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Contents
Title and Copyright Information
Preface
Audience
Related Documentation
Oracle Data Mining Resources on the Oracle Technology Network
Application Development and Database Administration Documentation
Documentation Accessibility
Conventions
Changes in This Release for Oracle Data Mining User's Guide
Oracle Data Mining User's Guide is New in This Release
Changes in Oracle Data Mining 12c Release 1 (12.1)
New Features
Desupported Features
Other Changes
1
Data Mining With SQL
Highlights of the Data Mining API
Example: Targeting Likely Candidates for a Sales Promotion
Example: Analyzing Preferred Customers
Example: Segmenting Customer Data
2
About the Data Mining API
About Mining Models
Data Mining Data Dictionary Views
USER_MINING_MODELS
USER_MINING_MODEL_ATTRIBUTES
USER_MINING_MODEL_SETTINGS
Data Mining PL/SQL Packages
DBMS_DATA_MINING
DBMS_DATA_MINING_TRANSFORM
DBMS_PREDICTIVE_ANALYTICS
Data Mining SQL Scoring Functions
3
Preparing the Data
Data Requirements
Column Data Types
Data Sets for Classification and Regression
Scoring Requirements
About Attributes
Data Attributes and Model Attributes
Target Attribute
Numericals, Categoricals, and Unstructured Text
Model Signature
Scoping of Model Attribute Name
Model Details
Using Nested Data
Nested Object Types
Example: Transforming Transactional Data for Mining
Using Market Basket Data
Example: Creating a Nested Column for Market Basket Analysis
Handling Missing Values
Examples: Missing Values or Sparse Data?
Missing Value Treatment in Oracle Data Mining
Changing the Missing Value Treatment
4
Transforming the Data
About Transformations
Preparing the Case Table
Creating Nested Columns
Converting Column Data Types
Text Transformation
About Business and Domain-Sensitive Transformations
Understanding Automatic Data Preparation
Binning
Normalization
Outlier Treatment
How ADP Transforms the Data
Embedding Transformations in a Model
Specifying Transformation Instructions for an Attribute
Building a Transformation List
Transformation Lists and Automatic Data Preparation
Oracle Data Mining Transformation Routines
Understanding Reverse Transformations
5
Creating a Model
Before Creating a Model
The CREATE_MODEL Procedure
Choosing the Mining Function
Choosing the Algorithm
Supplying Transformations
Specifying Model Settings
Specifying Costs
Specifying Prior Probabilities
Specifying Class Weights
Model Settings in the Data Dictionary
Viewing Model Details
6
Scoring and Deployment
About Scoring and Deployment
Using the Data Mining SQL Functions
Choosing the Predictors
Single-Record Scoring
Prediction Details
Cluster Details
Feature Details
Prediction Details
Real-Time Scoring
Dynamic Scoring
Cost-Sensitive Decision Making
DBMS_DATA_MINING.Apply
7
Mining Unstructured Text
About Unstructured Text
About Text Mining and Oracle Text
Creating a Model that Includes Text Mining
Creating a Text Policy
Configuring a Text Attribute
8
Administrative Tasks for Oracle Data Mining
Installing and Configuring a Database for Data Mining
About Installation
Enabling or Disabling a Database Option
Database Tuning Considerations for Data Mining
Upgrading or Downgrading Oracle Data Mining
Pre-Upgrade Steps
Upgrading Oracle Data Mining
Post Upgrade Steps
Downgrading Oracle Data Mining
Exporting and Importing Mining Models
About Oracle Data Pump
Options for Exporting and Importing Mining Models
Directory Objects for EXPORT_MODEL and IMPORT_MODEL
Using EXPORT_MODEL and IMPORT_MODEL
Importing From PMML
Controlling Access to Mining Models and Data
Creating a Data Mining User
System Privileges for Data Mining
Object Privileges for Mining Models
Auditing and Adding Comments to Mining Models
Adding a Comment to a Mining Model
Auditing Mining Models
A
The Data Mining Sample Programs
About the Data Mining Sample Programs
Installing the Data Mining Sample Programs
The Data Mining Sample Data
Index
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