Recall
(RapidMiner Studio Core)
Synopsis
This operator retrieves the specified object from the object store of the process. The objects can be stored in the object store by using the Remember operator.Description
The Recall operator can be used for retrieving the specified object from the object store of the process. The name of the object is specified through the name parameter. The io object parameter specifies the class of the required object. The Recall operator is always used in combination with the operators like the Remember operator. For Recall operator to retrieve an object, first it is necessary that the object should be stored in the object store by using operators like the Remember operator. The name and class of the object are specified when the object is stored using the Remember operator. The same name (in name parameter) and class (in io object parameter) should be specified in the Recall operator to retrieve that object. The same stored object can be retrieved multiple number of times if the remove from store parameter of the Recall operator is not set to true. There is no scoping mechanism in RapidMiner processes therefore objects can be stored (using Remember operator) and retrieved (using Recall operator) at any nesting level. But care should be taken that the execution order of operators is such that the Remember operator for an object always executes before the Recall operator for that object. The combination of these two operators can be used to build complex processes where an input object is used in completely different parts or loops of the processes.
Differentiation
Remember
The Recall operator is always used in combination with the Remember operator. The Remember operators stores the required object into the object store and the Recall operator retrieves the stored object when required.
Output
resultThe specified object is retrieved from the object store of the process and is delivered through this output port.
Parameters
- nameThe name of the required object is specified through this parameter. This name should be the same name that was used while storing the object in an earlier part of the process. Range: string
- io_objectThe class of the required object is selected through this parameter. This class should be the same class that was used while storing the object in an earlier part of the process. Range: selection
- remove_from_storeIf this parameter is set to true, the specified object is removed from the object store after it has been retrieved. In such a case the object can be retrieved just once. If this parameter is set to false, the object remains in the object store even after retrieval. Thus the object can be retrieved multiple number of times (by using the Recall operator multiple number of times). Range: boolean
Tutorial Processes
Introduction to Remember and Recall operators
This process uses the combination of the Remember and Recall operators to display the testing data set of the Split Validation operator. The testing data set is present in the testing subprocess of the Split Validation operator but it is not available outside the Split Validation operator.
The 'Golf'' data set is loaded using the Retrieve operator. The Split Validation operator is applied on it. The test set size parameter is set to 5 and the training set size parameter is set to -1. Thus the test set in the testing subprocess will be composed of 5 examples. The Default Model operator is used in the training subprocess to train a model. The testing data set is available at the tes port of the testing subprocess. The Remember operator is used to store the testing data set into the object store of the process. The Apply Model and Performance operator are applied in the testing subprocess later. In the main process, the Recall operator is used to retrieve the testing data set. The name and io object parameters of the Recall operator are set to 'Testset' and 'ExampleSet' respectively to retrieve the object that was stored by the Remember operator. The output of the Recall operator is connect to the result port of the process. Therefore the testing data set can be seen in the Results Workspace.
