Path parameters

• id string Required

  Identifier for the data frame analytics job. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters.

Responses

• 200 application/json
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  • authorization object
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    • api_key object

      If an API key was used for the most recent update to the job, its name and identifier are listed in the response.

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      • id string Required

        The identifier for the API key.

      • name string Required

        The name of the API key.

    • roles array[string]

      If a user ID was used for the most recent update to the job, its roles at the time of the update are listed in the response.

    • service_account string

      If a service account was used for the most recent update to the job, the account name is listed in the response.

  • allow_lazy_start boolean Required
  • analysis object Required
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    • classification 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.

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      • compute_feature_influence boolean

        Specifies whether the feature influence calculation is enabled.

        Default value is true.

      • feature_influence_threshold number

        The minimum outlier score that a document needs to have in order to calculate its feature influence score. Value range: 0-1.

        Default value is 0.1.

      • method string

        The method that outlier detection uses. Available methods are lof, ldof, distance_kth_nn, distance_knn, and ensemble. The default value is ensemble, which means that outlier detection uses an ensemble of different methods and normalises and combines their individual outlier scores to obtain the overall outlier score.

        Default value is ensemble.

      • n_neighbors number

        Defines the value for how many nearest neighbors each method of outlier detection uses to calculate its outlier score. When the value is not set, different values are used for different ensemble members. This default behavior helps improve the diversity in the ensemble; only override it if you are confident that the value you choose is appropriate for the data set.

      • outlier_fraction number

        The proportion of the data set that is assumed to be outlying prior to outlier detection. For example, 0.05 means it is assumed that 5% of values are real outliers and 95% are inliers.

      • standardization_enabled boolean

        If true, the following operation is performed on the columns before computing outlier scores: (x_i - mean(x_i)) / sd(x_i).

        Default value is true.

    • regression object
  • analyzed_fields object
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    • 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.

  • create_time number Required
  • description string
  • dest object Required
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    • index string Required

      Defines the destination index to store the results of the data frame analytics job.

    • results_field string

      Defines the name of the field in which to store the results of the analysis. Defaults to ml.

  • id string Required
  • max_num_threads number Required
  • model_memory_limit string Required
  • source object Required
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    • 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.

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      • * object Additional properties
    • _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.

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      • 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.

    • 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
  • version string Required