Decision Trees vs Linear Models
Free SOA Exam SRM (Statistics for Risk Modeling) lesson in Decision Trees. 14 min read, ~2,125 words.
Linear models fit a global additive form; trees fit a piecewise-constant, partitioning predictors into rectangles. 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. Trees process categorical predictors and missing values natively (via...
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What this lesson covers
- Content
- Example 1
- Example 2
- Common Mistakes
- Check Your Understanding
- Exam Shortcuts
Learning objectives
- 4d
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