Learn how to built analytics model and scored in R with ease. R extensible algorithms are enhanced to support and register additional algorithms for SQL users and graphical user interface users.
24.1 Oracle Data Mining with R Extensibility
Learn how you can use Oracle Data Mining to build, score, and view Oracle Data Mining models as well as R models.
The Oracle Data Mining framework is enhanced extending the data mining algorithm set with algorithms from the open source R ecosystem. Oracle Data Mining is implemented in the Oracle Database kernel. The mining models are Database schema objects. With the extensibility enhancement, the data mining framework can build, score, and view both Oracle Data Mining models and R models.
Registration of R scripts
The R engine on the database server executes the R scripts to build, score, and view R models. These R scripts must be registered with the database beforehand by a privileged user with rqAdmin role. You must first install Oracle R Enterprise to register the R scripts.
Functions of Oracle Data Mining with R Model
The following functions are supported for an R model:
Oracle Data Mining
DBMS_DATA_MININGpackage is enhanced to support R model. For example,
MODEL VIEWto get the R model details about a single model and a partitioned model.
Oracle Data Mining SQL functions are enhanced to operate with the R model functions. For example,
R model extensibility supports the following data mining functions:
24.2 Scoring with R
Learn how to build and score with R Mining model.
For more information, see Oracle Data Mining User’s Guide
24.3 About Algorithm Meta Data Registration
Algorithm Meta Data Registration allows for a uniform and consistent approach of registering new algorithm functions and their settings.
Manage R-based algorithms more easily
Easy to specify R-based algorithm for model build
Clean individual properties in JSON structure
Share R-based algorithm across user
Algorithm meta data registration extends the mining model capability of Oracle Data Mining.