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LinkedIn Learning

Machine Learning and AI Foundations: Decision Trees with SPSS

via LinkedIn Learning

Overview

Establish a strong foundation in ML by exploring the IBM SPSS Modeler and learning about CHAID and C&RT. This course is designed to help expand your data science skills.

Syllabus

Introduction

  • Welcome
  • What you should know
  • Using the exercise files

1. Decision Trees in IBM SPSS Modeler

  • Decision tree options in SPSS Modeler
  • Building a quick CHAID model
  • Adding a second model with C&RT
  • Analysis nodes
  • Lift and gains chart

2. Understanding CHAID

  • What is an algorithm?
  • Chi-squared overview
  • Buliding a tree interactively
  • Bonferonni adjustment
  • What is level of measurement?
  • How CHAID handles nominal variables
  • How CHAID handles ordinal variables
  • How CHAID handles continuous variables
  • A quick look at the complete CHAID tree

3. Understanding C&RT

  • What is the Gini coefficient?
  • How does C&RT weigh purity and balance?
  • How C&RT handles nominal, ordinal, and continuous variables
  • How C&RT handles missing data
  • Understanding pruning
  • A quick look at the complete C&RT tree

4. Improving Your Model

  • Stopping rules in CHAID and C&RT
  • Exhaustive CHAID
  • The Auto Classifier tuning trick

Conclusion

  • Next steps

Taught by

Keith McCormick

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