Machine Learning and AI Foundations: Decision Trees with SPSS

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.

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