To ensure that the IVA learns from the training records and detects the correct topics and entities, apply the training changes to the text analytics model for the system. You apply changes to the model after you enable the training data recording, and then create and review the training records.

There are several guidelines to consider when you train the text analytics model for your chatbot. The approach that you take when training model-based entities is different than when you are building rule-based entities. By observing the guidelines for training text analytics models, you decrease the time it takes to train an IVA by improving the accuracy of the model, so that the system can more efficiently detect correct, relevant information in a conversation. For more information, see Best practices when training model-based entities in an IVA, Best practices when building rule-based entities in an IVA, and Best practices for cleaning up training data in an IVA.

1. Enable training of your text analytics model for the IVA.
   For more information, see Enabling training data recording for an IVA.
2. Improve the IVA model by providing sample training records.
   For more information, see Creating training data manually for an IVA.
3. Update the training data by ensuring that the IVA detects the correct information by using text analysis.
   For more information, see Correcting training data in an IVA.
4. Optional: To copy the training data to another IVA, export and import the training records.
   This action makes the IVA easier to maintain and build in production, QA, and development environments. For more information, see Transferring training data to another IVA.
5. Make the IVA learn from the training data by building a text analytics model.
   This action improves the artificial intelligence of the system. For more information, see Applying changes to a text analytics model for an IVA.