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Machine Learning and AI Foundations: Decision Trees with SPSS

Via LinkedIn Learning

LinkedIn Learning based on 387 ratings

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Overview

"Machine Learning and AI Foundations: Decision Trees with SPSS" is a practical course designed to introduce learners to one of the most fundamental and interpretable machine learning techniques—decision trees—using IBM SPSS software. This course is ideal for data analysts, business professionals, and students who want to build predictive models without deep programming expertise. Participants will learn the core concepts behind decision trees, including how they split data based on feature values to make predictions for classification and regression problems. The course...

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
Machine Learning and AI Foundations: Decision Trees with SPSS
Go to Class

via LinkedIn Learning

2 hours

Certificate Available

English

On-Demand

Instructor

Keith McCormick

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