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Oracle® Database SQL Language Reference
12c Release 1 (12.1)

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Description of feature_id.gif follows
Description of the illustration feature_id.gif

Analytic Syntax


Description of feature_id_analytic.gif follows
Description of the illustration feature_id_analytic.gif


Description of mining_attribute_clause.gif follows
Description of the illustration mining_attribute_clause.gif


Description of mining_analytic_clause.gif follows
Description of the illustration mining_analytic_clause.gif

See Also:

"Analytic Functions" for information on the syntax, semantics, and restrictions of mining_analytic_clause


FEATURE_ID returns the identifier of the highest value feature for each row in the selection. The feature identifier is returned as an Oracle NUMBER.

Syntax Choice

FEATURE_ID can score the data in one of two ways: It can apply a mining model object to the data, or it can dynamically mine the data by executing an analytic clause that builds and applies one or more transient mining models. Choose Syntax or Analytic Syntax:


mining_attribute_clause identifies the column attributes to use as predictors for scoring. When the function is invoked with the analytic syntax, these predictors are also used for building the transient models. The mining_attribute_clause behaves as described for the PREDICTION function. (See "mining_attribute_clause::=".)

See Also:

About the Example:

The following example is excerpted from the Data Mining sample programs. For more information about the sample programs, see Appendix A in Oracle Data Mining User's Guide.


This example lists the features and corresponding count of customers in a data set.

SELECT FEATURE_ID(nmf_sh_sample USING *) AS feat, COUNT(*) AS cnt
  FROM nmf_sh_sample_apply_prepared
  GROUP BY FEATURE_ID(nmf_sh_sample USING *)
  ORDER BY cnt DESC, feat DESC;

      FEAT        CNT
---------- ----------
         7       1443
         2         49
         3          6
         6          1
         1          1