You can use the Model Scoring transformation to create a job that creates a target
table from a SAS Enterprise Miner model.
In this example, a statistician uses SAS Enterprise Miner and historical home equity
data to build a data mining model to predict if a customer might default on a home
equity loan. After the statistician builds the model, it is registered in a SAS
metadata repository that a SAS Data Integration Studio developer can use. Additional customer data is
collected using SAS Data Integration Studio. The new data has the same customer information
but does not contain the predictions about a customer's probability for defaulting
on a home equity loan. The SAS Data Integration Studio developer applies the SAS Enterprise
Miner model to the new data
source to generate the prediction of the customer's probability to default on a home equity
loan.
To use the Model Scoring transformation, your SAS Enterprise Miner models must be
registered in the same metadata repository that contains the sources for your job.
You can use the SAS Enterprise Miner Configuration Wizard to associate your SAS
Enterprise Miner metadata repository with the
metadata server that is used for your SAS Data Integration Studio application. See the SAS Enterprise
Miner online Help for more information about how to use this wizard.
Note: It is recommended that you
group your models in trees to make them easier to find when using
the Model Scoring transformation.
For best performance, the target of a Model Scoring transformation should have only
those columns that are required.
These columns include the required input variables from the source table and the output
results that are specified in the SAS Enterprise Miner model.
Perform the following
steps: