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IRIX 6.5  »  Books  »  End-User  »  
MineSet™ Enterprise Edition User's Guide for the Windows® Client
(document number: 007-4005-002  /  published: 2000-11-29)   additional info | download

The MineSet User's Guide describes the features and capabilities of this suite of database mining and visualization tools. MineSet allows you to mine and graphically display quantitative information in ways that help you better understand your data. Current information about the MineSet product can be found on the Web at http://www.sgi.com/software/mineset.

table of contents (expand all | collapse all)  |  list of figures  |  list of tables  |  list of examples  |  list of procedures  |  

   Front Matter
 - About This Guide
       Audience for This Guide
       Finding MineSet Information
       Structure of This Document
       Illustrations in This Guide
       Further Reading
       Typographical Conventions
       Reader Comments
 - Chapter 1. Overview of Data Mining and MineSet Tools
       Data Mining Terminology
       About Data Mining and Data Mining Methods
     - Analytical Data Mining
         - Supervised Modeling
               Classification
               Regression
               Assessing the Accuracy of Models
         - Unsupervised Modeling
               Associations
               Clustering
       Visual Data Mining
       MineSet Tools for Data Mining
     - Surveying the Data Mining Process
           Identifying the Data
         - Preparing the Data
               Transforming the Data
           Building a Model
           Evaluating a Model
           Deploying a Model
 - Chapter 2. Accessing Data with MineSet
       Where to Find MineSet
       How the MineSet Software Works
       MineSet and Your Application
       System Settings for Optimum Visual Displays
       Starting MineSet
       Using the Tool Manager Window
     - Viewing the Raw Records with Record Viewer
           Changing Record Viewer Columns
           Filtering Data in Record Viewer
           Saving Data in Record Viewer
     - Seeing Record Statistics with the Statistics Visualizer
           Understanding Box Plots
           Understanding Histograms
     - Starting the Statistics Visualizer
           Working with Sample Data Files
       Starting the Histogram Visualizer
     - Navigating in the MineSet 3D Visualizers
           Navigating in the Tree Visualizers
           Navigating in Non-Tree Visualizers
       Brushing in the 3DVisualizer Window
       Viewing Multiple Documents in the 3DVisualizer Window
       Getting Help
 - Chapter 3. Shaping the Data
       Why Shape the Data?
     - Transforming Data with the Tool Manager
           Removing and Adding Columns
           Changing or Creating New Bins for Columns
           Creating New Columns by Aggregation
           Restricting Column Contents by Filtering
         - Changing a Column Type or Name
               Changing a Column Type
               Changing a Column Name
           Applying a Model
           Sampling Data
       Retracing Your Steps with Table History
       Weighting Records
       Finding Important Columns
 - Chapter 4. Examining Data with the Scatter and Splat Visualizers
     - Overview of the Scatter and Splat Visualizers
           Overview of the Scatter Visualizer
           Overview of the Splat Visualizer
     + Transforming the Data for the Scatter and Splat Visualizers
     - Starting the Scatter and Splat Visualizers
           Dragging and Dropping Existing Visualization Files
           Mapping the Scatter Visualizer Visual Elements
           Mapping the Splat Visualizer Elements
           Viewing Categorical Data in the Splat Visualizer
     - Examining Results in the Scatter and Splat Visualizers
         - Viewing Modes
               Select Mode in the Scatter Visualizer
               Select Mode in the Splat Visualizer
         - Creating Sliders for the Scatter Visualizer
               Automatic Slider Creation
               Manual Slider Creation
     - Creating Animations in the Scatter and Splat Visualizers
           Animating Using the Visualizer Summary Window
           Showing Animation Trails in the Scatter Visualizer
           Animating in the Splat Visualizer
         - Interpreting the Summary Window in the Splat Visualizer
               Color Density in the Summary Window
               Creating a Path in the Summary Window
     - Manipulating Scatter and Splat Visualizer Results
           Changing the Displays
           Selecting and Drilling Through in the Scatter Visualizer
           Changing the Scatter Visualizer Display with the Shape Menu
           Changing the Splat Visualizer Display with the Shape Menu
 - Chapter 5. Examining Data with the Tree Visualizer
       Overview of the Tree Visualizer
     - Starting the Tree Visualizer
           Dragging and Dropping Existing Visualization Files
           Mapping the Tree Visualizer Visual Elements
     - Examining Your Results with the Tree Visualizer
