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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 12
c
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
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