# Get trained model configuration info


**GET /_ml/trained_models/{model_id}**

**All methods and paths for this operation:**

<div>
                      <span class="operation-verb get">GET</span>
                      <span class="operation-path">/_ml/trained_models</span>
                      </div>
                    <div>
                      <span class="operation-verb get">GET</span>
                      <span class="operation-path">/_ml/trained_models/{model_id}</span>
                      </div>

## Required authorization

* Cluster privileges: `monitor_ml`



## Servers
- http://api.example.com: http://api.example.com ()


## Authentication methods
- Api key auth
- Basic auth
- Bearer auth


## Parameters

### Path parameters
- **model_id** (string | array[string])
  The unique identifier of the trained model or a model alias.

  You can get information for multiple trained models in a single API
  request by using a comma-separated list of model IDs or a wildcard
  expression.

### Query parameters
- **allow_no_match** (boolean)
  Specifies what to do when the request:

  - Contains wildcard expressions and there are no models that match.
  - Contains the _all string or no identifiers and there are no matches.
  - Contains wildcard expressions and there are only partial matches.

  If true, it returns an empty array when there are no matches and the
  subset of results when there are partial matches.
- **decompress_definition** (boolean)
  Specifies whether the included model definition should be returned as a
  JSON map (true) or in a custom compressed format (false).
- **exclude_generated** (boolean)
  Indicates if certain fields should be removed from the configuration on
  retrieval. This allows the configuration to be in an acceptable format to
  be retrieved and then added to another cluster.
- **from** (number)
  Skips the specified number of models.
- **include** (string)
  A comma delimited string of optional fields to include in the response
  body.

  Supported values include:
    - `definition`: Includes the model definition.
    - `feature_importance_baseline`: Includes the baseline for feature importance values.
    - `hyperparameters`: Includes the information about hyperparameters used to train the model.
  This information consists of the value, the absolute and relative
  importance of the hyperparameter as well as an indicator of whether it was
  specified by the user or tuned during hyperparameter optimization.
    - `total_feature_importance`: Includes the total feature importance for the training data set. The
  baseline and total feature importance values are returned in the metadata
  field in the response body.
    - `definition_status`: Includes the model definition status.

- **size** (number)
  Specifies the maximum number of models to obtain.
- **tags** (string | array[string])
  A comma delimited string of tags. A trained model can have many tags, or
  none. When supplied, only trained models that contain all the supplied
  tags are returned.


## Responses
### 200


#### Body: application/json (object)
- **count** (number)

- **trained_model_configs** (array[object])
  An array of trained model resources, which are sorted by the model_id value in ascending order.


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