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