PMML in Oracle Data Mining

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PMML (Predictive Model Markup Langauge) is an XML formatted output that defines the core elements and settings for your Predictive Models. This XML formatted output can be used to migrate your models from one data mining or predictive modelling tool to another data mining or predictive modelling tool, such as Oracle.

Using PMML to migrate your models from one tool to another allows for you to use the most appropriate tools for developing your models and then allows them to be imported into another tool that will be used for deploying your predictive models in batch or real-time mode. In particular the ability to use your Predictive Model within your everyday applications enables you to work in the area of Automatic or Prescriptive Analytics. Oracle Data Mining and the Oracle Database are ideal or even the best possible tools to allow for Automatic and Prescriptive Analytics for your transa

PMML is an XML based standard specified by the Data Mining Group

Oracle Data Mining supports the importing of PMML models that are compliant with version 3.1 of the standard and for Regression Models only. The regression models can be for linear regression or binary logistic regression.

The Data Mining Group Archive webpage have a number of sample PMML files for you to download and then to load into your Oracle database.

To Load the PMML file into your Oracle Database you can use the DBMS_DATA_MINING.IMPORT_MODEL function. I’ve given examples of how you can use this function to import an Oracle Data Mining model that was exported using the EXPORT_MODEL function.

The syntax of the IMPORT_MODEL function when importing a PMML file is the following

      model_name        IN  VARCHAR2,
      pmmldoc           IN  XMLTYPE
      strict_check      IN  BOOLEAN DEFAULT FALSE);

The following example shows how you can load the version 3.1 Logistic Regression PMML file from the Data Mining Group archive webpage



   dbms_data_mining.IMPORT_MODEL (‘PMML_MODEL',
        XMLType (bfilename (‘IMPORT_DIR', 'sas_3.1_iris_logistic_reg.xml'),
          nls_charset_id ('AL32UTF8')


This example uses the default value for STRICT_CHECK as FALASE. In this case if there are any errors in the PMML structure then these will be ignored and the imported model may contain “features” that may make it perform in a slightly odd manner.