Create or update a trained model alias Added in 7.13.0
A trained model alias is a logical name used to reference a single trained model. You can use aliases instead of trained model identifiers to make it easier to reference your models. For example, you can use aliases in inference aggregations and processors. An alias must be unique and refer to only a single trained model. However, you can have multiple aliases for each trained model. If you use this API to update an alias such that it references a different trained model ID and the model uses a different type of data frame analytics, an error occurs. For example, this situation occurs if you have a trained model for regression analysis and a trained model for classification analysis; you cannot reassign an alias from one type of trained model to another. If you use this API to update an alias and there are very few input fields in common between the old and new trained models for the model alias, the API returns a warning.
Path parameters
-
The identifier for the trained model that the alias refers to.
-
The alias to create or update. This value cannot end in numbers.
Query parameters
-
reassign boolean
Specifies whether the alias gets reassigned to the specified trained model if it is already assigned to a different model. If the alias is already assigned and this parameter is false, the API returns an error.
curl \
-X PUT http://api.example.com/_ml/trained_models/{model_id}/model_aliases/{model_alias}{
"acknowledged": true
}