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.
Machine Learning and AI Foundations: Decision Trees with SPSS
Overview
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
