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Difficulty: Easy
Category: Linear Algebra & Machine Learning
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Topics: machine-learning, cross-validation, model-evaluation
You are building a trading model to predict daily stock returns. You have a limited dataset of historical stock prices. You want to evaluate how well your model generalizes to unseen data. What is the main problem that k-fold cross-validation addresses compared to using a single train/test split?
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