Shuffle
(AI Studio Core)
Synopsis
This operator creates a new, shuffled ExampleSet from the given ExampleSet by making a new copy of the given ExampleSet in the main memory.Description
The Shuffle operator creates a new, shuffled ExampleSet by making a new copy of the given ExampleSet in the main memory. Please note that the system may run out of memory, if the ExampleSet is too large. The local random seed parameter can be used for randomizing the shuffling process.
Input
example set input (Data table)This input port expects an ExampleSet. It is output of the Retrieve operator in the attached Example Process.
Output
- example set output (Data table)
The shuffled ExampleSet is output of this port.
- original (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
- use_local_random_seedThis parameter indicates if a local random seed should be used for randomization. Using the same value of the local random seed will produce the same randomization. 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
Shuffling the Iris data set
The 'Iris' data set is loaded using the Retrieve operator. A breakpoint is inserted here so that you can have a look at the ExampleSet. You can see that the ExampleSet has an id attribute. The ExampleSet is sorted in ascending order of this attribute. The Shuffle operator is applied on this ExampleSet to randomize the order of its examples. The resultant shuffled ExampleSet can be seen in the Results Workspace.
