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
- Reviewed and unreviewed messages
- Sources
- Taxonomies
- Training
- True and false positive and negative predictions
- Validation
- Messages
- 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
- Delete a source
- Export a dataset
- Using Exchange Integrations
- Preparing data for .CSV upload
- Model training and maintenance
- Understanding labels, general fields 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 annotating 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 general fields
- Generative extraction
- Using analytics and monitoring
- Automations and Communications Mining
- Licensing information
- FAQs and more
Communications Mining User Guide
Last updated Nov 7, 2024
Delete a dataset
User permissions required: Datasets admin.
Just like with updating a dataset, you have two options to permanently delete a dataset:
- Via the dataset card on the Your datasets page:
- Go to the main datasets page (you can navigate here by clicking the UiPath® Communications Mining logo at the top of your page).
- Select the ellipsis vertical icon, then Delete in the corner of the individual dataset card.
- Enter the name of the dataset
in the pop-up input box.
- Select Delete dataset
to confirm deletion.
Note: Deleting a dataset is permanent.
Dataset card with delete option
- Via the individual dataset settings page
- Once you select an individual dataset, go to the Settings page via the top navigation bar. You are redirected to the Dataset tab.
- Select Delete dataset permanently at the bottom of the page.
- Enter the full name of the
dataset in the pop-up input box. Select Delete dataset to confirm
deletion.
Note: Deleting a dataset is permanent.
Delete dataset modal
