Generate Direct Mailing Data (RapidMiner Studio Core)

Synopsis

This operator generates an ExampleSet that represents direct mailing data. The number of examples can be specified by the user.

Description

The Generate Direct Mailing Data operator generates an ExampleSet that represents direct mailing data. This ExampleSet can be used when you do not have a data set that represents a real direct mailing data. This ExampleSet can be used as a placeholder for such a requirement. This data set has 8 regular attributes and 1 special attribute. The regular attributes are name (nominal), age (integer), lifestyle (nominal), zip code (integer), family status (nominal), car (nominal), sports (nominal) and earnings (integer). The special attribute is label (nominal). The number of examples in the data set can be set by the number examples parameter. To have a look at this ExampleSet, just run the attached Example Process.

Output

output (Data Table)
The Generate Direct Mailing Data operator generates an ExampleSet which is delivered through this port. The meta data is also delivered along with the data.This output is same as the output of the Retrieve operator.

Parameters

number_examplesThis parameter specifies the number of examples to be generated. 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 Direct Mailing Data operator

The Generate Direct Mailing Data operator is applied for generating an ExampleSet that represents direct mailing data. The number examples parameter is set to 10000, thus the ExampleSet will have 10000 examples. You can see the ExampleSet 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.