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Communications Mining User Guide
Last updated Nov 27, 2024

Overview of the model training process

Training a model can be broken down into a three phase process:



In the first instance, it's good practice to go through these steps in order, but this can be an iterative process. You may find in time that for different labels, you may chop and change the different steps as you become more familiar with the platform.

Discover

Discover is where similar intents, patterns and conversation themes are grouped together into ‘clusters’. This is the starting point and is used to quickly build an initial model where you analyse your data and tag each cluster with one or more label that applies.

Explore

After reviewing clusters in Discover, Explore is used to further train your model. Most of your time will be spent here reviewing messages, adding labels, and improving the model’s understanding of your data.

Refine

This stage is used to assess and improve the overall performance of your model. In this stage, the platform provides guided feedback on the health of your model via the Model Rating, including performance issues and the next best actions to resolve them.

Discover, Explore and Refine phase can now be completed using the Train tab. For more information, see the Train page.

Prune / Re-organise

This is a part of the model training process that you can do at any time - renaming, merging or deleting labels as you go through the process. The process is explained in detail in the Explore page.

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