Скачать или смотреть Can Cross-Validation Estimate Generalization Error?

This video explores a fundamental question in machine learning: can cross-validation truly provide an accurate estimate of a model's generalization error? We'll dive into the nuances of this widely used technique to understand its capabilities and limitations in predicting real-world performance.

In this video, we will discuss:
► Understanding what generalization error represents in machine learning models.
► The role of cross-validation as a technique for model evaluation and hyperparameter tuning.
► Key factors that influence cross-validation's accuracy in estimating out-of-sample performance.
► Potential pitfalls and common misconceptions when interpreting cross-validation results.


#CrossValidation, #MachineLearning, #GeneralizationError, #StatisticalLearning, #ModelEvaluation, #DataScience