
Predictive Analytics Using Oracle Data Miner
Beschreibung
Weitere Details
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Inhalt
- Cover
- About the Author
- About the Technical Editor
- Title Page
- Copyright Page
- Contents at a Glance
- Contents
- Acknowledgments
- Introduction
- PART I: Oracle Data Miner Fundamentals
- Chapter 1: Oracle Data Miner
- In-Database Data Mining with Oracle Data Mining
- Oracle Advanced Analytics Option
- Oracle Data Mining
- Oracle R Enterprise (ORE)
- History of Data Mining in Oracle
- Oracle Data Mining Components
- Oracle Data Mining Architecture
- Oracle Data Miner GUI Tool
- Oracle Data Mining Using SQL and PL/SQL
- Oracle Statistical Functions
- Applications Powered by Oracle Data Mining
- How Are Customers Using Oracle Advanced Analytics
- Customer Success Stories
- Chapter 2: The Predictive Modeling Lifecycle
- Predictive Modeling Lifecycles
- Knowledge Discovery in Data (KDD) Process
- SEMMA
- CRISP-DM
- Business Understanding
- Data Understanding
- Data Preparation
- Modeling
- Evaluation
- Deployment
- Summary
- Chapter 3: How to Install, Set Up, and Get Started
- Enabling the Oracle Advanced Analytics Option
- Creating a Data Mining Tablespace
- Creating an ODM Schema
- Creating a Connection for Your DM User in SQL Developer
- Creating the Oracle Data Mining Repository
- Using SQL Developer to Create the ODM Repository
- Using SQL Scripts to Create the ODM Repository
- Setting Up Additional Users to Access ODM
- ODM Schema System Privileges
- Setting Up and Using the Pre-built Database Appliance
- Summary
- PART II: Using the Oracle Data Miner Tool
- Chapter 4: ODM Menus, Projects, and Workflows
- The ODM Menus
- Creating a Project
- Creating, Exporting, and Importing a Workflow
- Creating a Workflow
- Exporting a Workflow
- Importing a Workflow
- Adjusting the Layout
- The ODM Workflow Menu
- The Components Workflow Editor
- Summary
- Chapter 5: Exploring Your Data
- Gathering Statistics and Exploring Your Data
- Adding a Data Source
- Data Source Properties
- The Explore Data Node
- Building Up a Story About the Data
- Exploring the Data Based on Attribute Grouping
- Graphs
- Creating a Graph
- SQL Query Node
- Feature Selection
- Summary
- Chapter 6: Data Preparation
- Aggregate
- Using the Aggregation Wizard
- Adding a New Aggregation-Level Attribute
- Adding an Aggregation Expression
- Filter Columns
- Filter Columns Details
- Filter Rows
- Join
- Sample
- Transform
- Automatic Data Preparation (ADP)
- Summary
- Chapter 7: Association Rule Analysis
- What Is Association Rule Analysis?
- Association Rule Analysis in Oracle
- Building Association Rules Using ODM
- Defining the Data Source
- Creating the Association Node
- Model Settings
- Association Node Properties Tab
- Viewing the Association Rules
- Generated Rules
- Generated Itemsets
- Adding a Data Source Node for Transaction Descriptions
- Applying Filters to the Association Rules
- Outputting and Persisting the Association Rules
- Summary
- Chapter 8: Classification
- What Is Classification?
- Classification Methods Available in Oracle
- Building Classification Models
- Model Settings
- Property Inspector
- Using Different Build and Test Data Sets
- Creating Additional Models and Removing Unwanted Models
- Generating the Models
- Evaluating the Classification Models
- Performance
- Performance Matrix
- ROC
- Lift
- Profit
- Applying a Classification Model to New Data
- Summary
- Chapter 9: Clustering
- What Is Clustering?
- Clustering Methods Available in Oracle
- Building Clustering Models
- Model Settings
- Property Inspector
- Creating Additional Models and Removing Unwanted Models
- Generating the Models
- Evaluating the Classification Models
- View Your Cluster Models
- Cluster Details
- Comparing Clusters: Multicluster-Multivariable Comparison
- Renaming Clusters
- Applying a Clustering Model to New Data
- Summary
- Chapter 10: Regression
- What Is Regression?
