فهرست مطالب

• About This Book
• About the Author
• Acknowledgements
• Foreword
• Chapter 1: Introduction to Tree-Structured Models
• Introduction
• Tree-Based Models in SAS Viya
• Introducing Model Studio
• Quiz
• Chapter 2: Classification and Regression Trees
• Classification Trees
• Regression Trees
• Quiz
• Chapter 3: Growing a Decision Tree
• Recursive Partitioning
• Alternatives to Recursive Partitioning
• Constructing Decision Trees Interactively
• Feature Selection Using Split Search
• Split Points
• Splitting Criteria
• Quiz
• Chapter 4: Decision Trees: Strengths, Weaknesses, and Uses
• Missing Values in Decision Trees
• Variable Importance
• Strengths and Weaknesses of Decision Trees
• Secondary Uses of Decision Trees
• Quiz
• Chapter 5: Tuning a Decision Tree
• Model Complexity and Generalization
• Pruning Requirements
• Autotuning
• Quiz
• Chapter 6: Ensemble of Trees: Bagging, Boosting, and Forest
• Instability in a Decision Tree
• Ensemble Models
• Forest Models
• Tuning a Forest Model
• Quiz
• Chapter 7: Additional Forest Models
• Open-Source Random Forest Models
• Isolation Forest Models
• Introduction to Deep Forest Models
• Quiz
• Chapter 8: Tree-Based Gradient Boosting Machines
• Gradient Boosting Models
• Key Components of Gradient Boosting
• Tuning a Gradient Boosting Model
• Quiz
• Chapter 9: Additional Gradient Boosting Models
• Gradient Boosting for Transfer Learning
• Gradient Boosted Poisson and Tweedie Regression Trees
• SAS Gradient Boosting Using Open Source
• Quiz
• Appendix A: Practice Case Study
• References