Generate Nominal Data (RapidMiner Studio Core)

Synopsis

This operator generates an ExampleSet based on nominal attributes. The number of examples, number of attributes, and number of values can be specified by the user.

Description

The Generate Nominal Data operator generates an ExampleSet with the specified number of nominal attributes which is controlled by the number of attributes parameter. Please note that in addition to the specified number of regular attributes, the label attribute is automatically generated. The label attribute generated by this operator has only two possible values i.e. positive and negative. This operator is used for generating a random ExampleSet for testing purposes.

Output

  • output (IOObject)

    The Generate Nominal Data operator generates an ExampleSet based on nominal attributes which is delivered through this port. The meta data is also delivered along with the data.This output is the same as the output of the Retrieve operator.

Parameters

  • number_examplesThis parameter specifies the number of examples to be generated. Range: integer
  • number_of_attributesThis parameter specifies the number of regular attributes to be generated. Please note that the label attribute is generated automatically besides these regular attributes. Range: integer
  • number_of_valuesThis parameter specifies the number of unique values of the attributes. Range: integer
  • use_local_random_seedThis parameter indicates if a local random seed should be used for randomization. Using the same value of local random seed will produce the same ExampleSet. Changing the value of this parameter changes the way examples are randomized, thus the ExampleSet will have a different set of values. Range: boolean
  • local_random_seedThis parameter specifies the local random seed. This parameter is only available if the use local random seed parameter is set to true. Range: integer

Tutorial Processes

Introduction to the Generate Nominal Data operator

The Generate Nominal Data operator is applied for generating an ExampleSet. The number examples parameter is set to 100, thus the ExampleSet will have 100 examples. The number of attributes parameter is set to 3, thus three nominal attributes will be generated beside the label attribute. The number of values parameter is set to 5, thus each attribute will have 5 possible values. You can verify this by viewing the results in the Results Workspace. The use local random seed parameter is set to false in this Example process. Set the use local random seed parameter to true and run the process with different values of local random seed. You will see that changing the values of local random seed changes the randomization.