1. User's Guide
  2. Introduction to Oracle Machine Learning for R
  3. Typical Operations in Using Oracle Machine Learning for R

1.5 Typical Operations in Using Oracle Machine Learning for R

In using OML4R, the following is a typical progression of operations:

  1. In an R session, connect to a schema in an Oracle Database instance.

  2. Attach the schema and synchronize with the schema objects, which generates OML4R proxy objects for database tables.

  3. Prepare the data for analysis and possibly perform exploratory data analysis and data visualization.

  4. Build models using functions in the OREmodels or OREdm packages.

  5. Score data using the models either in your local R session or by using embedded R execution.

  6. Deploy the results of the analysis to end users.

Figure 1-1 Typical OML4R Workflow

This figure illustrates these steps and typical reiterations of them.

Description of Figure 1-1 follows
Description of "Figure 1-1 Typical OML4R Workflow"

Parent topic: Introduction to Oracle Machine Learning for R