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Clustering and Association Modeling Using IBM SPSS Modeler (V16)


Course Description


Overview

Clustering and Association Modeling Using IBM SPSS Modeler (v16) is a one day, instructor-led course that is designed to introduce participants 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.  

Audience

This course is for IBM SPSS Modeler Analysts who want to become familiar with the full range of modeling techniques available in IBM SPSS Modeler to segment (cluster) data and to create models using association or sequence data.

Prerequisites

You should have Experience using IBM SPSS Modeler, including a familiarity with the IBM SPSS Modeler environment, creating streams, reading in data files, assessing data quality and handling missing data (including Type and Data Audit nodes, basic data manipulation including Derive and Select nodes), andcreation of models.

Key topics

Introduction to Association and Cluster Modeling
  • Modeling Techniques
  • Clustering Types
  • Association Rules
  • Sequence Detection
  • Which Technique, and When?
Clustering Techniques and K-Means Clustering
  • Cluster Analysis and Principles
  • Explore K-Means Clustering
  • Examine the K-Means Node
  • Explore Clustering Profiles
Clustering Techniques and K-Means Clustering
  • Clustering with a Kohonen Network
  • Examine the Kohonen Node
Clustering Techniques and K-Means Clustering
  • TwoStep Clustering
  • Examine the TwoStep algorithm
  • The TwoStep Node
Association Rules
  • Examine the Apriori association detection algorithm
  • Rule and Measure Formats
  • Explore the Apriori Model Node dialog
  • Identify browsing rules and display statistics
  • Use the Associations
  • Explore the Generate Ruleset dialog
  • Examine the Ruleset in a stream
Advanced Association Rules
  • Advanced Association Rules
  • Explore the Apriori algorithm
  • Explore the Carma algorithm
  • Apriori Expert Options
  • Explore Apriori Evaluation Measures
  • Carma Expert Options
  • Choose a method and Expert Options
  • Missing Data with Association Rules
Sequence Detection
  • Examine Sequences
  • Examine the Sequence Node
  • Explore Sequence Rulesets
  • Rule support
  • Sorting Rulesets
  • Supernodes
  • Export Rules
Advanced Sequence Detection
  • Explore the Sequence Node
  • Identify Sequence Node options
  • Examine Expert options
  • Examine Time field guidelines
  • Generate Sequence Results
  • Generate and edit the Ruleset
  • Explore the results

Objectives

Please refer to Course Overview for description information.

Course Duration

1 day
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