What evaluation method involves training and testing multiple times across different data partitions to assess generalization?

What evaluation method involves training and testing multiple times across different data partitions to assess generalization?

• A. K-fold Cross-Validation
• B. Ridge Regression (L2 penalty)
• C. LASSO (L1 penalty)
• D. Elastic Net (L1 + L2 penalties)

Answer: (A)

Cross-validation is an evaluation approach that estimates how a model will perform on unseen data by repeatedly training and testing on different subsets of the data. In k-fold cross-validation, you divide the dataset into k equal parts, train the model on k−1 parts, and test it on the remaining part. This process is repeated k times so every part serves as a test set once, and the results are averaged. This repeated training and testing across diverse partitions gives a robust measure of generalization, helping to compare models and tune parameters without relying on a single train/test split. Regularization methods like Ridge, LASSO, and Elastic Net, on the other hand, modify the learning objective to penalize complexity; they relate to fitting the model rather than describing an evaluation procedure across multiple data partitions.

Cross-validation is an evaluation approach that estimates how a model will perform on unseen data by repeatedly training and testing on different subsets of the data. In k-fold cross-validation, you divide the dataset into k equal parts, train the model on k−1 parts, and test it on the remaining part. This process is repeated k times so every part serves as a test set once, and the results are averaged. This repeated training and testing across diverse partitions gives a robust measure of generalization, helping to compare models and tune parameters without relying on a single train/test split. Regularization methods like Ridge, LASSO, and Elastic Net, on the other hand, modify the learning objective to penalize complexity; they relate to fitting the model rather than describing an evaluation procedure across multiple data partitions.