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Oracle9i Data Mining Concepts

Part Number A95961-02
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1 Basic ODM Concepts

1.1 New Features and Functionality
1.2 Oracle9i Data Mining Components
1.2.1 Oracle9i Data Mining API
1.2.2 Data Mining Server
1.3 Data Mining Functions
1.3.1 Classification
1.3.2 Clustering
1.3.3 Association Rules
1.3.4 Attribute Importance
1.4 ODM Algorithms
1.4.1 Adaptive Bayes Network
1.4.2 Naive Bayes Algorithm
1.4.3 Model Seeker
1.4.4 Enhancedk-Means Algorithm
1.4.5 O-Cluster Algorithm
1.4.6 Predictor Variance Algorithm
1.4.7 Apriori Algorithm
1.5 Data Mining Tasks
1.5.1 Model Build
1.5.2 Model Test
1.5.3 Computing Lift
1.5.4 Model Apply (Scoring)
1.6 ODM Objects and Functionality
1.6.1 Physical Data Specification
1.6.2 Mining Function Settings
1.6.3 Mining Algorithm Settings
1.6.4 Logical Data Specification
1.6.5 Mining Attributes
1.6.6 Data Usage Specification
1.6.7 Mining Model
1.6.8 Mining Results
1.6.9 Confusion Matrix
1.6.10 Mining Apply Output
1.7 Missing Values
1.7.1 Missing Values Handling
1.8 Discretization (Binning)
1.8.1 Numerical and Categorical Attributes
1.8.2 Automated Binning
1.8.3 Data Preparation
1.9 PMML Support

2 ODM Programming

2.1 Compiling and Executing ODM Programs
2.2 Using ODM to Perform Mining Tasks
2.2.1 Build a Model
2.2.2 Perform Tasks in Sequence
2.2.3 Find the Best Model
2.2.4 Find and Use the Most Important Attributes
2.2.5 Apply a Model to New Data

3 ODM Basic Usage

3.1 Using the Short Sample Programs
3.2 Building a Model
3.2.1 Before Building an ODM Model
3.2.2 Main Steps in ODM Model Building
3.2.3 Connect to the Data Mining Server
3.2.4 Describe the Build Data
3.2.5 Create the MiningFunctionSettings Object
3.2.6 Build the Model
3.3 Scoring Data Using a Model
3.3.1 Before Scoring Data
3.3.2 Main Steps in ODM Scoring
3.3.3 Connect to the Data Mining Server
3.3.4 Describe the Input Data
3.3.5 Describe the Output Data
3.3.6 Specify the Format of the Apply Output
3.3.7 Apply the Model

A ODM Sample Programs

A.1 Overview of the ODM Sample Programs
A.1.1 ODM Java API
A.1.2 Oracle9i JDeveloper Project for the Sample Programs
A.1.3 Requirements for Using the Sample Programs
A.2 ODM Sample Programs Summary
A.2.1 Basic ODM Usage
A.2.2 Adaptive Bayes Network Models
A.2.3 Naive Bayes Models
A.2.4 Model Seeker Usage
A.2.5 Clustering Models
A.2.6 Association Rules Models
A.2.7 PMML Export and Import
A.2.8 Attribute Importance Model Build and Use
A.2.9 Discretization
A.3 Using the ODM Sample Programs
A.4 Data Used by the Sample Programs
A.5 Property Files for the ODM Sample Programs
A.5.10 Sample_AssociationRules Property Files
A.5.16 Other Sample_AdaptiveBayesNetwork Property Files
A.5.17 Sample PMML Import and Export Property
A.6 Compiling and Executing ODM Sample Programs
A.6.1 Compiling the Sample Programs
A.6.2 Executing the Sample Programs