A classifier has high training accuracy but poor representative validation performance. Which approach best fits?

1. Use metrics such as precision, recall, and PR analysis appropriate to the business costs.
2. Reserve a final independent test set and use validation data for model selection.
3. Choose and validate a decision threshold aligned with recall and false-positive costs.
4. Investigate overfitting and use appropriate regularization or data improvements.