elasticsearch/docs/reference/ml/df-analytics/apis/explain-dfanalytics.asciidoc

[role="xpack"]
[testenv="platinum"]
[[explain-dfanalytics]]
= Explain {dfanalytics} API

[subs="attributes"]
++++
<titleabbrev>Explain {dfanalytics}</titleabbrev>
++++

Explains a {dataframe-analytics-config}.


[[ml-explain-dfanalytics-request]]
== {api-request-title}

`GET _ml/data_frame/analytics/_explain` +

`POST _ml/data_frame/analytics/_explain` +

`GET _ml/data_frame/analytics/<data_frame_analytics_id>/_explain` +

`POST _ml/data_frame/analytics/<data_frame_analytics_id>/_explain`


[[ml-explain-dfanalytics-prereq]]
== {api-prereq-title}

Requires the following privileges:

* cluster: `monitor_ml` (the `machine_learning_user` built-in role grants this 
  privilege)
* source indices: `read`, `view_index_metadata`


[[ml-explain-dfanalytics-desc]]
== {api-description-title}

This API provides explanations for a {dataframe-analytics-config} that either 
exists already or one that has not been created yet.
The following explanations are provided:

* which fields are included or not in the analysis and why,
* how much memory is estimated to be required. The estimate can be used when 
  deciding the appropriate value for `model_memory_limit` setting later on.

If you have object fields or fields that are excluded via source filtering,
they are not included in the explanation.


[[ml-explain-dfanalytics-path-params]]
== {api-path-parms-title}

`<data_frame_analytics_id>`::
(Optional, string)
include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=job-id-data-frame-analytics]

[[ml-explain-dfanalytics-request-body]]
== {api-request-body-title}

A {dataframe-analytics-config} as described in <<put-dfanalytics>>.
Note that `id` and `dest` don't need to be provided in the context of this API.

[role="child_attributes"]
[[ml-explain-dfanalytics-results]]
== {api-response-body-title}

The API returns a response that contains the following:

`field_selection`::
(array)
An array of objects that explain selection for each field, sorted by 
the field names.
+
.Properties of `field_selection` objects
[%collapsible%open]
====
`is_included`:::
(Boolean) Whether the field is selected to be included in the analysis.

`is_required`:::
(Boolean) Whether the field is required.

`feature_type`:::
(string) The feature type of this field for the analysis. May be `categorical` 
or `numerical`.

`mapping_types`:::
(string) The mapping types of the field.

`name`:::
(string) The field name.

`reason`:::
(string) The reason a field is not selected to be included in the analysis.
====

`memory_estimation`::
(object) 
An object containing the memory estimates.
+
.Properties of `memory_estimation`
[%collapsible%open]
====
`expected_memory_with_disk`:::
(string) Estimated memory usage under the assumption that overflowing to disk is 
allowed during {dfanalytics}. `expected_memory_with_disk` is usually smaller 
than `expected_memory_without_disk` as using disk allows to limit the main 
memory needed to perform {dfanalytics}.

`expected_memory_without_disk`:::
(string) Estimated memory usage under the assumption that the whole 
{dfanalytics} should happen in memory (i.e. without overflowing to disk).
====


[[ml-explain-dfanalytics-example]]
== {api-examples-title}

[source,console]
--------------------------------------------------
POST _ml/data_frame/analytics/_explain
{
  "source": {
    "index": "houses_sold_last_10_yrs"
  },
  "analysis": {
    "regression": {
      "dependent_variable": "price"
    }
  }
}
--------------------------------------------------
// TEST[skip:TBD]


The API returns the following results:

[source,console-result]
----
{
  "field_selection": [
    {
      "field": "number_of_bedrooms",
      "mappings_types": ["integer"],
      "is_included": true,
      "is_required": false,
      "feature_type": "numerical"
    },
    {
      "field": "postcode",
      "mappings_types": ["text"],
      "is_included": false,
      "is_required": false,
      "reason": "[postcode.keyword] is preferred because it is aggregatable"
    },
    {
      "field": "postcode.keyword",
      "mappings_types": ["keyword"],
      "is_included": true,
      "is_required": false,
      "feature_type": "categorical"
    },
    {
      "field": "price",
      "mappings_types": ["float"],
      "is_included": true,
      "is_required": true,
      "feature_type": "numerical"
    }
  ],
  "memory_estimation": {
    "expected_memory_without_disk": "128MB",
    "expected_memory_with_disk": "32MB"
  }
}
----