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课程大纲
   
 
  • 课程介绍
    In this course, students review the basic concepts of data mining and learn how leverage the predictive analytical power of the Oracle Database Data Mining option by using Oracle Data Miner 11g Release 2. The Oracle Data Miner GUI is an extension to Oracle SQL Developer 3.0 that enables data analysts to work directly with data inside the database.
    The Data Miner GUI provides intuitive tools that help you to explore the data graphically, build and evaluate multiple data mining models, apply Oracle Data Mining models to new data, and deploy Oracle Data Mining's predictions and insights throughout the enterprise. Oracle Data Miner's SQL APIs automatically mine Oracle data and deploy results in real-time. Because the data, models, and results remain in the Oracle Database, data movement is eliminated, security is maximized and information latency is minimized.

    课程对象: Oracle数据库技术人员

  • 课程大纲:

            Introduction
                Course Objectives
                Suggested Course Pre-requisites
                Suggested Course Schedule
                Class Sample Schemas
                Practice and Solutions Structure
                Review location of additional resources (including ODM and SQL Developer documentation and online resources)
           Overviewing Data Mining Concepts
                What is Data Mining?
                Why use Data Mining?
                Examples of Data Mining Applications
                Supervised Versus Unsupervised Learning
                Supported Data Mining Algorithms and Uses
           Understanding the Data Mining Process
                Common Tasks in the Data Mining Process
           Introducing Oracle Data Miner 11g Release 2
                Data mining with Oracle Database
                Introducing the SQL Developer interface
                Setting up Oracle Data Miner
                Accessing the Data Miner GUI
                Identifying Data Miner interface components
                Examining Data Miner Nodes
                Previewing Data Miner Workflows
           Using Classification Models
                Reviewing Classification Models
                Adding a Data Source to the Workflow
                Using the Data Source Wizard
                Creating Classification Models
                Building the Models
                Examining Class Build Tabs
                Comparing the Models
                Selecting and Examining a Model
           Using Regression Models
                Reviewing Regression Models
                Adding a Data Source to the Workflow
                Using the Data Source Wizard
                Performing Data Transformations
                Creating Regression Models
                Building the Models
                Comparing the Models
                Selecting a Model
           Performing Market Basket Analysis
                What is Market Basket Analysis?
                Reviewing Association Rules
                Creating a New Workflow
                Adding a Data Source to th Workflow
           Creating an Association Rules Model
                Defining Association Rules
                Building the Model
                Examining Test Results
           Using Clustering Models
                Describing Algorithms used for Clustering Models
                Adding Data Sources to the Workflow
                Exploring Data for Patterns
                Defining and Building Clustering Models
                Comparing Model Results
                Selecting and Applying a Model
                Defining Output Format
                Examining Cluster Results
           Performing Anomaly Detection
                Reviewing the Model and Algorithm used for Anomaly Detection
                Adding Data Sources to the Workflow
                Creating the Mode
                Building the Model
                Examining Test Results
                Applying the Model
                Evaluating Results
           Deploying Data Mining Results
                Requirements for deployment
                Deployment Tasks
                Examining Deployment Options

 

 
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