Machine Learning and AI: Advanced Decision Trees with SPSS

Work toward a mastery of machine learning by exploring advanced decision tree algorithm concepts. Learn about the QUEST and C5.0 algorithms and a few advanced topics.

Introduction

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

1. Understanding QUEST

• Overview
• How QUEST handles nominal variables
• How QUEST handles ordinal and continuous variables
• How QUEST handles missing data
• Pruning in QUEST
• Stopping rules in QUEST

2. Understanding C5.0

• ID3 and C4.5
• Winnowing attributes
• Rule sets
• Understanding information gain
• Pruning in C5.0
• How C5.0 handles missing data

3. Advanced Topics

• Ensembles
• What is bagging?
• Using bagging for feature selection
• Random forests
• What is boosting?
• Costs and priors

Conclusion

• Next steps