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Predicting Continuous Targets Using IBM SPSS Modeler

 

Overview

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Predicting Continuous Targets Using IBM SPSS Modeler is an intermediate level course that provides an overview of how to use IBM SPSS Modeler to predict a target field that describes numeric values. Students will be exposed to rule induction models such as CHAID and C&R Tree. They will also be introduced to traditional statistical models such as Linear Regression. Machine learning models will also be presented. Business use case examples include: predicting the length of subscription (for newspapers, telecommunication, job length, and so forth) and predicting claim amount (insurance).

Prerequisites

Additional Courses

Follow-On Course

Key Topics

Introduction to Predicting Continuous Targets

  • List modeling objectives
  • List business questions that involve predicting continuous targets
  • Explain the concept of field measurement level and its implications for selecting a modeling technique
  • List types of models to predict continuous targets
  • Determine the classification model to use

Building Your Tree Interactively

  • Explain how CHAID grows a tree
  • Explain how C&R Tree grows a tree
  • Build CHAID and C&R Tree models interactively
  • Evaluate models for continuous targets
  • Use the model nugget to score records

Building Your Tree Directly

  • Customize options in the CHAID node
  • Customize options in the C&R Tree node
  • List differences between CHAID and C&R Tree

Using Traditional Statistical Models

  • Explain key concepts for Linear
  • Customize options in the Linear node
  • Explain key concepts for Cox
  • Customize options in the Cox node

Using Machine Learning Models

  • Explain key concepts for Neural Net
  • Customize options in the Neural Net node

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