Mastering and Tuning Decision Trees

Description

IBM SPSS Modeler is a data mining workbench that allows you to build predictive models quickly and intuitively without programming. Analysts typically use SPSS Modeler to analyze data by mining historical data and then deploying models to generate predictions for recent (or even real-time) data.

Overview: Mastering and Tuning Decision Trees is a series of self-paced videos that discusses the decision tree methods (CHAID, C5.0, CRT, and QUEST) available in IBM SPSS Modeler. These techniques produces a rule based predictive model for an outcome variable based on the values of the predictor variables. Students will gain an understanding of the situations in which one would this technique, its assumptions, how to do the analysis automatically as well as interactively, and how to interpret the results. Particular emphasis is made on contrasting CHAID and C&RT in detail. Tuning – the adjusting of parameters to optimize performance – is demonstrated using both CHAID and C&RT.

What You Will Learn!

• Understand the theory behind classification trees
• Differentiate between classification tree algorithms
• Know the assumptions of classification trees
• Learn the advantage and disadvantages of the different algorithms
• Interpret the results

Who Should Attend!

• Anyone that has experience with IBM SPSS Modeler or has completed an introductory level data mining course and would like to learn about decision tree models.

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