Preface

This guide explains how to use the programmatic interfaces to Oracle Machine Learning for SQL (OML4SQL), previously known as Oracle Data Mining. This guide also describes how to use features of Oracle Database to administer OML4SQL, and presents the tools and procedures for implementing the concepts that are presented in Oracle Machine Learning for SQL Concepts .

This preface contains these topics:

• Technology Rebrand

• Audience

• Documentation Accessibility

• Related Documentation

• Conventions

Technology Rebrand

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 interfaces (APIs) 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).

Audience

This guide is intended for application developers and database administrators who are familiar with SQL programming and Oracle Database administration and who have a basic understanding of machine learning concepts.

Documentation Accessibility

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.

Related Documentation

The following manuals document Oracle Machine Learning for SQL:

• Oracle Machine Learning for SQL Concepts

• Oracle Machine Learning for SQL User’s Guide (this guide)

• Oracle Machine Learning for SQL API Guide

  Note:

  This publication combines key passages from the other two Oracle Machine Learning for SQL manuals with related reference documentation in Oracle Database PL/SQL Packages and Types Reference, Oracle Database SQL Language Reference, and Oracle Database Reference.

• Oracle Database PL/SQL Packages and Types Reference (PL/SQL packages)

  • DBMS_DATA_MINING

  • DBMS_DATA_MINING_TRANSFORM

  • DBMS_PREDICTIVE_ANALYTICS

• Oracle Database Reference (data dictionary views for ALL_, USER_, and DBA_)

  • ALL_MINING_MODELS

  • ALL_MINING_MODEL_ATTRIBUTES

  • ALL_MINING_MODEL_SETTINGS

• Oracle Database SQL Language Reference (OML4SQL functions)

  • CLUSTER_DETAILS, CLUSTER_DISTANCE, CLUSTER_ID, CLUSTER_PROBABILITY, CLUSTER_SET

  • FEATURE_DETAILS, FEATURE_ID, FEATURE_SET, FEATURE_VALUE

  • PREDICTION, PREDICTION_BOUNDS, PREDICTION_COST, PREDICTION_DETAILS, PREDICTION_PROBABILITY, PREDICTION_SET

Oracle Machine Learning for SQL Resources on the Oracle Technology Network

The Oracle Machine Learning for SQL page on the Oracle Technology Network (OTN) provides a wealth of information, including white papers, demonstrations, blogs, discussion forums, and Oracle By Example tutorials.

You can download Oracle Data Miner, the graphical user interface to Oracle Machine Learning for SQL, from this site:

Oracle Data Miner

Application Development and Database Administration Documentation

For documentation to assist you in developing database applications and in administering Oracle Database, refer to the following:

• Oracle Database Concepts

• Oracle Database Administrator’s Guide

• Oracle Database Development Guide

Conventions

The following text conventions are used in this document:

Convention	Meaning
boldface	Boldface type indicates graphical user interface elements associated with an action, or terms defined in text or the glossary.
italic	Italic type indicates book titles, emphasis, or placeholder variables for which you supply particular values.
monospace	Monospace type indicates commands within a paragraph, URLs, code in examples, text that appears on the screen, or text that you enter.