Explain K-Fold Cross-Validation and Its Trade-Offs

Q: Explain K-Fold Cross-Validation and Its Trade-Offs

This question evaluates a candidate's understanding of k-fold cross-validation and related competencies in model evaluation, including reasoning about bias–variance trade-offs, computational cost, and pitfalls such as data leakage, temporal/ordered data, and class imbalance.

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Question

Technical Phone Screen: Cross-Validation

Task

You are interviewing for a Data Scientist role. Explain and reason about k-fold cross-validation.

Questions

Describe the k-fold cross-validation procedure concisely.
What are the trade-offs in choosing the number of folds k (bias–variance, compute, stability)?
In what situations can cross-validation give misleading performance estimates? Discuss the roles of data leakage, temporal/ordered data, and class imbalance.

Explain K-Fold Cross-Validation and Its Trade-Offs

Technical Phone Screen: Cross-Validation

Task

Questions

Solution

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