Explain k-fold cross-validation and stratified cross-validation. Why is cross-validation important, and what are its variations?

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Cross-validation is a resampling technique that provides robust estimates of model performance by training and evaluating the model multiple times on different subsets of the data. It addresses limitations of single train-test splits.