# Using the additionalParams object to tune the export of model-training information
<a name="machine-learning-additionalParams"></a>

The `additionalParams` object contains fields that you can use to specify machine-learning class labels and features for training purposes and guide the creation of a training data configuration file.

The export process cannot automatically infer which node and edge properties should be the machine learning class labels to serve as examples for training purposes. It also cannot automatically infer the best feature encoding for numeric, categorical and text properties, so you need to supply hints using fields in the `additionalParams` object to specify these things, or to override the default encoding.

For property-graph data, the top-level structure of `additionalParams` in an export request might look like this:

```
{
  "command": "export-pg",
  "outputS3Path": "s3://(your Amazon S3 bucket)/neptune-export",
  "params": {
    "endpoint": "(your Neptune endpoint DNS name)",
    "profile": "neptune_ml"
  },
  "additionalParams": {
      "neptune_ml": {
        "version": "v2.0",
        "targets": [ (an array of node and edge class label targets) ],
        "features": [ (an array of node feature hints) ]
    }
  }
}
```

For RDF data, its top-level structure might look like this:

```
{
  "command": "export-rdf",
  "outputS3Path": "s3://(your Amazon S3 bucket)/neptune-export",
  "params": {
    "endpoint": "(your Neptune endpoint DNS name)",
    "profile": "neptune_ml"
  },
  "additionalParams": {
      "neptune_ml": {
        "version": "v2.0",
        "targets": [ (an array of node and edge class label targets) ]
    }
  }
}
```

You can also supply multiple export configurations, using the `jobs` field:

```
{
  "command": "export-pg",
  "outputS3Path": "s3://(your Amazon S3 bucket)/neptune-export",
  "params": {
    "endpoint": "(your Neptune endpoint DNS name)",
    "profile": "neptune_ml"
  },
  "additionalParams" : {
    "neptune_ml" : {
      "version": "v2.0",
      "jobs": [
        {
          "name" : "(training data configuration name)",
          "targets": [ (an array of node and edge class label targets) ],
          "features": [ (an array of node feature hints) ]
        },
        {
          "name" : "(another training data configuration name)",
          "targets": [ (an array of node and edge class label targets) ],
          "features": [ (an array of node feature hints) ]
        }
      ]
    }
  }
}
```

# Top-level elements in the neptune\$1ml field in additionalParams
<a name="machine-learning-neptune_ml-top-level"></a>

## The version element in neptune\$1ml
<a name="machine-learning-neptune_ml-version"></a>

Specifies the version of training data configuration to generate.

(*Optional*), *Type*: string, *Default*: "v2.0".

If you do include `version`, set it to `v2.0`.

## The jobs field in neptune\$1ml
<a name="machine-learning-neptune_ml-jobs"></a>

Contains an array of training-data configuration objects, each of which defines a data processing job, and contains:
+ **`name`**   –   The name of the training data configuration to be created.

   For example, a training data configuration with the name "job-number-1" results in a training data configuration file named `job-number-1.json`.
+ **`targets`**   –   A JSON array of node and edge class label targets that represent the machine-learning class labels for training purposes. See [The targets field in a neptune\$1ml object](machine-learning-neptune_ml-targets.md).
+ **`features`**   –   A JSON array of node property features. See [The features field in neptune\$1ml](machine-learning-neptune_ml-features.md).