Synopsis
This operator can be used to change the attribute role (regular, special, label, id...).
Description
This operator can be used to change the role of an attribute of the input ExampleSet. If you want to change the attribute name you should use the
Rename operator.
The target role indicates if the attribute is a regular attribute (used by learning operators) or a special attribute (e.g. a label or id attribute). The following target attribute types are possible:
- regular: only regular attributes are used as input variables for learning tasks
- id: the id attribute for the example set
- label: target attribute for learning
- prediction: predicted attribute, i.e. the predictions of a learning scheme
- cluster: indicates the membership to a cluster
- weight: indicates the weight of the example
- batch: indicates the membership to an example batch
Users can also define own attribute types by simply using the desired name.
Please be aware that roles have to be unique! Assigning a non regular role the second time will cause the first attribute to be dropped from the example set. If you want to keep this attribute, you have to change it's role first.
Input
- example set input: expects: ExampleSetMetaData: #examples: = 0; #attributes: 0
, expects: ExampleSet
Output
- example set output:
- original:
Parameters
- name: The name of the attribute whose role should be changed.
- target role: The target role of the attribute (only changed if parameter change_attribute_type is true).