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Learn cross-validation techniques for model evaluation and selection in this university lecture that explores fundamental questions about what constitutes a good statistical model and how to choose optimal parameters like polynomial degree in regression analysis. Discover the train/test split methodology for assessing model performance and understand when to implement a three-way train/validation/test split approach for both model selection and generalization assessment. Master essential concepts in data analysis that help prevent overfitting and ensure robust model performance on unseen data.
