Clustering and Association Modeling Using IBM SPSS Modeler v18.1.1 0A048G

Modelers, Analysts

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

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

• Identify three methods of generating association rules

Interpret association rules

• Identify association modeling terms and rules

• Identify evaluation measures used in association modeling

• Identify the capabilities of the Association Rules node

• 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