- Regression Methods Available in Oracle
- Preparing Your Data for Regression
- Building Regression Models
- Regression Model Settings
- Property Inspector
- Generating the Regression Models
- Viewing the Regression Models
- Regression Model Test Results
- Applying a Regression Model to New Data
- Summary
- Chapter 11: Anomaly Detection
- What Is Anomaly Detection?
- Anomaly Detection in Oracle
- Building an Anomaly Detection Model
- Model Settings
- Property Inspector
- Generating the Models
- Evaluating the Anomaly Detection Model
- Applying the Model to Your Data
- Summary
- PART III: Data Mining Using SQL and PL/SQL
- Chapter 12: The ODM Data Dictionary, SQL, and PL/SQL Packages
- ODM Data Dictionary Views
- ODM SQL Functions
- ODM PL/SQL Packages
- DBMS_DATA_MINING PL/SQL Package
- DBMS_PREDICTIVE_ANALYTICS PL/SQL Package
- Summary
- Chapter 13: Data Preparation
- Data Preparation for Data Mining
- Data Sampling
- Data Aggregation and Pivoting the Data
- Handling Missing Data
- Histograms and Binning
- Creating a Target Variable/Attribute
- Automatic Data Preparation in ODM
- ADP with Transformation Lists
- Using DBMS_DATA_MINING_TRANSFORM PL/SQL Package
- List of Package Procedures and Functions
- Example of Using the DBMS_DATA_MINING_TRANSFORM Package
- Embedding Transformation List into the Model
- Summary
- Chapter 14: Association Rule Analysis
- Setting Up Your Data
- Settings Table
- Creating the Association Rule Analysis Model
- Viewing the Association Rule Model Item Sets and Rule
- Viewing the Frequent Item Sets
- Viewing the Association Rules
- Summary
- Chapter 15: Classification
- Setting Up Your Data
- Settings Table
- Creating the Classification Models
- Evaluating the Classification Models
- Preparing the Data
- Computing the Confusion Matrix
- Computing the Lift
- Computing the ROC
- Applying the Model to New Data
- Applying the Model in Real Time
- Applying the Model in Batch
- Summary
- Chapter 16: Clustering
- Setting Up Your Data
- Viewing Your Existing Cluster Models
- Settings Table
- Creating a Cluster Model
- Examining the Cluster Model
- Querying the Cluster Models in Your Schema
- Examining the Cluster Details
- Applying the Cluster Model to New Data
- Applying the Cluster Model in Real Time
- Applying the Cluster Model in Batch Mode
- Combining Clusters
- Summary
- Chapter 17: Regression
- Examining the Existing Regression Model(s)
- Settings Table for Regression
- Creating a Regression Model
- Examining and Evaluating the Regression Models
- Global Statistics for a GLM Regression Model
- GLM Regression Model Details
- SVM Regression Model Details
- Residual Statistics
- Applying Regression Model to Your Data
- Using the Regression Model in Real Time
- Using the Regression Model in Batch Mode
- Summary
- Chapter 18: Anomaly Detection
- Examining the Existing Anomaly Detection Model(s)
- Settings Table
- Creating an Anomaly Detection Model
- Applying the Anomaly Detection Model to Your Data
- Using the Anomaly Detection Model in Real Time
- Using the Anomaly Detection Model in Batch Mode
- Summary
- PART IV: Migration and Implementations
- Chapter 19: How to Migrate Your ODM Models
- Oracle Data Miner Script Generation
- Running the ODM Workflow Scripts
- PL/SQL Procedures for ODM Model Migration
- System Privileges Needed for Exporting and Importing ODM Models
- Exporting an ODM Model
- Importing and the ODM Model
- Dropping an ODM Model
- Renaming an ODM Model
- Summary
- Chapter 20: Implementation-Related Topics
- How to Add Your ODM Models to Your OBI Dashboards
- Importing the ODM Model
- Creating a View to Include the ODM Model
- Importing the View to the Physical Layer of the BI Repository (RPD)
- Adding New Columns to the Business Model Layer
- Adding to the OBI Dashboards
- How to Build and Apply ODM Models in Parallel
- How to Run Your ODM Workflows and ODM Models in Parallel
- How to Run Your ODM Model in Real Time Using Parallel Query
- How to Run Your ODM Model in Batch Mode Using Parallel Query
- Predictive Queries
- Summary
- Index
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