IBM 0A047G - Clustering and Association Modeling Using IBM SPSS Modeler (v18)

1: Introduction to clustering and association models- 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 data2: 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 node3: Clustering using the Kohonen network- Identify the basic characteristics of the Kohonen network- Understand how to configure a Kohonen node- Model a Kohonen network4: Clustering using TwoStep clustering- Identify the basic characteristics of TwoStep clustering- Identify the basic characteristics of Two Step AS clustering- Model and analyze a TwoStep clustering solution5: 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 rules6: 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 Apriori7: Sequence detection- Explore sequence detection association models- Identify sequence detection methods- Examine the Sequence node- Interpret the sequence rules and add sequence predictions to steams8: 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 dataA: Examine learning rate in Kohonen networks (Optional)- Understand how a Kohonen neural network learnsB: Association using the Carma model (Optional)- Review association rules- Identify the Carma model- Identify the Carma node- Model associations and generate rules using Carma