Machine learning trained model

The machine learning trained models APIs enable you to perform model management operations.

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13 endpoints

Clear trained model deployment cache
- POST /_ml/trained_models/{model_id}/deployment/cache/_clear
Get trained model configuration info
- GET /_ml/trained_models/{model_id}
Create a trained model
- PUT /_ml/trained_models/{model_id}
Delete an unreferenced trained model
- DELETE /_ml/trained_models/{model_id}
Create or update a trained model alias
- PUT /_ml/trained_models/{model_id}/model_aliases/{model_alias}
Delete a trained model alias
- DELETE /_ml/trained_models/{model_id}/model_aliases/{model_alias}
Get trained models usage info
- GET /_ml/trained_models/{model_id}/_stats
Evaluate a trained model
- POST /_ml/trained_models/{model_id}/_infer
Create part of a trained model definition
- PUT /_ml/trained_models/{model_id}/definition/{part}
Create a trained model vocabulary
- PUT /_ml/trained_models/{model_id}/vocabulary
Start a trained model deployment
- POST /_ml/trained_models/{model_id}/deployment/_start
Stop a trained model deployment
- POST /_ml/trained_models/{model_id}/deployment/_stop
Update a trained model deployment
- POST /_ml/trained_models/{model_id}/deployment/_update