The OML4R machine learning interface is built on top of OML4SQL, leveraging the same in-database algorithms, with the ability to use the same algorithm hyperparameters.

These OREdm package functions provide R interfaces that use arguments that conform to typical R usage for corresponding predictive analytics and OML4SQL functions.

This section has the following topics:

• In-Database Algorithms Supported by OML4R
  
• About In-Database Model Names and Renaming with OML4R Functions
  In each OREdm R model object, the slot name is the name of the underlying OML4SQL model generated by the OREdm function.
• Specify Model Settings
  Functions in the OREdm package have an argument that specifies settings for an in-database model and some have an argument for setting text processing parameters.