Cross-validatory choice and assessment of statistical predictions

Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society: Series B (Methodological), 36(2), 111-147.

Type

Journal article

Intellectual base

Primary research

Year

1974

Link

https://doi.org/10.1111/j.2517-6161.1974.tb00994.xmatched

Cited from

statistics_experimental_design

Cited by

2 citations across 2 artifacts.

Each citation links to the sentence it supports in the citing article.

Primes

• Overfitting
  • Supports disciplined modeling: out-of-sample testing, cross-validation, and regularization are deliberate responses to overfitting risk

    This sourceFoundational paper formalizing cross-validation, holdout sets, and predictive-error estimation as the core machinery of model validation in statistics and machine learning.

• Validation
  • Machine learning & statistics: Holdout validation sets; cross-validation to estimate model generalization, as Stone (1974) formalized in his foundational treatment; testing on held-out temporal windows (time-series validation); out-of-distribution (OOD) validation to check behavior on unfamiliar inputs; calibration validation (checking whether predicted probability matches observed frequency).

    This sourceFoundational paper formalizing cross-validation, holdout sets, and predictive-error estimation as the core machinery of model validation in statistics and machine learning.

Verification

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