2.215 ALL_MINING_MODEL_ATTRIBUTES

ALL_MINING_MODEL_ATTRIBUTES describes the attributes of the mining models accessible to the current user. Only the attributes in the model signature are included in this view. The attributes in the model signature correspond to the columns in the training data that were used to build the model.

Mining models are schema objects created by Oracle Data Mining.

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(128)

NOT NULL

Owner of the mining model

MODEL_NAME

VARCHAR2(128)

NOT NULL

Name of the mining model

ATTRIBUTE_NAME

VARCHAR2(128)

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

  • TEXT: Unstructured text data

  • PARTITION: The input signature column is used for the partitioning key

  • MIXED: The input signature column takes on more than one attribute type.

    This is due to user-defined embedded transformations that allow an input column to be transformed into multiple independent mining attributes, including mining attributes of different types.

DATA_TYPE

VARCHAR2(106)

Data type of the attribute

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.

ATTRIBUTE_SPEC

VARCHAR2(4000)

One or more keywords that identify special treatment for the attribute during model build. Values are:

  • FORCE_IN: (GLM only) When feature selection is enabled, forces the inclusion of the attribute in the model build. Feature selection is disabled by default. If the model is not using GLM with feature selection enabled, this value is ignored.

  • NOPREP: When ADP is on, prevents automatic transformation of the attribute. If ADP is OFF, this value is ignored.

  • TEXT: Causes the attribute to be treated as unstructured text data. The TEXT value supports three subsettings: POLICY_NAME, MAX_FEATURES, TOKEN_TYPE, and MIN_DOCUMENTS. Subsettings are specified as name:value pairs within parentheses. For example: (POLICY_NAME:mypolicy)(MAX_FEATURES:2000)(TOKEN_TYPE:THEME). See Oracle Data Mining User’s Guide for details.

  • NULL: The ATTRIBUTE_SPEC for this attribute is NULL.

    ATTRIBUTE_SPEC is a parameter to the PL/SQL procedure DBMS_DATA_MINING_TRANSFORM.SET_TRANSFORM. See Oracle Database PL/SQL Packages and Types Reference for details.

See Also:

Oracle Data Mining User’s Guide for more information about the attributes of machine learning models