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Foreword
by Donald K. Burleson
Oracle
Data Mining and Predictive Analytics
Why
this book is important
Chapter
1: Introduction to Model
Building
What
is Data Mining?
Components
of Oracle Data Miner
Sampling
Data from the Database
Concentrating
on a customer
Building
a Classification Model
Naming
Data Mining Activities
Running
a Data Mining Activity
Viewing
your Results
The
ODM ROC Curve
Applying
changes to a Model
Attribute
Importance in the Naīve Bayes Model
Building
Naīve Bayes Model with Fewer Attributes
Applying
the Model
Using
the Create View Wizard
Scoring
New Data
Viewing
Top Rankings
Conclusion
Chapter
2: Adaptive Bayes Network and
Decision Trees
Introduction
to Classification
Data
Mining Classification Models
Using
the Models
Importing
a Dataset
Exploring
and Reducing the Dataset
Viewing
Attribute Histograms
Attribute
Importance
Comparing
Naīve Bayes Models for Forest Cover
Adaptive
Bayes Single Feature Model
Building
the Adaptive Bayes Network Model
Sampling
Viewing
Adaptive Bayes Network Results
Interpreting
Adaptive Bayes Network Results
Building
the Adaptive Bayes Multi Feature Model
Using
the ROC Feature
Introducing
Cost Bias to the Classification Model
Building
a Decision Tree
The
Decision Tree Classification Model
Decision
Tree Classification Rules
Conclusion
Chapter
3: Using Support Vector
Machines
Introduction
to Support Vector Machine
Inside
Support Vector Machines
Importing
the Irish Wind Data File
Computing
a New Attribute with Compute Field Transformation Wizard
Building
the SVM Model
Handling
Outlier Values in SVM Analysis
Missing
Values in SVM Analysis
Sparse
Data in SVM Analysis
Normalization
of SVM Data
Linear
and Gaussian Kernels
SVM
and Over-fitting
SVM
Results with Gaussian Kernel
Importing
Boston House Price Data
Building
SVM Classification Models
Interpreting
the SVM Results
Refining
the SVM Model
Building
a SVM Regression Model
Regression
Model Results
Linear
Regression Analysis
Drilling
into the SVM Data
Using
Text Data in SVM Predictive Models
Importing
CLOB Data
Loading
CLOB Data into the Oracle Database
Building
a SVM Text Model
Interpreting
the SVM text Data
Conclusion
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Chapter
4: Creating Clusters and Cohorts
Clustering
and Cohorts
The
k-Means Cluster
Using
O-Cluster
O-Cluster
Sensitivity Settings
Using
K-Means for Clustering
Examining
the CoIL Data
Building
a K-Means Cluster
Finding
majority cohort values
Comparing
data sub-sets with K-Means
Choosing
the Appropriate Data Mining Algorithm
When
to use K-Means Analysis
When
to use O-Cluster Analysis
Applying
the Cluster
Publishing
the Cluster Results
Publishing
to a File
Using
the Discoverer Gateway for Publication
Publishing
to an Oracle Database
Importing
the model to a different Oracle database
Conclusion
Chapter
5: Inside Oracle Data Miner
Exploring
Data Miner
Data
Miner Activity Builder Tasks
Quantile
Binning
Using
the Discretize Transform Wizard
Customizing
Discretize Transformations
Using
the Aggregate Transformation Wizard
Recode
Transformation Wizard
Using
the Split Transformation Wizard
Using
the Stratified Sample Transformation Wizard
Using
the Filter Single-Record Transformation Wizard
Inside
the Sample Transformation Wizard
Preparing
datasets for Data Mining Activities
Using
the Missing Values Transformation Wizard
Using
the Normalize Transformation Wizard
Using
the Numeric Transformation Wizard
Using
the Outlier Treatment Transformation Wizard
Conclusion
Chapter
6: Predictive Analytics
Predictive
Analytics in Data Mining
Explain
Procedure
Predict
Procedure
Explain
Wizard
Predict
Wizard
Applying
Predictive Analytics
Conclusion
Chapter
7: Personalized Form Letter
Generation with Oracle BI Publisher
Scenarios
for using ODM with BI Publisher
Building
a Decision Tree Model
Results
of the Decision Tree Model
Scoring
the Apply Dataset.
Using
SQL to View Results of Scored Data
Creating
a Report using BI Publisher Enterprise Server
Using
Template Builder for Oracle BI Publisher
Adding
Fields to the Word Template using BI Publisher Template Builder
Creating
a Personalized Customer Letter with Three Offers
Scenario
for Personalizing a Form Letter
Building
a Decision Tree Model using Oracle Data Miner
Accuracy
of the Fund Raiser DT Model
Results
of the Fund Raiser DT Model
Generating
XML Data using BI Publisher
Creating
a Form Letter with the Template Builder
Conclusion
Book
Conclusion
Appendix
A: Installing Oracle Data
Miner
ODM
Tutorial
Purpose
Time
to Complete
Topics
Overview
Prerequisites
Enabling
the DMSYS Account
Creating
and Configuring A Data Mining Account
Installing
Oracle Data Miner
Summary
Appendix
B: Script to Create ODM User
Scripts
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