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Intelligent Miner Help: Contents

   About the Intelligent Miner

Creating and defining objects

Preparing data using processing functions

Mining your data

Analyzing your data using statistical functions

Automating the mining process using sequences

Index

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Intelligent Miner Help: Index

Navigate through the index by clicking on the letters below:

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Table of Contents
= kR\ L5p5q5 W./usr/lpp/IMiner/html/idmblabt.htm Introduction to Intelligent Miner Help  
Where to find information about the Intelligent Miner
   

Online Help System
 
The Intelligent Miner online help contains detailed information on the functions, parameters, settings, and input and output data used in the Intelligent Miner. The help system provides example and sample data for each function or feature. Information on how to perform a specific task in the Intelligent Miner is included in the TaskGuide windows on the products. These windows lead you through tasks step by step, providing instructions for using the TaskGuide on each page. When you need more information, click on the Help button and the online help window for the task will open. The online help supplies reference information that will help you understand the concept associated with the task and how your data can be used in the task.

There are two types of help pages for most pages of a TaskGuide: Concepts and examples and Valid values.
 
Concepts and examples Shown with titles in a yellow background and denoted by the yellow button
 

Concepts and examples pages provide discussion on theoretical and abstract concepts and explain how they relate to the functions of the Intelligent Miner and your data. These pages provide sample scenarios of how data can be used. They include example data and hints and tips.
 
Valid values and actions Shown with titles in a green background and denoted by the green button
 
Valid values and actions pages specify what type of data you can use with the function or feature. It supplies a grid that lists several fields of the Intelligent Miner GUI and describes the type of data appropriate for each field.
 

Printed Book: Using the Intelligent Miner for data

This book, which is also supplied online, will give you information on installing and running intelligent miner and introduce you to its features. It describes the graphical user interface (GUI) in detail. The user's manual is an excellent source of information when you begin using the product, and as a reference for specific information about parameters, functions, concepts, and values. The book will also guide you through a simple scenario using the Intelligent Miner. It also covers interpereting the results of the data after a mining run. The book also contains a glossary of terms that are commonly associated with data mining and those specific to the Intelligent Miner.

Also included with the Intelligent Miner is an HTML version of the user's manual. This is simply an electronic format for the paper book.

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   d ks!iM5p5q5 Xi./usr/lpp/IMiner/html/idmbnotc.htm Notices  
Notices  
   
References in this publication to IBM products, programs, or services do not imply that IBM intends to make these available in all countries in which IBM operates. Any reference to an IBM product, program, or service is not intended to state or imply that only IBM's product, program, or service may be used. Any functionally equivalent product, program, or service that does not infringe any of IBM's intellectual property rights may be used instead of the IBM product, program, or service. Evaluation and verification of operation in conjunction with other products, except those expressly designated by IBM, is the user's responsibility.

Licensees of this program who wish to have information about it for the purpose of enabling; (i) the exchange of information between independently created programs and other programs (including this one) and (ii) the mutual use of the information which has been exchanged, should contact IBM Deutschland Informationssysteme GmbH, Department 3982, Pascalstrasse 100, 70569 Stuttgart, Germany. Such information may be available, subject to appropriate terms and conditions, including in some cases, payment of a fee.

IBM may have patents or pending patent applications covering subject matter in this document. The furnishing of this document does not give you any license to these patents. You can send license inquiries, in writing, to the IBM Director of Licensing, IBM Corporation, 500 Columbus Avenue, Thornwood NY 10594, U.S.A.

The Intelligent Miner incorporates code generated by the Purdue Compiler Construction Tool Set (PCCTS).

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US Government Users Restricted Rights - Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Author" k(Y"%M5p5q5 Z%./usr/lpp/IMiner/html/idmbp99o.htm idmba01.htm-CorrelationMatricesBasic  
Create settings from output data

Key:
Concepts and examples
Valid values and actions
Help contents

Index ly k,#o$M5p5q5 [o$./usr/lpp/IMiner/html/idmbtoc.htm Table of Contents Page. Intelligent Miner
TaskGuide Table of Contents    


About the Intelligent Miner
Where to find information about the Intelligent Miner
Using the main window
Using the preferences notebook
Creating and defining data objects:
Connecting to data
Database table
Database view
Flat files
Mapping data names
Using existing data
Mapping names manually
Mapping data values
Using existing data
Mapping data manually
Creating taxonomy (classification) relationships
Using existing data
Manually creating taxonomy relationship
Separating data into categories (discretization)
Creating discretization using existing data
Manually create a discretization
Preparing data using processing functions
Aggregating values
Calculating values
Cleaning up data sources (deleting data sources)
Converting uppercase to lowercase (or vice versa)
Copying records to a file
Discarding records with missing values
Discretizing into quantiles
Discretizing using ranges
Encoding missing values
Encoding nonvalid values
Filtering fields
Filtering records
Filtering records using a value set
Getting a random sample
Grouping records
Joining data sources
Mapping values
Pivoting fields to records
Running SQL
Mining your data
Discovering associations
Discovering basic associations between data
Discovering advanced associations between data
Discovering clusters
Discovering basic demographic clusters
Discovering advanced demographic clusters
Using basic neural networks
Using advanced neural networks
Discovering sequential patterns
Discovering basic sequential patterns
Discovering advanced sequential patterns
Discovering similar time sequences
Discovering basic similar time sequences
Discovering advanced time sequences
Predicting classifications
Using basic neural networks
Using advanced neural networks
Predicting basic classifications using tree-induction
Predicting advanced classifications using tree-induction
Predicting values
Using basic neural networks
Using advanced neural networks to predict values
Using basics of the Radial Basis Function (RBF)
Advanced use of the RBF
Analyzing your data using statistical functions
Bivariate statistics
Basic bivariate statistics
Advanced bivariate statistics
Correlation matrices
Basic correlation matrices
Advanced correlation matrices
Cross-correlation
Basic cross-correlation
Advanced cross-correlation statistics
Factor analysis
Basic factor analysis
Advanced factor analysis
Linear regression
Basic linear regression
Advanced linear regression
Principal component analysis
Basic principal component analysis
Advanced principal component analysis
Univariate curve fitting
Basic univariative curve fitting
Advanced univariative curve fitting
Automating the mining process using sequences
Creating a sequence

" k4$gM5p5q5 ^g./usr/lpp/IMiner/html/idmbwn00.htm Intelligent Miner help Name mapping
  1. Create a name mapping using existing input data
  2. Create a name mapping manually

Index o kQ%[M5p5q5 _[./usr/lpp/IMiner/html/idmbwt00.htm Intelligent Miner help Taxonomy

  1. Create a taxonomy using existing input data
  2. Create a taxonomy manually

Index DY> < k:&jM5p5q5 `j./usr/lpp/IMiner/html/idmbwv00.htm Intelligent Miner help Value mapping

  1. Create a value mapping using existing input data
  2. Create a value mapping manually

Index ting tkss&jM5p5q5 `j./usr/lpp/IMiner/html/idmbwv00.htm Intelligent Miner help Value mapping

  1. Create a value mapping using existing input data