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PJF-004 information that is not present in the data. This can lead to overfitting and a less generalizable model. **Recommendation:** 1. **Check for data imbalance:** Ensure that the number of classes in the dataset is not biased. If there is a high imbalance, consider using techniques such as oversampling, under sampling, or weighting to balance the dataset. 2. **Use regularization techniques:** This will prevent overfitting and make the model more generalizable. 3. **Enhance training:** Increase the number of epochs, increase the batch size, or evaluate the base model to determine if it is suitable for the task.

2003年5月16日60 分钟