indicates if the calculated weights should be normalized or not. If set to true, all weights are normalized in the 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 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
  • CThis parameter specifies the SVM complexity weighting factor. Range: real

Tutorial Processes

Calculating the weights of the attributes of the Polynomial data set

The 'Polynomial' data set is loaded using the Retrieve operator. The Weight by SVM operator is applied on it to calculate the weights of the attributes. All parameters are used with default values. The normalize weights parameter is set to true, thus all the weights will be normalized in the range 0 to 1. The sort weights parameter is set to true and the sort direction parameter is set to 'ascending', thus the results will be in ascending order of the weights. You can verify this by viewing the results of this process in the Results Workspace.