ALL_MINING_MODEL_ATTRIBUTES

ALL_MINING_MODEL_ATTRIBUTES describes the attributes of the mining models accessible to the current user.

Attributes correspond to the columns of data used to build a model. Columns with the same names and data types should be available in any data set to which the model is applied.

Related Views

DBA_MINING_MODEL_ATTRIBUTES describes the attributes of all mining models in the database.
USER_MINING_MODEL_ATTRIBUTES describes the attributes of the mining models owned by the current user. This view does not display the OWNER column.

Column	Datatype	NULL	Description
`OWNER`	`VARCHAR2(30)`	`NOT NULL`	Owner of the mining model
`MODEL_NAME`	`VARCHAR2(30)`	`NOT NULL`	Name of the mining model
`ATTRIBUTE_NAME`	`VARCHAR2(30)`	`NOT NULL`	Name of the attribute
`ATTRIBUTE_TYPE`	`VARCHAR2(11)`		Logical type of the attribute. The type is identified during the model build or apply process: `NUMERICAL` - Numeric data `CATEGORICAL` - Character data
`DATA_TYPE`	`VARCHAR2(12)`		Data type of the attribute: `VARCHAR2` `NUMBER` `FLOAT` `CHAR` `NESTED TABLE`
`DATA_LENGTH`	`NUMBER`		Length of the data type
`DATA_PRECISION`	`NUMBER`		Precision of a fixed point number. Precision, which is the total number of significant decimal digits, is represented as p in the data type `NUMBER(p,s)`.
`DATA_SCALE`	`NUMBER`		Scale of a fixed point number. Scale, which is the number of digits from the decimal to the least significant digit, is represented as s in the data type `NUMBER(p,s)`.
`USAGE_TYPE`	`VARCHAR2(8)`		Indicates whether the attribute was used to construct the model (`ACTIVE`) or not (`INACTIVE`). Some attributes may be eliminated by transformations or algorithmic processing. The `*_MINING_MODEL_ATTRIBUTES` view only lists the attributes used by the model, therefore the value of this column is always `ACTIVE`.
`TARGET`	`VARCHAR2(3)`		Indicates whether the attribute is the target of a predictive model (`YES`) or not (`NO`). The target describes the result that is produced when the model is applied.