           Tree Visualizer Example
         - Getting a Closer Look at Your Data in the Tree Visualizer
               Highlighting an Object or Node
               Selecting an Object
           Seeing the Whole Picture with Overview
           Finding Specific Objects with the Search Panel
           Flagging Important Locations with the Marks Panel
           Filtering the Data with the Filter Panel
       Fine-Tuning the Tree Visualizer Display
 - Chapter 6. Examining Data with the Map Visualizer
       Overview of the Map Visualizer
     - Starting the Map Visualizer
           Dragging and Dropping Existing Visualization Files
     - Preparing the Data
           Aggregating the Data
           Choosing the Map Shapes
         - Linking the Map Visualizer Elements
               Mapping to Sliders
               Mapping to Maps
     - Examining the Map Visualizer
         - Viewing Modes
               Drilling Up and Drilling Down
               Visualizing Null Data
       Creating an Animation in the Map Visualizer
     - Manipulating the Map Visualizer Results
           Changing the Map Visualizer Display
           Selecting and Drilling Through
 - Chapter 7. Understanding Predictive Modeling
       Overview of Predictive Modeling
     - Generating a Model
           Evidence Model
           Decision Tree Model
           Option Tree Model
           Decision Table Model
           Regression Tree Model
     - Evaluating a Predictive Model
           Classifying Using All Your Data
           Holdout Error Estimation
           Cross-Validation Error Estimation
           Creating a Learning Curve
     - Applying a Predictive Model
           Selecting a Model
           Applying a Model
       Where to Go from Here
 - Chapter 8. Modeling and Predicting with Decision, Option, and Regression Trees
     - Overview of Decision, Option, and Regression Trees
           The Decision Tree
           Option Tree
           Regression Tree
     - Starting the Decision, Option, and Regression Trees
           Dragging and Dropping Existing Visualization Files
     + Examining Your Results with the Decision Tree Visualizer
       Examining Your Results with the Option Tree Visualizer
     - Examining Your Results with the Regression Tree Visualizer
           Predicting Values Using the Regression Tree Main Window
           Error Estimation in Regression Tree
           Other Useful Options
       Predicting with Decision, Option, and Regression Trees
 - Chapter 9. Modeling and Predicting with the Decision Table Classifier and Visualizer
       Overview of the Decision Table Classifier
     - Starting the Decision Table
           Dragging and Dropping Existing Visualization Files
     - Examining Your Results with the Decision Table Visualizer
           Examining the Decision Table Pane
           The Label Probability Pane
           Decision Table Example
       Predicting with Decision Table
 - Chapter 10. Modeling and Predicting with the Evidence Classifier and Visualizer
     - Overview of the Evidence Classifier and Visualizer
           The Evidence Visualizer Window
     - Starting the Evidence Tool
           Dragging and Dropping Existing Visualization Files
     - Examining Your Results with the Evidence Visualizer
         + Evidence View
           Probability View
           Bar View
           Changing the Evidence Visualizer Views
       Predicting with the Evidence Classifier
 - Chapter 11. Refining Predictive Modeling
     - Ensuring the Accuracy of Models
           Testing the Model
           Fitting Data to a Model
           Backfitting in Error Estimation
           Improving Accuracy with Boosting
     - Fine-tuning Models with the Confusion Matrix and Loss Matrix
           Using a Confusion Matrix to Investigate Errors
           Displaying a Confusion Matrix
           Defining a Loss Matrix
     - Assessing Models with the Lift Curve and ROI Curve
           Examining Prediction with a Lift Curve
           Finding Marketing Benefits Using a Return on Investment Curve
 - Chapter 12. Segmenting the Data with Clustering
       Overview of Clustering
     - Starting Clustering with Tool Manager
           Dragging and Dropping Existing Visualization Files
           Working with a Sample Clustering File
       Understanding the Cluster Visualizer Main Window
       Alternative Visualization of Clustering
 - Chapter 13. Analyzing Data with Association Rules
     - Overview of Association Rules Generation and Visualization
           Association Rules Generation
           Rules Visualization
     - Starting the Association Rules
           Setting Up Associations
           Dragging and Dropping Existing Visualization Files
           Record Weighting
           Mapping Rule Attributes to Visual Elements
       Interpreting Association Rules in the Scatter Visualizer
       Drilling Through
       Multiway Association Rules
   MineSet User's Glossary
   Index


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