Delete an unreferenced trained model

DELETE /_ml/trained_models/{model_id}

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

Required authorization

Authentication

Api key

Authorization: <value>

Elasticsearch APIs support key-based authentication. You must create an API key and use the encoded value in the request header. For example:

		curl -X GET "${ES_URL}/_cat/indices?v=true" \
  -H "Authorization: ApiKey ${API_KEY}"

To get API keys, use the /_security/api_key APIs.

Basic

Authorization: Basic <credentials>

Bearer

Authorization: Bearer <token>

Elasticsearch APIs support the use of bearer tokens in the Authorization HTTP header to authenticate with the API. For examples, refer to Token-based authentication services

Path parameters

Query parameters

Response

application/json

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
}