communications-mining
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- Getting started
- 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
- 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
- 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)
- 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
Communications Mining User Guide
Last updated Feb 10, 2025
Amend dataset settings
User permissions required: Modify datasets.
There are two ways to amend the settings of a dataset:
- Via the dataset card on the Your datasets page:
Update Dataset modal
- Navigate to the datasets page by clicking the UiPath® Communications Mining logo on the top left.
- Click the three dots from the top right-hand corner of the individual dataset card.
- Select Edit. You can change the following fields:
- Title. A short description of the dataset.
- Description. A more detailed description of the dataset.
- Sources. Select the sources to be included in the taxonomy.
- Preferred date and currency format.
- Select Update dataset.
- Via the dataset settings page:
- Select Settings on the top navigation bar.
- In the dataset, you are able to update the following dataset elements:
- Dataset name
- Description
- Sources
- Use the toggle to enable or disable the Use
generative AI features option. The features provide 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.
If you use the preview generative extraction mode, this uses a third-party LLM, and requires you to turn on the toggle for Use preview generative extraction model.
Note: To disable third-party LLMs, make sure you turn off the Use Generative AI Features toggle for a dataset. - Select Update to save the changes of the dataset.
- 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.
