communications-mining
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- Introduction
- Balance
- Clusters
- Concept drift
- Coverage
- Datasets
- General fields (previously entities)
- Labels (predictions, confidence levels, hierarchy, etc.)
- Models
- Streams
- Model Rating
- Projects
- Precision
- Recall
- Annotated and unannotated messages
- Extraction Fields
- Sources
- Taxonomies
- Training
- True and false positive and negative predictions
- Validation
- Messages
- Access Control and Administration
- Manage sources and datasets
- Understanding the data structure and permissions
- Create or delete a data source in the GUI
- Uploading a CSV file into a source
- Preparing data for .CSV upload
- Create a new dataset
- Multilingual sources and datasets
- Enabling sentiment on a dataset
- Amend dataset settings
- Delete messages via the UI
- Delete a dataset
- Export a dataset
- Using Exchange Integrations
- Model training and maintenance
- Understanding labels, general fields, and metadata
- Label hierarchy and best practices
- Analytics vs. automation use cases
- Turning your objectives into labels
- Overview of the model training process
- Generative Annotation (NEW)
- Dastaset status
- Model training and annotating best practice
- Training with label sentiment analysis enabled
- Understanding data requirements
- 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 general fields
- Generative extraction
- Using analytics and monitoring
- Automations and Communications Mining
- Licensing information
- FAQs and more
Important :
Communications Mining is now part of UiPath IXP. Check the User Guide Introduction for more details.
Communications Mining User Guide
Last updated Mar 25, 2025
Amend dataset settings
Note: You must have the Modify datasets permissions assigned to
amend the settings of a dataset.
To amend the settings of a dataset, proceed as follows:
- Select the ellipsis for a specific dataset from the homepage.
- Select Dataset Settings, which redirects you to the Settings page.
- Update the following dataset elements
in the Dataset tab:
- Dataset name
- Description
- Sources
- Use the toggle to enable or disable
the Use generative AI features option. The feature provides design-time and
run-time capabilities, which use third-party generative AI models. These
significantly improve time-to-value with features such as Generative
annotation.
Note: To disable third-party LLMs, make sure you turn off the Use Generative AI Features toggle for a dataset.
- Select Update.
Note:
- To update general fields, check Enabling, disabling, updating and creating general fields, and go to Taxonomy, then General fields.
- To modify labels or extraction fields, go to Taxonomy, then Labels and extraction fields.
