What are the parameters for k-fold cross-validation?
An example of an AI chatbot conversation about k-fold cross-validation parameters.
What are the parameters for k-fold cross-validation?
K-fold cross-validation involves several key parameters: the number of folds (k), the random seed, and the scoring metric.
How do I choose the value of k?
A common practice is to use k=5 or k=10, but it can depend on the size of your dataset. Larger datasets can use higher k values.
What happens if k is too high?
If k is too high, it can lead to longer computation times and may result in overfitting, as the model is trained on very similar data.
Can you explain the random seed parameter?
The random seed ensures that the randomization process is reproducible. Setting it to a fixed value allows for consistent results across runs.
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