Cross-validation
/krɒs ˌvælɪˈdeɪʃən/
Definition
A technique splitting data into k folds and training/evaluating k times to get a robust performance estimate.
Example in context
"5-fold cross-validation gives five accuracy scores — we report the mean and standard deviation, not just one split."
Related terms
Practice this term
Master Cross-validation in context by working through exercises in the Data Science & ML module. You'll see the term used in real engineering scenarios with multiple-choice, fill-in-the-blank, and matching drills.