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Schulung - IBM 0A048G - Clustering and Association Modeling Using IBM SPSS Modeler (v18.1.1)

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1 Tag ( 7 Stunden)

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1 Tag ( 7 Stunden)


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Overview

Clustering and Association Modeling Using IBM SPSS Modeler (v18.1.1) introduces modelers to two specific classes of modeling that are available in IBM SPSS Modeler: clustering and associations. Participants will explore various clustering techniques that are often employed in market segmentation studies. Participants will also explore how to create association models to find rules describing the relationships among a set of items, and how to create sequence models to find rules describing the relationships over time among a set of items.

Zielgruppe

Wer sollte teilnehmen:

Zielgruppe

Audience

Modelers, Analysts

Voraussetzungen

Prerequisites

• Experience using IBM SPSS Modeler
• A familiarity with the IBM SPSS Modeler environment: creating models, creating streams, reading in data files, and assessing data quality
• A familiarity with handling missing data (including Type and Data Audit nodes), and basic data manipulation (including Derive and Select nodes)

Trainingsprogramm

Trainingsprogramm

Course Outline

1: Introduction to clustering and association modeling 
Identify the association and clustering modeling techniques available in IBM SPSS Modeler 
Explore the association and clustering modeling techniques available in IBM SPSS Modeler 
Discuss when to use a particular technique on what type of data 


2: Clustering models and K-Means clustering 
Identify basic clustering models in IBM SPSS Modeler 
Identify the basic characteristics of cluster analysis 
Recognize cluster validation techniques 
Understand K-Means clustering principles 
Identify the configuration of the K-means node 


3: Clustering using the Kohonen network 
Identify the basic characteristics of the Kohonen network 
Understand how to configure a Kohonen node 
Model a Kohonen network 


4: Clustering using TwoStep clustering 
Identify the basic characteristics of TwoStep clustering 
Identify the basic characteristics of TwoStep-AS clustering 
Model and analyze a TwoStep clustering solution 


5: Use Apriori to generate association rules 
Identify three methods of generating association rules 
Use the Apriori node to build a set of association rules 
Interpret association rules

 

6: Use advanced options in Apriori 
Identify association modeling terms and rules 
Identify evaluation measures used in association modeling 
Identify the capabilities of the Association Rules node 
Model associations and generate rules using Apriori 


7: Sequence detection 
Explore sequence detection association models 
Identify sequence detection methods 
Examine the Sequence node 
Interpret the sequence rules and add sequence predictions to steams 


8: Advanced Sequence detection 
Identify advanced sequence detection options used with the Sequence node 
Perform in-depth sequence analysis 
Identify the expert options in the Sequence node 
Search for sequences in Web log data 


A: Examine learning rate in Kohonen networks (Optional) 
Understand how a Kohonen neural network learns 


B: Association using the Carma model (Optional) 
Review association rules 
Identify the Carma model 
Identify the Carma node 
Model associations and generate rules using Carma

Objective

  • Introduction to clustering and association modeling 
  • Clustering models and K-Means clustering 
  • Clustering using the Kohonen network 
  • Clustering using TwoStep clustering 
  • Use Apriori to generate association rules 
  • Use advanced options in Apriori 
  • Sequence detection 
  • Advanced Sequence detection 
  • Examine learning rate in Kohonen networks (Optional) 
  • Association using the Carma model (Optional) 

Schulungsmethode

Schulungsmethode

presentation, discussion, hands-on exercises

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Schulung - IBM 0A048G - Clustering and Association Modeling Using IBM SPSS Modeler (v18.1.1)