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

E17209-15
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FEATURE_SET

Syntax

feature_set::=

Description of feature_set.gif follows
Description of the illustration feature_set.gif

Analytic Syntax

feature_set_analytic::=

Description of feature_set_analytic.gif follows
Description of the illustration feature_set_analytic.gif

mining_attribute_clause::=

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

mining_analytic_clause::=

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

Purpose

FEATURE_SET returns a set of feature ID and feature value pairs for each row in the selection. The return value is a varray of objects with field names FEATURE_ID and VALUE. The data type of both fields is NUMBER.

topN and cutoff

You can use topN and cutoff to specify the number of features returned by the function. Both topN and cutoff are positive integers.

To return the N features that are greater than or equal to cutoff, specify both topN and cutoff.

Syntax Choice

FEATURE_SET 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

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.

Example

This example lists the top features corresponding to a given customer record and determines the top attributes for each feature (based on coefficient > 0.25).

WITH
feat_tab AS (
SELECT F.feature_id fid,
       A.attribute_name attr,
       TO_CHAR(A.attribute_value) val,
       A.coefficient coeff
  FROM TABLE(DBMS_DATA_MINING.GET_MODEL_DETAILS_NMF('nmf_sh_sample')) F,
       TABLE(F.attribute_set) A
 WHERE A.coefficient > 0.25
),
feat AS (
SELECT fid,
       CAST(COLLECT(Featattr(attr, val, coeff))
         AS Featattrs) f_attrs
  FROM feat_tab
GROUP BY fid
),
cust_10_features AS (
SELECT T.cust_id, S.feature_id, S.value
  FROM (SELECT cust_id, FEATURE_SET(nmf_sh_sample, 10 USING *) pset
          FROM nmf_sh_sample_apply_prepared
         WHERE cust_id = 100002) T,
       TABLE(T.pset) S
)
SELECT A.value, A.feature_id fid,
       B.attr, B.val, B.coeff
  FROM cust_10_features A,
       (SELECT T.fid, F.*
          FROM feat T,
               TABLE(T.f_attrs) F) B
 WHERE A.feature_id = B.fid
ORDER BY A.value DESC, A.feature_id ASC, coeff DESC, attr ASC, val ASC;

   VALUE  FID ATTR                      VAL                        COEFF
-------- ---- ------------------------- ------------------------ -------
  6.8409    7 YRS_RESIDENCE                                       1.3879
  6.8409    7 BOOKKEEPING_APPLICATION                              .4388
  6.8409    7 CUST_GENDER               M                          .2956
  6.8409    7 COUNTRY_NAME              United States of America   .2848
  6.4975    3 YRS_RESIDENCE                                       1.2668
  6.4975    3 BOOKKEEPING_APPLICATION                              .3465
  6.4975    3 COUNTRY_NAME              United States of America   .2927
  6.4886    2 YRS_RESIDENCE                                       1.3285
  6.4886    2 CUST_GENDER               M                          .2819
  6.4886    2 PRINTER_SUPPLIES                                     .2704
  6.3953    4 YRS_RESIDENCE                                       1.2931
  5.9640    6 YRS_RESIDENCE                                       1.1585
  5.9640    6 HOME_THEATER_PACKAGE                                 .2576
  5.2424    5 YRS_RESIDENCE                                       1.0067
  2.4714    8 YRS_RESIDENCE                                        .3297
  2.3559    1 YRS_RESIDENCE                                        .2768
  2.3559    1 FLAT_PANEL_MONITOR                                   .2593