Bias in Error Estimation when Using Cross-validation for Model Selection¶
Varma, S., & Simon, R. (2006). Bias in Error Estimation when Using Cross-validation for Model Selection. BMC Bioinformatics, 7(91).
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Primes¶
- Holdout Set
- The single-use accounting is the formal corrective — each peek spends evaluative power, and nested cross-validation (an outer fold protecting against inner-fold leakage) is the bookkeeping that tracks the erosion.
This sourceDemonstrates the optimistic bias of using one cross-validation loop for both selection and evaluation, and that nested cross-validation (an outer fold) gives an unbiased estimate — the bookkeeping of holdout erosion.
- The single-use accounting is the formal corrective — each peek spends evaluative power, and nested cross-validation (an outer fold protecting against inner-fold leakage) is the bookkeeping that tracks the erosion.
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