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Oracle® Data Mining Application Developer's Guide,
10
g
Release 2 (10.2)
Part Number B14340-01
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Contents
Title and Copyright Information
Preface
Audience
Documentation Accessibility
Related Documentation
Conventions
1
Introducing the Oracle Data Mining APIs
1.1
New Features
1.2
Predictive and Descriptive Data Mining
1.3
Steps in a Data Mining Application
1.4
Data Preparation
1.5
Model Settings
1.6
Model Details
1.7
Predictive Analytics
1.8
SQL Scoring Functions
2
Managing Data
2.1
Data Types
2.1.1
Collection Types
2.1.2
Text
2.1.3
Date and Time Data
2.2
Columns and Attributes
2.2.1
Attribute Data Types
2.2.1.1
Converting Column Data Types
2.2.1.2
DATE and TIMESTAMP Columns with Predictive Analytics
2.2.2
Attribute Names
2.3
Nested Tables
2.3.1
Object Views and Multi-Record Collections
2.3.2
Example: Multi-Record Collections With an Object View
2.4
Data Storage Optimization
3
Managing Models
3.1
Models in the Database
3.1.1
Model Names
3.1.2
Model Access
3.2
Import/Export
3.3
Model Settings
3.3.1
Costs
3.3.2
Priors
4
Using the PL/SQL API and SQL Scoring Functions
4.1
The PL/SQL Sample Applications
4.2
The DBMS_DATA_MINING Package
4.2.1
Build Results
4.2.2
Apply Results
4.2.3
Test Results for Classification Models
4.2.4
Test Results for Regression Models
4.2.4.1
Root Mean Square Error
4.2.4.2
Mean Absolute Error
4.3
Example: Building a Decision Tree Model
4.3.1
Mining Data
4.3.2
Build Settings
4.3.3
Model Creation
4.4
Example: Using SQL Functions to Test a Decision Tree Model
4.5
Example: Using SQL Functions to Apply a Decision Tree Model
5
Using PL/SQL to Prepare Text Data for Mining
5.1
Oracle Text for Oracle Data Mining
5.2
Term Extraction in the Sample Programs
5.2.1
Text Mining Programs
5.3
From Unstructured Data to Structured Data
5.4
Steps in the Term Extraction Process
5.4.1
Transform a Text Column in the Build Table
5.4.2
Transform a Text Column in the Test and Apply Tables
5.4.3
Creating the Index and Index Preference
5.4.4
Creating the Intermediate Terms Table
5.4.4.1
FEATURE_PREP Calling Syntax
5.4.4.2
FEATURE_PREP Return Value
5.4.4.3
FEATURE_PREP Arguments
5.4.4.4
FEATURE_PREP Example
5.4.5
Creating the Final Terms Table
5.4.5.1
FEATURE_EXPLAIN Calling Syntax
5.4.5.2
FEATURE_EXPLAIN Return Value
5.4.5.3
FEATURE_EXPLAIN Arguments
5.4.5.4
FEATURE_EXPLAIN Example
5.4.6
Populating a Nested Table Column
5.5
Example: Transforming a Text Column
6
Java API Overview
6.1
The JDM 1.0 Standard
6.2
Oracle Extensions to JDM 1.0
6.3
Principal Objects in the ODM Java API
6.3.1
PhysicalDataSet Object
6.3.2
BuildSettings Object
6.3.3
Task Object
6.3.4
Model Object
6.3.5
TestMetrics Object
6.3.6
ApplySettings Object
7
Using the Java API
7.1
The Java Sample Applications
7.2
Setting up Your Development Environment
7.3
Connecting to the Data Mining Server
7.3.1
Connection Factory
7.3.1.1
Create a ConnectionFactory Using OraConnectionFactory
7.3.1.2
Create a ConnectionFactory From the JNDI Server
7.3.2
Managing the DMS Connection
7.3.2.1
Pre-Create the JDBC Connection
7.3.2.2
Use a ConnectionSpec for the DMS Connection
7.3.3
Features of a DMS Connection
7.3.3.1
Create Object Factories
7.3.3.2
Provide Access to Mining Object Metadata
7.3.3.3
Save and Retrieve Mining Objects
7.3.3.4
Execute Mining Tasks
7.3.3.5
Retrieve DMS Capabilities and Metadata
7.3.3.6
Retrieve Version Information
7.4
API Design Overview
7.5
Describing the Mining Data
7.6
Build Settings
7.7
Executing Mining Tasks
7.8
Building a Mining Model
7.9
Exploring Model Details
7.10
Testing a Model
7.11
Applying a Model for Scoring Data
7.12
Using a Cost Matrix
7.13
Using Prior Probabilities
7.14
Using Automated Prediction and Explain Tasks
7.15
Preparing the Data
7.15.1
Using Binning/Discretization Transformation
7.15.2
Using Normalization Transformation
7.15.3
Using Clipping Transformation
7.15.4
Using Text Transformation
8
Converting to the ODM 10.2 Java API
8.1
Comparing the 10.1 and 10.2 Java APIs
8.2
Converting Your Applications
9
Sequence Matching and Annotation (BLAST)
9.1
NCBI BLAST
9.2
Using ODM BLAST
9.2.1
Using BLASTN_MATCH to Search DNA Sequences
9.2.1.1
Searching for Good Matches in DNA Sequences
9.2.1.2
Searching DNA Sequences Published After a Certain Date
9.2.2
Using BLASTP_MATCH to Search Protein Sequences
9.2.2.1
Searching for Good Matches in Protein Sequences
9.2.3
Using BLASTN_ALIGN to Search and Align DNA Sequences
9.2.3.1
Searching and Aligning for Good Matches in DNA Sequences
9.2.4
Output of BLAST Queries
9.2.5
Using BLASTN_COMPRESS to Improve Search Performance
9.2.5.1
Compress Sequences
9.2.5.2
Passing a Compressed Sequence to a BLAST Function
9.2.6
Sample Data for BLAST
9.2.6.1
SWISSPROT Table
9.2.6.2
PROT_DB Table
9.2.6.3
ECOLI10 Table
9.2.6.4
Genetic Codes and Names
9.2.6.5
Sequence Databases
9.2.6.6
Loading Sequences into an Oracle Database
Summary of BLAST Table Functions
BLASTN_COMPRESS Table Function
BLASTN_MATCH Table Function
BLASTP_MATCH Table Function
TBLAST_MATCH Table Function
BLASTN_ALIGN Table Function
BLASTP_ALIGN Table Function
TBLAST_ALIGN Table Function
Index
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