What is Cross-validation in FRM Part 1?

Repeatedly training and validating a model on different data folds to estimate out-of-sample performance and tune complexity. All preprocessing and feature selection must occur inside each training fold to avoid information leakage.

Cross-validation

FRM Part 1 glossary · Quantitative Analysis

Definition

Repeatedly training and validating a model on different data folds to estimate out-of-sample performance and tune complexity.

Cross-validation in plain English

All preprocessing and feature selection must occur inside each training fold to avoid information leakage.

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Machine learning

Related FRM Part 1 terms

Bayes' theorem
Bootstrapping (term structure)
Central limit theorem
Copula
Exponentially weighted moving average (EWMA)
Generalized Autoregressive Conditional Heteroskedasticity (GARCH)
Heteroskedasticity
Monte Carlo simulation
Ordinary least squares (OLS)
p-value

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