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4 cards from this section. Quick, good the night before a test.
What is cross-validation?
Think about how we test models.
What is the purpose of K-Fold Cross-Validation?
What does splitting data accomplish?
What method is used to evaluate a model using multiple data subsets?
It's a technique to test reliability.
K-Fold Cross-Validation divides data into how many parts?
Remember the variable K.
Create a comprehensive plan to implement K-Fold Cross-Validation on a dataset of your choice, outlining the number of folds and justifying your choice.
Think about how many folds provide a good mix of training/testing data.
Evaluate a case where K-Fold Cross-Validation might not be beneficial. Provide justifications based on data characteristics.
Consider the size and diversity of your data.
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