Decision Trees vs Linear Models
Free SOA Exam SRM (Statistics for Risk Modeling) lesson in Decision Trees. 14 min read, ~2,047 words.
Linear models assume a global additive functional form; trees partition the predictor space into rectangles with a constant prediction inside each. The form drives every strength and weakness. Trees handle non-linearities, interactions, and mixed predictor types automatically; linear models need explicit transformations, dummy coding, and interaction terms. Linear models extrapolate...
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What this lesson covers
- Content
- Example 1
- Example 2
- Common Mistakes
- Key Takeaways
- Exam Shortcuts
Learning objectives
- 4d
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