Answer-first summary for fast verification
Answer: k=5
The correct answer is k=5 (option C) as it is the most commonly used default value for k-fold cross-validation in practice, especially with limited data samples. Community discussion shows strong consensus (67% selected C) with multiple comments noting that typical k values are 5 or 10. The Microsoft documentation reference and machine learning best practices support k=5 as a standard choice that balances bias-variance tradeoff while being computationally efficient. Option B (k=0.01) is invalid as k must be an integer ≥2. Option A (k=0.5) is also invalid for the same reason. Option D (k=1) would be leave-one-out cross-validation, which is computationally expensive and not practical for limited data scenarios.
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You are solving a classification task and need to evaluate your model on a limited data sample using k-fold cross-validation. You start by configuring the k parameter as the number of splits.
Which value should you use for the k parameter?
A
k=0.5
B
k=0.01
C
k=5
D
k=1