This document explains how to install and administer Oracle Machine Learning for R (OML4R) Release 1.5.1.
Oracle R Enterprise is now Oracle Machine Learning for R (OML4R).
Oracle is rebranding the suite of products and components that support machine learning with Oracle Database and Big Data. This technology is now known as Oracle Machine Learning (OML).
The OML application programming interface for R, previously under the name Oracle R Enterprise, is now named Oracle Machine Learning for R (OML4R). The package, class, and function names are not rebranded. They remain
ore.connect, and so on.
The OML application programming interfaces for SQL include PL/SQL packages, SQL functions, and data dictionary views. Using these APIs is described in publications, previously under the name Oracle Data Mining, that are now named Oracle Machine Learning for SQL (OML4SQL). The PL/SQL package and database view names are not rebranded. They remain
ALL_MINING_MODELS, and so on.
The Oracle R Advanced Analytics for Hadoop (ORAAH) technology is now Oracle Machine Learning for Spark (OML4Spark).
For more information, see Oracle Machine Learning.
This document is intended for anyone who is responsible for installing or administering Oracle Machine Learning for R.
Installation of OML4R requires knowledge of R and knowledge of Oracle Database.
The Oracle Machine Learning for R documentation set includes the following publications.
For information about Oracle's commitment to accessibility, visit the Oracle Accessibility Program website at http://www.oracle.com/pls/topic/lookup?ctx=acc&id=docacc.
Access to Oracle Support
Oracle customers that have purchased support have access to electronic support through My Oracle Support. For information, visit http://www.oracle.com/pls/topic/lookup?ctx=acc&id=info or visit http://www.oracle.com/pls/topic/lookup?ctx=acc&id=trs if you are hearing impaired.
The following text conventions are used in this document.
Boldface type indicates graphical user interface elements associated with an action, or terms defined in text or the glossary.
Italic type indicates book titles, emphasis, or placeholder variables for which you supply particular values.
Monospace type indicates commands within a paragraph, URLs, code in examples, text that appears on the screen, or text that you enter.