Home > Model Nodes > Association Node > Classification Node > Edit Classification Build Node > Classification Node Properties > Advanced Settings Overview > Lower Pane of Advanced Sett... > Data Usage Tab
The data usage tab is not supported for Association.
To modify any values, to see which attributes are not used as input, or to see mining types, unselect Auto in the upper pane.
You can change data usage information for several models at the same time, as described in Viewing and Changing Data Usage.
The data usage tab contains the Data Grid. The Data Grid lists all attributes in the data source. For each attribute, the grid lists Data Type, Input, Mining Type, and Auto Prep.
For models that have a target, such as classification and regression models, the target is marked with a red target icon.
Name is the name of the attribute/
Data Type is the Oracle Database data type of the attribute.
Input indicates if the attribute is used to build the model:
The attribute is used to build the model:
The attribute is ignored (not used to build the model)
There are two kinds of reasons for not selecting an attribute as Input:
The attribute has a data type that is not supported by the algorithm used for model build.
For example, Decision Tree and O-Cluster do not support nested data types such as DM_NESTED_NUMERICALS
; if you use an attribute with type DM_NESTED_NUMERICALS
to build a Decision Tree or O-Cluster model, the build fails.
The attribute does not provide data useful for mining. For example, an attribute that has constant or nearly constant values.
If you include attributes of this kind, the model has lower quality than if you exclude them.
To change the input type. click Automatic. Then click the icon and select the new icon.
Mining Type is the logical type of the attribute, either Numerical (numeric data), Categorical (character data), nested numerical, or nested categorical, text or custom text. If the attribute has a type that is not supported for mining, the column is blank. Mining type is indicated by an icon; float the cursor over the icon to see what the icon represents.
To change the mining type, fist click Automatic and then click the type for the attribute. Select a new type from the list. You can change mining types as follows:
Numerical can be changed to Categorical; changing to Categorical casts the numerical value to string
Categorical
Nested Categorical and Nested Numerical cannot be changed.
If Auto Prep is selected, Automatic Data Preparation (ADP) is performed on the attribute. If Auto Prep is not selected, no automatic data preparation is performed for the attribute; in this case, you are required to perform any data preparation, such as normalization, that may be required by the algorithm used to build the model. No data preparation is done (or required) for target attributes. The default is to perform automatic data preparation.