The following diagram
illustrates the model management process:
Here is a summary of
the model management process:
-
Create Model Repository:
create a secure model repository on the SAS Content Server where SAS
code, input and output files, and metadata that is associated with
a model can be stored.
-
Register Candidate
Models: register input and output files, and then import
and configure a model.
-
Compare Models:
perform scoring tests and create comparison reports for the models
by using test data sources.
-
Declare Champion or
Challenger Model: declare the model as champion or challenger
to use for testing and production phases of the workflow.
-
Validate Model:
perform scoring tests and create validation reports for the champion
model and challenger models by using test data sources.
-
Lock Version:
lock a version when the champion model is approved for production.
-
Deliver or Publish
Model: publish a champion or challenger models to a SAS
publish channel, to a database, or to the SAS Metadata Repository.
-
Monitor Model Performance:
provide comparative model performance benchmarking.
-
Retrain Models:
select models to retrain in response to data or market changes.
-
Retire Model:
retire a model from production.
Here is an example of
the model management process for comparing a challenger model to the
champion model to determine the best champion model:
-
Register candidate models in the version that is under
development.
-
Create a Dynamic Lift report and compare the model
to the champion model. Flag the model as a challenger based on the
results of the Dynamic Lift report.
-
Perform scoring tests with the champion and challenger
models in real time or in batch. This step can be performed outside SAS Model Manager.
-
Publish the challenger model to a database or to the
SAS Metadata Repository.
-
Prepare performance data sources, which include both
the actual outcome variable and predicted variable.
-
Create and execute the performance monitoring for
the champion and challenger models to create reports to compare and
validate the champion model and challenger models. One of the reports
that is available for this comparison is the Champion and Challenger
Performance report.
-
Set the challenger model as the project champion if
the challenger is good enough to be promoted. Go to step 3, or consider
building another model as a challenger with existing or a new input
training data source.
-
Publish the new project champion model with or without
a new challenger model.