Delete a Dataset

Keep the following points in mind when deleting a dataset.

If a dataset is being trained and has an associated model with a status of QUEUED or RUNNING, you must wait until the training is complete before you can delete the dataset.
If you want to delete a dataset and the models associated with it, delete the models first. Deleting a dataset doesn't delete the models created from that dataset. After you delete a dataset, you can still make predictions against the associated models, but you lose the ability to list the models for the deleted dataset.
After you delete a dataset, use the id to get the status of the deletion. See Get Deletion Status.

Response Body

Name	Type	Description	Available Version
`deletedObjectId`	string	ID of the object deleted. When you delete a dataset, this value is the dataset ID.	2.0
`id`	string	ID of the deletion. Use this ID to query the status of the deletion and when it's complete.	2.0
`message`	string	Additional information about the dataset deletion.	2.0
`object`	string	Object returned; in this case, `deletion`.	2.0
`organizationId`	integer	ID of the org to which the dataset belongs.	2.0
`progress`	integer	How far the dataset deletion has progressed. Values are between 0–1.	2.0
`status`	string	Status of the dataset deletion. When you delete a dataset, this value is `QUEUED`.	2.0
`type`	string	Object that's being deleted. When you delete a dataset, this value is `DATASET`.	2.0