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

E17209-15
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CLUSTER_ID

Syntax

cluster_id::=

Description of cluster_id.gif follows
Description of the illustration cluster_id.gif

Analytic Syntax

cluster_id_analytic::=

Description of cluster_id_analytic.gif follows
Description of the illustration cluster_id_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

CLUSTER_ID returns the identifier of the highest probability cluster for each row in the selection. The cluster identifier is returned as an Oracle NUMBER.

Syntax Choice

CLUSTER_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

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 Examples:

The following examples are 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

The following example lists the clusters into which the customers in mining_data_apply_v have been grouped.

SELECT CLUSTER_ID(km_sh_clus_sample USING *) AS clus, COUNT(*) AS cnt 
  FROM mining_data_apply_v
  GROUP BY CLUSTER_ID(km_sh_clus_sample USING *)
  ORDER BY cnt DESC;

      CLUS        CNT
---------- ----------
         2        580
        10        216
         6        186
         8        115
        19        110
        12        101
        18         81
        16         39
        17         38
        14         34

Analytic Example

This example divides the customer database into four segments based on common characteristics. The clustering functions compute the clusters and return the score without a predefined clustering model.

SELECT * FROM (
     SELECT cust_id,
          CLUSTER_ID(INTO 4 USING *) OVER () cls,
          CLUSTER_DETAILS(INTO 4 USING *) OVER () cls_details
     FROM mining_data_apply_v)
WHERE cust_id <= 100003
ORDER BY 1; 
 
CUST_ID CLS CLS_DETAILS
------- --- -----------------------------------------------------------------------------
 100001   5 <Details algorithm="K-Means Clustering" cluster="5">
            <Attribute name="FLAT_PANEL_MONITOR" actualValue="0" weight=".349" rank="1"/>
            <Attribute name="BULK_PACK_DISKETTES" actualValue="0" weight=".33" rank="2"/>
            <Attribute name="CUST_INCOME_LEVEL" actualValue="G: 130\,000 - 149\,999"
               weight=".291" rank="3"/>
            <Attribute name="HOME_THEATER_PACKAGE" actualValue="1" weight=".268" rank="4"/>
            <Attribute name="Y_BOX_GAMES" actualValue="0" weight=".179" rank="5"/>
            </Details>

 100002   6 <Details algorithm="K-Means Clustering" cluster="6">
            <Attribute name="CUST_GENDER" actualValue="F" weight=".945" rank="1"/>
            <Attribute name="CUST_MARITAL_STATUS" actualValue="NeverM" weight=".856" rank="2"/>
            <Attribute name="HOUSEHOLD_SIZE" actualValue="2" weight=".468" rank="3"/>
            <Attribute name="AFFINITY_CARD" actualValue="0" weight=".012" rank="4"/>
            <Attribute name="CUST_INCOME_LEVEL" actualValue="L: 300\,000 and above" 
               weight=".009" rank="5"/>
            </Details>
 
 100003   7 <Details algorithm="K-Means Clustering" cluster="7">
            <Attribute name="CUST_MARITAL_STATUS" actualValue="NeverM" weight=".862" rank="1"/>
            <Attribute name="HOUSEHOLD_SIZE" actualValue="2" weight=".423" rank="2"/>
            <Attribute name="HOME_THEATER_PACKAGE" actualValue="0" weight=".113" rank="3"/>
            <Attribute name="AFFINITY_CARD" actualValue="0" weight=".007" rank="4"/>
            <Attribute name="CUST_ID" actualValue="100003" weight=".006" rank="5"/>
            </Details>