You trained a model that looks strong on the data it saw during development, but the team is worried it may not generalize well to new data. You need to explain how you would tell whether the model is overfitting.
How would you determine whether a model is overfitting?
Gap between training and validation or test performanceCross-validation performance materially below training performanceValidation loss worsening while training loss keeps improvingLarge gains in complexity with little or no holdout improvement