k-fold cross-validation means to split data into k subsets, and train models on k-1 subsets...
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k-fold cross-validation means to split data into k subsets, and train models on k-1 subsets while leaving one set out for evaluation. In which of the following situations is cross validation generally unnecessary?
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Answer: A. Optimizing the depth of a decision tree for a random forest model.
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