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Contents

List of Examples

List of Figures

List of Tables

Title and Copyright Information

Preface

• Audience
• Related Documentation
• Documentation Accessibility
• Conventions

Changes in This Release for Oracle Data Mining Concepts

• Changes in Oracle Data Mining 12c Release 1 (12.1)

Part I Introductions

1 What Is Data Mining?

• What Is Data Mining?
• What Can Data Mining Do and Not Do?
• The Data Mining Process

2 Introduction to Oracle Data Mining

• About Oracle Data Mining
• Data Mining in the Database Kernel
• Data Mining in Oracle Exadata
• Interfaces to Oracle Data Mining
• Overview of Database Analytics

3 Oracle Data Mining Basics

• Mining Functions
• Algorithms
• Data Preparation
• In-Database Scoring

Part II Mining Functions

4 Regression

• About Regression
• Testing a Regression Model
• Regression Algorithms

5 Classification

• About Classification
• Testing a Classification Model
• Biasing a Classification Model
• Classification Algorithms

6 Anomaly Detection

• About Anomaly Detection
• Anomaly Detection Algorithm

7 Clustering

• About Clustering
• Evaluating a Clustering Model
• Clustering Algorithms

8 Association

• About Association
• Transactional Data
• Association Algorithm

9 Feature Selection and Extraction

• Finding the Best Attributes
• About Feature Selection and Attribute Importance
• About Feature Extraction
• Algorithms for Attribute Importance and Feature Extraction

Part III Algorithms

10 Apriori

• About Apriori
• Association Rules and Frequent Itemsets
• Data Preparation for Apriori
• Calculating Association Rules
• Evaluating Association Rules

11 Decision Tree

• About Decision Tree
• Growing a Decision Tree
• Tuning the Decision Tree Algorithm
• Data Preparation for Decision Tree

12 Expectation Maximization

• About Expectation Maximization
• Algorithm Enhancements
• Configuring the Algorithm
• Data Preparation for Expectation Maximization

13 Generalized Linear Models

• About Generalized Linear Models
• GLM in Oracle Data Mining
• Scalable Feature Selection
• Tuning and Diagnostics for GLM
• Data Preparation for GLM
• Linear Regression
• Logistic Regression

14 k-Means

• About k-Means
• Tuning the k-Means Algorithm
• Data Preparation for k-Means

15 Minimum Description Length

• About MDL
• Data Preparation for MDL

16 Naive Bayes

• About Naive Bayes
• Tuning a Naive Bayes Model
• Data Preparation for Naive Bayes

17 Non-Negative Matrix Factorization

• About NMF
• Tuning the NMF Algorithm
• Data Preparation for NMF

18 O-Cluster

• About O-Cluster
• Tuning the O-Cluster Algorithm
• Data Preparation for O-Cluster

19 Singular Value Decomposition

• About Singular Value Decomposition
• Configuring the Algorithm
• Data Preparation for SVD

20 Support Vector Machines

• About Support Vector Machines
• Tuning an SVM Model
• Data Preparation for SVM
• SVM Classification
• One-Class SVM
• SVM Regression

Glossary

Index