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| title | slug | 
|---|---|
| createMlModel | /main-concepts/metadata-standard/schemas/api/data/createmlmodel | 
CreateMlModelRequest
Create Ml Model entity request
Properties
- name: Name that identifies this ML model. Refer to ../../type/basic.json#/definitions/entityName.
- displayName(string): Display Name that identifies this ML model. It could be title or label from the source services.
- description: Description of the ML model instance. How it was trained and for what it is used. Refer to ../../type/basic.json#/definitions/markdown.
- algorithm(string): Algorithm used to train the ML Model.
- mlFeatures(array): Features used to train the ML Model. Default:- None.- Items: Refer to ../../entity/data/mlmodel.json#/definitions/mlFeature.
 
- target: For supervised ML Models, the value to estimate. Refer to ../../type/basic.json#/definitions/entityName.
- mlHyperParameters(array): Hyper Parameters used to train the ML Model. Default:- None.- Items: Refer to ../../entity/data/mlmodel.json#/definitions/mlHyperParameter.
 
- dashboard: Performance Dashboard URL to track metric evolution. Refer to ../../type/entityReference.json.
- mlStore: Location containing the ML Model. It can be a storage layer and/or a container repository. Refer to ../../entity/data/mlmodel.json#/definitions/mlStore.
- server: Endpoint that makes the ML Model available, e.g,. a REST API serving the data or computing predictions. Refer to ../../type/basic.json#/definitions/href.
- tags(array): Tags for this ML Model. Default:- None.- Items: Refer to ../../type/tagLabel.json.
 
- owner: Owner of this database. Refer to ../../type/entityReference.json.
- service: Link to the pipeline service where this pipeline is hosted in. Refer to ../../type/entityReference.json.
Documentation file automatically generated at 2022-07-14 10:51:34.749986.
