|Oracle® Database SQL Language Reference
11g Release 2 (11.2)
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This function is for use with classification models created by the
DBMS_DATA_MINING package or with Oracle Data Miner. It returns a measure of cost for a given prediction as an Oracle
If you specify the optional
class parameter, then the function returns the cost for the specified class. If you omit the
class parameter, then the function returns the cost associated with the best prediction. You can use this form in conjunction with the
PREDICTION function to obtain the best pair of prediction value and cost.
COST clause is relevant for all classification models.
MODEL to indicate that the scoring should be performed by taking into account the scoring cost matrix associated with the model. If no such scoring cost matrix exists, then the database returns an error.
AUTO if the existence of a cost matrix is unknown. In this case:
If the stored cost matrix exists, then the function returns the cost using the stored cost matrix.
If no stored cost matrix exists, then the function applies the unit cost matrix (0's on the diagonal and 1's everywhere else). This is equivalent to one minus probability for the given class.
VALUES clause (the bottom branch of the
cost_matrix_clause) to specify an inline cost matrix. You can use an inline cost matrix regardless of whether the model has an associated scoring cost matrix. Refer to Oracle Data Mining Application Developer's Guide for an example of an inline cost matrix
mining_attribute_clause behaves as described for the
PREDICTION function. Refer to mining_attribute_clause.
The following example finds the ten customers living in Italy who are least expensive to convince to use an affinity card.
This example and the prerequisite data mining operations can be found in the demo file
$ORACLE_HOME/rdbms/demo/dmdtdemo.sql. General information on data mining demo files is available in Oracle Data Mining Administrator's Guide. The example is presented here to illustrate the syntactic use of the function.
WITH cust_italy AS ( SELECT cust_id FROM mining_data_apply_v WHERE country_name = 'Italy' ORDER BY PREDICTION_COST(DT_SH_Clas_sample, 1 COST MODEL USING *) ASC, 1 ) SELECT cust_id FROM cust_italy WHERE rownum < 11; CUST_ID ---------- 100081 100179 100185 100324 100344 100554 100662 100733 101250 101306 10 rows selected.