Preview features used by data frame analytics Generally available; Added in 7.13.0

POST /_ml/data_frame/analytics/{id}/_preview
Api key auth Basic auth Bearer auth

All methods and paths for this operation:

GET /_ml/data_frame/analytics/_preview

POST /_ml/data_frame/analytics/_preview
GET /_ml/data_frame/analytics/{id}/_preview
POST /_ml/data_frame/analytics/{id}/_preview

Preview the extracted features used by a data frame analytics config.

Required authorization

  • Cluster privileges: monitor_ml

Path parameters

  • id string Required

    Identifier for the data frame analytics job.

application/json

Body

  • config object

    A data frame analytics config as described in create data frame analytics jobs. Note that id and dest don’t need to be provided in the context of this API.

    Hide config attributes Show config attributes object
    • source object Required
      Hide source attributes Show source attributes object
      • index string | array[string] Required

        Index or indices on which to perform the analysis. It can be a single index or index pattern as well as an array of indices or patterns. NOTE: If your source indices contain documents with the same IDs, only the document that is indexed last appears in the destination index.

      • runtime_mappings object

        Definitions of runtime fields that will become part of the mapping of the destination index.

      • _source object

        Specify includes and/or `excludes patterns to select which fields will be present in the destination. Fields that are excluded cannot be included in the analysis.

      • query object

        The Elasticsearch query domain-specific language (DSL). This value corresponds to the query object in an Elasticsearch search POST body. All the options that are supported by Elasticsearch can be used, as this object is passed verbatim to Elasticsearch. By default, this property has the following value: {"match_all": {}}.

        Query DSL
    • analysis object Required
      Hide analysis attribute Show analysis attribute object
      • outlier_detection object

        The configuration information necessary to perform outlier detection. NOTE: Advanced parameters are for fine-tuning classification analysis. They are set automatically by hyperparameter optimization to give the minimum validation error. It is highly recommended to use the default values unless you fully understand the function of these parameters.

    • model_memory_limit string
    • max_num_threads number
    • analyzed_fields object
      Hide analyzed_fields attributes Show analyzed_fields attributes object
      • includes array[string]

        An array of strings that defines the fields that will be excluded from the analysis. You do not need to add fields with unsupported data types to excludes, these fields are excluded from the analysis automatically.

      • excludes array[string]

        An array of strings that defines the fields that will be included in the analysis.

Responses

  • 200 application/json
    Hide response attribute Show response attribute object
    • feature_values array[object] Required

      An array of objects that contain feature name and value pairs. The features have been processed and indicate what will be sent to the model for training.

      Hide feature_values attribute Show feature_values attribute object
      • * string Additional properties
POST /_ml/data_frame/analytics/{id}/_preview 
POST _ml/data_frame/analytics/_preview
{
  "config": {
    "source": {
      "index": "houses_sold_last_10_yrs"
    },
    "analysis": {
      "regression": {
        "dependent_variable": "price"
      }
    }
  }
}
resp = client.ml.preview_data_frame_analytics(
    config={
        "source": {
            "index": "houses_sold_last_10_yrs"
        },
        "analysis": {
            "regression": {
                "dependent_variable": "price"
            }
        }
    },
)
const response = await client.ml.previewDataFrameAnalytics({
  config: {
    source: {
      index: "houses_sold_last_10_yrs",
    },
    analysis: {
      regression: {
        dependent_variable: "price",
      },
    },
  },
});
response = client.ml.preview_data_frame_analytics(
  body: {
    "config": {
      "source": {
        "index": "houses_sold_last_10_yrs"
      },
      "analysis": {
        "regression": {
          "dependent_variable": "price"
        }
      }
    }
  }
)
$resp = $client->ml()->previewDataFrameAnalytics([
    "body" => [
        "config" => [
            "source" => [
                "index" => "houses_sold_last_10_yrs",
            ],
            "analysis" => [
                "regression" => [
                    "dependent_variable" => "price",
                ],
            ],
        ],
    ],
]);
curl -X POST -H "Authorization: ApiKey $ELASTIC_API_KEY" -H "Content-Type: application/json" -d '{"config":{"source":{"index":"houses_sold_last_10_yrs"},"analysis":{"regression":{"dependent_variable":"price"}}}}' "$ELASTICSEARCH_URL/_ml/data_frame/analytics/_preview"
client.ml().previewDataFrameAnalytics(p -> p
    .config(c -> c
        .source(s -> s
            .index("houses_sold_last_10_yrs")
        )
        .analysis(a -> a
            .regression(r -> r
                .dependentVariable("price")
            )
        )
    )
);
Request example
An example body for a `POST _ml/data_frame/analytics/_preview` request. 
{
  "config": {
    "source": {
      "index": "houses_sold_last_10_yrs"
    },
    "analysis": {
      "regression": {
        "dependent_variable": "price"
      }
    }
  }
}