Skip Headers
Oracle® Database SQL Language Reference
11g Release 1 (11.1)

Part Number B28286-01
Go to Documentation Home
Go to Book List
Book List
Go to Table of Contents
Go to Index
Go to Master Index
Master Index
Go to Feedback page
Contact Us

Go to previous page
Go to next page
View PDF



Description of prediction.gif follows
Description of the illustration prediction.gif


Description of cost_matrix_clause.gif follows
Description of the illustration cost_matrix_clause.gif


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


This function is for use with models created by the DBMS_DATA_MINING package or with the Oracle Data Mining Java API. It returns the best prediction for the model. The datatype returned depends on the target value type used during the build of the model. For regression models, this function returns the expected value.

cost_matrix_clause  The COST clause is relevant for all classification models.

If you omit the cost_matrix_clause clause, then the best prediction is the target class with the highest probability. If two or more classes are tied with the highest probability, the database chooses one class.

mining_attribute_clause This maps the predictors that were provided when the model was built. Specifying USING * maps to all to the columns and expressions that can be retrieved from the underlying inputs (tables, views, and so on).

See Also:


The following example returns by gender the average age of customers who are likely to use an affinity card. The PREDICTION function takes into account only the cust_marital_status, education, and household_size predictors.

This example, and the prerequisite data mining operations, including the creation of the view, 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.

SELECT cust_gender, COUNT(*) AS cnt, ROUND(AVG(age)) AS avg_age
   FROM mining_data_apply_v
      USING cust_marital_status, education, household_size) = 1
   GROUP BY cust_gender
   ORDER BY cust_gender;

C        CNT    AVG_AGE
- ---------- ----------
F        170         38
M        685         42