Assessing Model Accuracy
Free SOA Exam SRM (Statistics for Risk Modeling) lesson in Basics of Statistical Learning. 13 min read, ~1,944 words.
Training error always falls as flexibility rises; test error is U-shaped. Minimize test error, not training error. Regression uses mean squared error (MSE); classification uses misclassification rate, ROC/AUC, or log-loss. k-fold cross-validation (typically k=5 or k=10) is the workhorse. LOOCV is k=n: low bias, high variance, expensive. Test MSE decomposes...
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What this lesson covers
- Content
- Example 1
- Example 2
- Example 3
- Example 4
- Common Mistakes
- Key Takeaways
- Exam Shortcuts
Learning objectives
- 1b
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