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Classroom Contents
A Guide to Cross-Validation for AI - Avoiding Overfitting and Ensuring Generalizability
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- 1 Introduction
- 2 Overfitting vs. generalizability
- 3 Pitfalls of using one-time split method
- 4 Pitfall #1: Non-representative test set
- 5 Pitfall #2: Tuning to the test set
- 6 Cross-validation
- 7 Important note: in CV we are testing pipeline, not a single model
- 8 K-fold, folded test set
- 9 K-fold, hold-out test-set
- 10 Nested cross-validation
- 11 leave-one-out
- 12 random sampling
- 13 selecting an approach: pros and cons
- 14 Final thoughts
