R Extensibility

23 R Extensibility

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.

23.1 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_MINING package is enhanced to support R model. For example, CREATE_MODEL and DROP_MODEL.
MODEL VIEW to 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, PREDICTION and CLUSTER_ID.

R model extensibility supports the following data mining functions:

Association
Attribute Importance
Regression
Classification
Clustering
Feature Extraction

23.2 Scoring with R

Learn how to build and score with R Mining model.

For more information, see Oracle Data Mining User’s Guide

23.3 About Algorithm Meta Data Registration

Algorithm Meta Data Registration allows for a uniform and consistent approach of registering new algorithm functions and their settings.

Users have the ability to add new R-based algorithms through the registration process. The new algorithms appear as available within Oracle R Enterprise and within the appropriate mining functions. Based on the registration meta data, the settings page is dynamically rendered. The advantages are as follows:

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.

Related Topics

23.3.1 Algorithm Meta Data Registration

Algorithm Meta Data Registration allows for a uniform and consistent approach of registering new algorithm functions and their settings.

User have the ability to add new algorithms through the registration process. The new algorithms can appear as available within Oracle Data Mining R within their appropriate mining functions. Based on the registration meta data, the settings page is dynamically rendered. Algorithm meta data registration extends the mining model capability of Oracle Data Mining.

Related Topics