Delete an unreferenced trained model

DELETE /_ml/trained_models/{model_id}

Auth

The request deletes a trained inference model that is not referenced by an ingest pipeline.

Required privileges

Cluster privileges manage_ml

Path parameters

model_id string required: The unique identifier of the trained model.

Query parameters

force boolean: Forcefully deletes a trained model that is referenced by ingest pipelines or has a started deployment.
timeout union oneOf · default: 30s: Period to wait for a response. If no response is received before the timeout expires, the request fails and returns an error.; Values: -1 0

Response

application/json

acknowledged boolean required: For a successful response, this value is always true. On failure, an exception is returned instead.

View as Markdown

Examples

Request Console 1 / 8 languages

Console Kibana Dev Tools

DELETE _ml/trained_models/regression-job-one-1574775307356

JavaScript Elasticsearch JavaScript Client

const response = await client.ml.deleteTrainedModel({
  model_id: "regression-job-one-1574775307356",
});

Python Elasticsearch Python Client

resp = client.ml.delete_trained_model(
    model_id="regression-job-one-1574775307356",
)

curl Shell

curl -X DELETE "$ELASTICSEARCH_URL/_ml/trained_models/regression-job-one-1574775307356" \
  -H "Authorization: ApiKey $ELASTIC_API_KEY"

Java Elasticsearch Java Client

client.ml().deleteTrainedModel(d -> d
    .modelId("regression-job-one-1574775307356")
);

C# Elasticsearch .NET Client

var response = await client.MachineLearning.DeleteTrainedModelAsync(modelId: "regression-job-one-1574775307356");

PHP Elasticsearch PHP Client

$resp = $client->ml()->deleteTrainedModel([
    "model_id" => "regression-job-one-1574775307356",
]);

Ruby Elasticsearch Ruby Client

response = client.ml.delete_trained_model(
  model_id: "regression-job-one-1574775307356"
)

Response

A successful response when deleting an existing trained inference model.

{
  "acknowledged": true
}