Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

LinkedIn Learning

Machine Learning and AI Foundations: Decision Trees with SPSS

via LinkedIn Learning

Write review
Coursera Ad

Learn AI, Data Science & Business — Earn Certificates That Get You Hired

Learn More → Scrimba Ad

Get 20% off all career paths from fullstack to AI

Learn More →

Overview

Google, IBM & Meta Certificates – 40% Off
One plan covers every Professional Certificate on Coursera.
Unlock All Certificates
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

Reviews

4.4 rating at LinkedIn Learning based on 283 ratings

Start your review of Machine Learning and AI Foundations: Decision Trees with SPSS

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free
Someone learning on their laptop while sitting on the floor.