In a situation where you have limited data, how would you decide between using Cross-Validation or Bootstrapping, and why?
- Always use Bootstrapping
- Always use Cross-Validation
- Choose based on computational resources
- Choose based on the model, the nature of the data, and the analysis objectives
Deciding between Cross-Validation and Bootstrapping when dealing with limited data depends on the model, the nature of the data, and the analysis objectives. Cross-Validation provides robust validation by utilizing all data for both training and validation, while Bootstrapping can offer statistical insights. The decision should be tailored to the specific scenario.
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