Model attributes are numerical, categorical, or unstructured (text). Data attributes, which are columns in a case table, have Oracle data types, as described in "Column Data Types".
Numerical attributes can theoretically have an infinite number of values. The values have an implicit order, and the differences between them are also ordered. Oracle Data Mining interprets NUMBER, FLOAT, BINARY_DOUBLE, BINARY_FLOAT, DM_NESTED_NUMERICALS, DM_NESTED_BINARY_DOUBLES, and DM_NESTED_BINARY_FLOATS as numerical.
Categorical attributes have values that identify a finite number of discrete categories or classes. There is no implicit order associated with the values. Some categoricals are binary: they have only two possible values, such as yes or no, or male or female. Other categoricals are multi-class: they have more than two values, such as small, medium, and large.
Oracle Data Mining interprets CHAR and VARCHAR2 as categorical by default, however these columns may also be identified as columns of unstructured data (text). Oracle Data Mining interprets columns of DM_NESTED_CATEGORICALS as categorical. Columns of CLOB, BLOB, and BFILE always contain unstructured data. For information about mining unstructured data, see Mining Unstructured Text.
The target of a classification model is categorical. (If the target of a classification model is numeric, it is interpreted as categorical.) The target of a regression model is numerical. The target of an attribute importance model is either categorical or numerical.