- Getting Started
- Administration
- Manage Sources and Datasets
- Understanding the data structure and permissions
- Create a data source in the GUI
- Uploading a CSV file into a source
- Create a new dataset
- Multilingual sources and datasets
- Enabling sentiment on a dataset
- Amend a dataset's settings
- Delete messages via the UI
- Delete a dataset
- Export a dataset
- Using Exchange Integrations
- Preparing Data for .CSV Upload
- Model Training and Maintenance
- Understanding labels, entities and metadata
- Label hierarchy and best practice
- Defining your taxonomy objectives
- Analytics vs. automation use cases
- Turning your objectives into labels
- Building your taxonomy structure
- Taxonomy design best practice
- Importing your taxonomy
- Overview of the model training process
- Generative Annotation (NEW)
- Understanding the status of your dataset
- Model training and labelling best practice
- Training with label sentiment analysis enabled
- Train
- Introduction to 'Refine'
- Precision and recall explained
- Precision and recall
- How does Validation work?
- Understanding and improving model performance
- Why might a label have low average precision?
- Training using 'Check label' and 'Missed label'
- Training using Teach label (Refine)
- Training using Search (Refine)
- Understanding and increasing coverage
- Improving Balance and using 'Rebalance'
- When to stop training your model
- Using Analytics & Monitoring
- Automations and Communications Mining
- FAQs and More
Create a stream
User permissions required: 'Streams admin'.
UPDATE: Streams were previously known as Triggers in the platform. They've been renamed to better reflect the functionality that they provide for our users. This name change won't affect existing API routes. The trigger routes still exist, and new streams routes have been added that are identical in functionality. We'll gradually migrate our customers to these new streams routes in the coming months.
Create a stream
You need to have a Pinned Model.
- Select the New stream + button at the top of the streams page. This opens the Create a stream modal.
Create stream modal
- Give the stream a title and a description.
- Set an API name.
- Specify the model (labeller) version to use (this is very important).
- Use the filters bar on the left-hand-side to set user-property filters which must be satisfied for messages to enter the queue for the stream.
- Select a label and a confidence threshold:
Setting a confidence threshold
Setting a threshold means that for the message to enter the queue for the stream, the platform must predict that label with a confidence equal to (or greater than) the set threshold.
The platform predicts the number of false positives and false negatives the stream would get wrong or miss.
The default threshold for a label is 100%. At this point it is disabled and the stream will not return predictions for the label.If the threshold is set to less than 100%, then the stream will return predictions for the labels that are above the threshold. - Select the tick button to create the stream.
